TY - GEN A1 - Sebastia-Saez, Daniel A1 - Hernandez, Leonor A1 - Arellano-García, Harvey A1 - Enrique Julia, Jose T1 - Numerical and experimental characterization of the hydrodynamics and drying kinetics of a barbotine slurry spray T2 - Chemical Engineering Science N2 - Spray drying is a basic unit operation in several process industries such as food, pharmaceutical, ceramic, and others. In this work, a Eulerian-Lagrangian three-phase simulation is presented to study the drying process of barbotine slurry droplets for the production of ceramic tiles. To this end, the simulated velocity field produced by a spray nozzle located at the Institute of Ceramic Technology in Castelló (Spain) is benchmarked against measurements obtained by means of laser Doppler anemometry in order to validate the numerical model. Also, the droplet size distribution generated by the nozzle is obtained at operating conditions by means of laser diffraction and the data obtained are compared qualitatively to those found in the literature. The characteristic Rosin-Rammler droplet size from the distribution is introduced thereafter in the three-phase simulation to analyse the drying kinetics of individual droplets. The model predicts the theoretical linear evolution of the square diameter (D²-law), and the temperature and mass exchange with the environment. The proposed model is intended to support the design and optimization of industrial spray dryers. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/pii/S0009250918308170?via%3Dihub U6 - https://doi.org/10.1016/j.ces.2018.11.040 SN - 1873-4405 SN - 0009-2509 VL - 195 SP - 83 EP - 94 ER - TY - GEN A1 - Foster, Niall A1 - Sebastia-Saez, Daniel A1 - Arellano-García, Harvey T1 - Fractal branch-like fractal shell-and-tube heat exchangers: A CFD study of the shell side performance T2 - IFAC-PapersOnLine N2 - Nature has provided some of the most ingenious and elegant solutions to complex problems over millions of years of refining through evolution. The adaptation of Nature´s solutions to engineering problems is a recent trend which has opened opportunities for improvement in many areas ranging from Architecture to Chemical Engineering. In particular, the use of fractal geometries on heat exchangers is a recent design trend. Recent investigations highlight the benefit of implementing fractal-based geometries on the tube side of shell and tube heat exchangers. A complete evaluation of such devices by assessing the performance of the shell side has not been undertaken, though. Here, we present a systematic numerical assessment of the shell side of a tree-like shaped heat exchanger. Key performance parameters, i.e. temperature change, pressure drop and coefficient of performance, are obtained and compared to those of a straight tube, in order to fully understand the potential of the application of fractal-based shapes to the design of heat exchangers. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/pii/S2405896319301296?via%3Dihub U6 - https://doi.org/10.1016/j.ifacol.2019.06.044 SN - 2405-8963 VL - 52 IS - 1 SP - 100 EP - 105 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Masham, Elliot A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Centralised versus localised supply chain management using a flow configuration model T2 - Computer Aided Chemical Engineering N2 - Traditional food supply chains are often centralised and global in nature. Moreover they require a large amount of resource which is an issue in a time with increasing need for more sustainable food supply chains. A solution is to use localised food supply chains, an option theorised to be more sustainable, yet not proven. Therefore, this paper compares the two systems to investigate which one is more environmentally friendly, cost efficient and resilient to disruption risks. This comparison between the two types of supply chains, is performed using MILP models for an ice cream supply chain for the whole of England over the period of a year. The results obtained from the models show that the localised model performs best environmentally and economically, whilst the traditional, centralised supply chain performs best for resilience. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780128186343502319?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-818634-3.50231-9 SN - 1570-7946 VL - 46 SP - 1381 EP - 1386 ER - TY - GEN A1 - Yentumi, Richard A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Modelling and optimal operation of a natural gas fired natural draft heater T2 - Computer Aided Chemical Engineering N2 - Current industrial trends promote reduction of material and energy consumption of fossil fuel burning, and energy-intensive process equipment. It is estimated that approximately 75% of the energy consumption in hydrocarbon processing facilities is used by such equipment as fired heater, hence even small improvements in the energy conservation may lead to significant savings [1, 2]. In this work, a mathematical modelling and optimisation study is undertaken using gPROMS® ProcessBuilder® to determine the optimal operating conditions of an existing API 560 Type-E vertical-cylindrical type natural draft fired heater, in operation at the Atuabo Gas Processing Plant (GPP), in the Western Region of Ghana. It is demonstrated that the optimisation results in significant reduction of fuel gas consumption and operational costs. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/abs/pii/B978012818634350165X?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-818634-3.50165-X SN - 1570-7946 VL - 46 SP - 985 EP - 990 ER - TY - GEN A1 - Al-Hmoud, Aya A1 - Sebastia-Saez, Daniel A1 - Arellano-García, Harvey T1 - Comparative CFD analysis of thermal energy storage materials in photovoltaic/thermal panels T2 - Computer Aided Chemical Engineering N2 - Photovoltaic/thermal systems are a novel renewable energy approach to transform incident radiation into electricity and simultaneously store the excess thermal energy produced. Both sensible and latent heat storage materials have been investigated in the past for thermal storage; with desert sand having been recently considered as an efficient and inexpensive alternative. In this work, we use a transient Computational Fluid Dynamics simulation to compare the performance of desert sand to that of well-established phase-change materials used in photovoltaic/thermal systems. The simulation gives as a result the temperature profiles within the device as well as the time evolution of the charge/discharge cycles when using PCMs. The results show the suitability of desert sand as a thermal storage material to be used in photovoltaic/thermal systems. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780128186343501338?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-818634-3.50133-8 SN - 1570-7946 VL - 46 SP - 793 EP - 798 ER - TY - GEN A1 - Mechleri, Evgenia A1 - Sidnell, Tim A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Optimisation and control of a distributed energy resource network using Internet-of-Things technologies T2 - Computer Aided Chemical Engineering N2 - This work investigates the use of variable pricing to control electricity imported and exported to and from both fixed and unfixed distributed energy resource network designs within the UK residential sector. It was proven that networks which utilise much of their own energy and import little from the national grid are barely affected by variable import pricing, but are encouraged to export more energy to the grid by dynamic export pricing. Dynamic import and export pricing increased CO2 emissions due to feed-in tariffs which encourages CHP generation over lower-carbon technologies such as solar panels or wind turbines. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/abs/pii/B978012818634350014X?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-818634-3.50014-X SN - 1570-7946 VL - 46 SP - 79 EP - 84 ER - TY - GEN A1 - Arellano-García, Harvey A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia T1 - Devicification of Food Process Engineering T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - Food and beverages industry is facing major challenges in the years to come, as the world population is expected to grow, accompanied by a growing need for energy, feed and fuel. Much of the processing in the food industry is performed in small-scale decentralized plants, with relatively few possibilities of energy recovery. Innovation in areas such as process and product modeling, process intensification and process control enable the development of new manufacturing pathways, more efficient, versatile, selective and sustainable. Furthermore, the addition of Internet of Things elements and the way they connect to the physical process will ensure continuous communication between the various actors of the food value chain. This will enable the design of new compact, scalable, flexible, modular, and automated production equipment that will offer food manufacturers the ability to respond rapidly, economically, accurately and flexibly to the consumer demands. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/pii/B9780124095472144269?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-409547-2.14426-9 VL - 2019 ER - TY - BOOK A1 - Odriozola, José Antonio A1 - Ramirez Reina, Tomas A1 - Arellano-García, Harvey T1 - Engineering Solutions for CO2 Conversion N2 - A comprehensive guide that offers a review of the current technologies that tackle CO2 emissionsThe race to reduce CO2 emissions continues to be an urgent global challenge. "Engineering Solutions for CO2 Conversion" offers a thorough guide to the most current technologies designed to mitigate CO2 emissions ranging from CO2 capture to CO2 utilization approaches.... KW - CO2 conversion KW - CO2 emissions KW - reduce CO2 emissions KW - CO2 capture KW - computer modeling Y1 - 2021 SN - 978-3-527-34639-4 SN - 3-527-34639-2 PB - Wiley-VCH CY - Berlin ; Boston ER - TY - GEN A1 - Arellano-García, Harvey A1 - Ife, Maximilian R. A1 - Sanduk, Mohammed A1 - Sebastia-Saez, Daniel T1 - Hydrogen production via load-matched coupled solar-proton exchange membrane electrolysis using aqueous methanol T2 - Chemical engineering & technology N2 - This study investigates hydrogen production via a directly coupled solar‐PEM electrolysis system using aqueous methanol instead of water. The effect of load matching and methanol concentration on hydrogen production rates, electrolysis efficiency, and solar‐hydrogen efficiency was investigated. The electrolysis efficiencies were subsequently used in simulation studies to estimate production costs in scaled up systems. The results show that the added hydrogen production associated with the methanol solutions leads to favourable hydrogen production costs at smaller scales. Y1 - 2019 U6 - https://doi.org/10.1002/ceat.201900285 SN - 1521-4125 SN - 0930-7516 VL - 42 IS - 11 SP - 2340 EP - 2347 ER - TY - GEN A1 - Sebastia-Saez, Daniel A1 - Ramirez Reina, Tomas A1 - Silva, Ravi A1 - Arellano-García, Harvey T1 - Synthesis and characterisation of n‐octacosane@silica nanocapsules for thermal storage applications T2 - International Journal of Energy Research N2 - This work reports the synthesis and characterisation of a core‐shell n‐octacosane@silica nanoencapsulated phase‐change material obtained via interfacial hydrolysis and polycondensation of tetraethyl orthosilicate in miniemulsion. Silica has been used as the encapsulating material because of its thermal advantages relative to synthesised polymers. The material presents excellent heat storage potential, with a measured melting latent heat varying between 57.1 and 89.0 kJ kg−1 (melting point between 58.2°C and 59.9°C) and a small particle size (between 565 and 227 nm). Degradation of the n‐octacosane core starts between 150°C and 180°C. Also, the use of silica as shell material gives way to a heat conductivity of 0.796 W m−1 K−1 (greater than that of nanoencapsulated materials with polymeric shell). Charge/discharge cycles have been successfully simulated at low pressure to prove the suitability of the nanopowder as phase‐change material. Further research will be carried out in the future regarding the use of the synthesised material in thermal applications involving nanofluids. Y1 - 2019 UR - https://onlinelibrary.wiley.com/doi/10.1002/er.5039 U6 - https://doi.org/10.1002/er.5039 SN - 1099-114X SN - 0363-907X VL - 44 IS - 3 SP - 2306 EP - 2315 ER - TY - GEN A1 - Gehring, Nicole A1 - Dorneanu, Bogdan A1 - Manrique-Silupú, José A1 - Ipanaqué, William A1 - Arellano-García, Harvey T1 - Circular Economy in Banana Cultivation T2 - Computer Aided Chemical Engineering N2 - This paper examines the most important approaches that could be applied for the introduction of circular economy strategies for the banana production process in the region of Piura (Peru). Based on this, a framework for an optimized economic cycle that is able to conserve resources and minimize the capital investments of farmers, while simultaneously increasing their production, can be created. Challenges and potential solutions are discussed for the production stages. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780128233771502627?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-823377-1.50262-7 SN - 1570-7946 VL - 48 SP - 1567 EP - 1572 ER - TY - GEN A1 - Hamdan, Mustapha A1 - Sebastia-Saez, Daniel A1 - Hamdan, Malak A1 - Arellano-García, Harvey T1 - CFD Analysis of the Use of Desert Sand as Thermal Energy Storage Medium in a Solar Powered Fluidised Bed Harvesting Unit T2 - Computer Aided Chemical Engineering N2 - This work presents an Euler-Euler hydrodynamic and heat transfer numerical analysis of the multiphase flow involving desert sand and a continuous gas phase in a compact-size fluidised bed. The latter is part of a novel conceptual solar power design intended for domestic use. Desert sand is a highly available and unused resource with suitable thermal properties to be employed as thermal energy storage medium. It also allows for high working temperatures owing to its high resistance to agglomeration. Computational Fluid Dynamics simulations are used here to assess the heat transfer between desert sand and several proposed working fluids (including air, argon, nitrogen and carbon dioxide) to justify the design in terms of equipment dimensions and suitability of the materials used. The results show that the device can provide up to 1,031 kW when using carbon dioxide as the heat transfer fluid. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780128233771500598?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-823377-1.50059-8 SN - 1570-7946 VL - 48 SP - 349 EP - 354 ER - TY - GEN A1 - Menzhausen, Robert A1 - Merino, Manuel A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - A Fuzzy Control Approach for an Industrial Refrigeration System T2 - Computer Aided Chemical Engineering N2 - This contribution presents the development of a model for the refrigeration plant used for mangos, which is able to simulate both the chamber and the fruit temperatures. The model is developed from energy balances for each section of the refrigeration system and the fruits, and is the basis for the setup of a fuzzy controller, capable of regulating continuously the compressor’s frequency to achieve the desired temperature. The model is able to accurately predict the chamber temperature profiles, but is more sensitive when simulating the fruit temperature. The fuzzy controller is able to achieve the set-point more accurately and in a shorter time than the on/off control, achieving a decrease in energy consumption as well. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/abs/pii/B978012823377150210X?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-823377-1.50210-X SN - 1570-7946 VL - 48 SP - 1255 EP - 1260 ER - TY - GEN A1 - Arellano-García, Harvey A1 - Barz, Tilman A1 - Dorneanu, Bogdan A1 - Vassiliadis, Vassilios S. T1 - Real-time feasibility of nonlinear model predictive control for semi-batch reactors subject to uncertainty and disturbances T2 - Computers & Chemical Engineering N2 - This paper presents two nonlinear model predictive control based methods for solving closed-loop stochastic dynamic optimisation problems, ensuring both robustness and feasibility with respect to state output constraints. The first one is a new deterministic approach, using the wait-and-see strategy. The key idea is to specifically anticipate violation of output hard-constraints, which are strongly affected by instantaneous disturbances, by backing off of their bounds along the moving horizon. The second method is a stochastic approach to solve nonlinear chance-constrained dynamic optimisation problems under uncertainties. The key aspect is the explicit consideration of the stochastic properties of both exogenous and endogenous uncertainties in the problem formulation (here-and-now strategy). The approach considers a nonlinear relation between uncertain inputs and the constrained state outputs. The performance of the proposed methodologies is assessed via an application to a semi-batch reactor under safety constraints, involving strongly exothermic reactions. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/pii/S0098135419303333?via%3Dihub U6 - https://doi.org/10.1016/j.compchemeng.2019.106529 SN - 1873-4375 SN - 0098-1354 VL - 133 ER - TY - GEN A1 - Mohamed, Abdelrahim A1 - Ruan, Hang A1 - Heshmat Hassan Abdelwahab, Mohamed A1 - Dorneanu, Bogdan A1 - Xiao, Pei A1 - Arellano-García, Harvey A1 - Gao, Yang A1 - Tafazolli, Rahim T1 - An Inter-Disciplinary Modelling Approach in Industrial 5G/6G and Machine Learning Era T2 - 2020 IEEE International Conference on Communications Workshops (ICC Workshops) N2 - Recently, the fifth-generation (5G) cellular system has been standardised. As opposed to legacy cellular systems geared towards broadband services, the 5G system identifies key use cases for ultra-reliable and low latency communications (URLLC) and massive machine-type communications (mMTC). These intrinsic 5G capabilities enable promising sensor-based vertical applications and services such as industrial process automation. The latter includes autonomous fault detection and prediction, optimised operations and proactive control. Such applications enable equipping industrial plants with a sixth sense (6S) for optimised operations and fault avoidance. In this direction, we introduce an inter-disciplinary approach integrating wireless sensor networks with machine learning-enabled industrial plants to build a step towards developing this 6S technology. We develop a modular-based system that can be adapted to the vertical-specific elements. Without loss of generalisation, exemplary use cases are developed and presented including a fault detection/prediction scheme, and a sensor density-based boundary between orthogonal and non-orthogonal transmissions. The proposed schemes and modelling approach are implemented in a real chemical plant for testing purposes, and a high fault detection and prediction accuracy is achieved coupled with optimised sensor density analysis. Y1 - 2020 UR - https://ieeexplore.ieee.org/document/9145434 SN - 978-1-7281-7440-2 SN - 978-1-7281-7441-9 U6 - https://doi.org/10.1109/ICCWorkshops49005.2020.9145434 SN - 2474-9133 SP - 1 EP - 6 CY - Dublin, Ireland ER - TY - GEN A1 - Stephenson, Ted A1 - Carvalho Ellero, Caio A1 - Sebastia-Saez, Daniel A1 - Klymenko, Oleksiy A1 - Battley, Angela Maria A1 - Arellano-García, Harvey T1 - Numerical modelling of the interaction between eccrine sweat and textile fabric for the development of smart clothing T2 - International Journal of Clothing Science and Technology N2 - Purpose Live non-invasive monitoring of biomarkers is of great importance for the medical community. Moreover, some studies suggest that there is a substantial business gap in the development of mass-production commercial sweat-analysing wearables with great revenue potential. The objective of this work is to quantify the concentration of biomarkers that reaches the area of the garment where a sensor is positioned to advance the development of commercial sweat-analysing garments. Design/methodology/approach Computational analysis of the microfluidic transport of biomarkers within eccrine sweat glands provides a powerful way to explore the potential for quantitative measurements of biomarkers that can be related to the health and/or the physical activity parameters of an individual. The numerical modelling of sweat glands and the interaction of sweat with a textile layer remain however rather unexplored. This work presents a simulation of the production of sweat in the eccrine gland, reabsorption from the dermal duct into the surrounding skin and diffusion within an overlying garment. Findings The model represents satisfactorily the relationship between the biomarker concentration and the flow rate of sweat. The biomarker distribution across an overlying garment has also been calculated and subsequently compared to the minimum amount detectable by a sensor previously reported in the literature. The model can thus be utilized to check whether or not a given sensor can detect the minimum biomarker concentration threshold accumulated on a particular type of garment. Originality/value The present work presents to the best of our knowledge, the earliest numerical models of the sweat gland carried out so far. The model describes the flow of human sweat along the sweat duct and on to an overlying piece of garment. The model considers complex phenomena, such as reabsorption of sweat into the skin layers surrounding the duct, and the structure of the fibres composing the garment. Biomarker concentration maps are obtained to check whether sensors can detect the threshold concentration that triggers an electric signal. This model finds application in the development of smart textiles. Y1 - 2020 UR - https://www.emerald.com/insight/content/doi/10.1108/IJCST-07-2019-0100/full/html U6 - https://doi.org/10.1108/IJCST-07-2019-0100 SN - 0955-6222 VL - 32 IS - 5 SP - 761 EP - 774 ER - TY - GEN A1 - Baena-Moreno, Francisco Manuel A1 - Cid-Castillo, N. A1 - Arellano-García, Harvey A1 - Ramirez Reina, Tomas T1 - Towards emission free steel manufacturing – Exploring the advantages of a CO2 methanation unit to minimize CO2 emissions T2 - Science of The Total Environment N2 - This paper demonstrates the benefits of incorporating CO2 utilisation through methanation in the steel industry. This approach allows to produce synthetic methane, which can be recycled back into the steel manufacturing process as fuel and hence saving the consumption of natural gas. To this end, we propose a combined steel-making and CO2 utilisation prototype whose key units (shaft furnace, reformer and methanation unit) have been modelled in Aspen Plus V8.8. Particularly, the results showed an optimal performance of the shaft furnace at 800°C and 6 bar, as well as 1050°C and atmospheric pressure for the reformer unit. Optimal results for the methanation reactor were observed at 350°C. Under these optimal conditions, 97.8% of the total CO2 emissions could be mitigated from a simplified steel manufacturing scenario and 89.4% of the natural gas used in the process could be saved. A light economic approach is also presented, revealing that the process could be profitable with future technologic developments, natural gas prices and forthcoming increases of CO2 emissions taxes. Indeed, the cash-flow can be profitable (325 k€) under the future costs: methanation operational cost at 0.105 €/Nm³; electrolysis operational cost at 0.04 €kWh, natural gas price at 32 €/MWh; and CO2 penalty at 55€/MWh. Hence this strategy is not only environmentally advantageous but also economically appealing and could represent an interesting route to contribute towards steel-making decarbonisation. Y1 - 2021 UR - https://www.sciencedirect.com/science/article/pii/S0048969721018441?via%3Dihub U6 - https://doi.org/10.1016/j.scitotenv.2021.146776 SN - 1879-1026 SN - 0048-9697 VL - 781 ER - TY - GEN A1 - Mechleri, Evgenia A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - A Model Predictive Control-Based Decision-Making Strategy for Residential Microgrids T2 - Eng N2 - This work presents the development of a decision-making strategy for fulfilling the power and heat demands of small residential neighborhoods. The decision on the optimal operation of a microgrid is based on the model predictive control (MPC) rolling horizon. In the design of the residential microgrid, the new approach different technologies, such as photovoltaic (PV) arrays, micro-combined heat and power (micro-CHP) units, conventional boilers and heat and electricity storage tanks are considered. Moreover, electricity transfer between the microgrid components and the national grid are possible. The MPC problem is formulated as a mixed integer linear programming (MILP) model. The proposed novel approach is applied to two case studies: one without electricity storage, and one integrated microgrid with electricity storage. The results show the benefits of considering the integrated microgrid, as well as the advantage of including electricity storage. Y1 - 2022 UR - https://www.mdpi.com/2673-4117/3/1/9 U6 - https://doi.org/10.3390/eng3010009 SN - 2673-4117 VL - 3 IS - 1 SP - 100 EP - 115 ER - TY - GEN A1 - Jurischka, Constantin A1 - Dorneanu, Bogdan A1 - Stollberg, Christian A1 - Arellano-García, Harvey T1 - A novel approach to continuous extraction of active ingredients from essential oils through combined chromatography T2 - Computer Aided Chemical Engineering N2 - This contribution introduces a combined liquid chromatography purification designed for a continuous and resource-efficient process, integrating the rotating columns and the simulated bed principles. The approach is demonstrated and validated based on bisabolol oxides A and B, which are effective ingredients with anti-inflammatory and spasmolytic effects, prepared from chamomile essential oil. The results show superior efficiency to the traditional selective methods for isolating ingredients from multicomponent mixtures, as well as reduction in resources and costs. Y1 - 2022 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780323958790501296?via%3Dihub U6 - https://doi.org/10.1016/B978-0-323-95879-0.50129-6 SN - 1570-7946 VL - 51 SP - 769 EP - 774 ER - TY - GEN A1 - Estrada, Carlos A. A1 - Manrique-Silupú, José A1 - Ipanaqué, William A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - A model-based approach for the prediction of banana rust thrips incidence from atmospheric variables T2 - Computer Aided Chemical Engineering N2 - This work focuses on the development of a mathematical model for the population growth of banana red rust thrips (Chaetanaphothrips signipennis) based on a modified temperature-based growth rate with the addition of climatic variables, such as relative humidity, wind speed and rainfall rate. The aim is to enable better prediction of the pest incidence and improve decision making, productivity, as well as quantifying the influence of these variables on the development of red rust thrips. The developed model is then compared with current solutions for predicting the pest incidence, showing improved accuracy (higher than 67%) versus experimental data, for which the state-of-the-art models indicate extremely poor fits. Y1 - 2022 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780323958790500850?via%3Dihub U6 - https://doi.org/10.1016/B978-0-323-95879-0.50085-0 SN - 1570-7946 VL - 51 SP - 505 EP - 510 ER - TY - GEN A1 - Amao, Khalid A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Economic Analysis of Novel Pathways for Recovery of Lithium Battery Waste T2 - Computer Aided Chemical Engineering N2 - Using the Umicore process, a current state-of-the-art recycling in the metal recovery industry for lithium battery waste, as a baseline, this contribution examines economic and environmentally friendly solutions for effective metal recovery from spent LIBs. At the same time, possible synergies between existing resource use from other manufacturing and waste treatment industries are considered as valuable input to metal recycling, while also reducing the amount of atmospheric carbon. This further presents a case for possible integration of various waste management approaches as a single business unit for economic incentive and profitability for possible investment. Y1 - 2022 UR - https://www.sciencedirect.com/science/article/abs/pii/B978032395879050271X?via%3Dihub U6 - https://doi.org/10.1016/B978-0-323-95879-0.50271-X SN - 1570-7946 VL - 51 SP - 1621 EP - 1626 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Heinzelmann, Norbert A1 - Schnitzlein, Klaus A1 - Arellano-García, Harvey T1 - A novel approach to modelling trickle bed reactors T2 - Computer Aided Chemical Engineering N2 - In this contribution, the development of a toolbox for the simulation of trickle bed reactors based on a model able to account for the local properties of the liquid and gas flow in a packed bed at particle scale is introduced. The implementation uses a modular and flexible setup, with local liquid distribution considered as a function of the operating conditions and the physical properties of the three phases. Moreover, the impact of the local incomplete wetting on the conversion, as well as the mass transport and kinetics at both particle and reactor scale are accounted for. Furthermore, different particle geometries are considered, and the model is able to reliably predict the performance of the catalytic trickle bed reactors. Y1 - 2022 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780323958790500473?via%3Dihub U6 - https://doi.org/10.1016/B978-0-323-95879-0.50047-3 SN - 1570-7946 VL - 51 SP - 277 EP - 282 ER - TY - GEN A1 - Campos, Jean C. A1 - Manrique-Silupú, José A1 - Ipanaqué, William A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Mechanistic modelling for thrips incidence in organic banana T2 - Computer Aided Chemical Engineering N2 - This contribution introduces a data acquisition and modelling framework for the prediction of banana pests’ incidence. An IoT sensors-based system collects weather and micro-climate variables, such as temperature, relative humidity, and wind speed, which are uploaded in real time to a cloud storage space. The incidence of the red rust thrips (Chaetanaphothrips signipennis) is collected “manually” by periodic inspection. The mathematical model is adapted from population growth functions and a model of insect species development and allows predictions to be made at various time intervals with an accuracy greater than 80%, improving decision-making capacity for agro-producers and enabling the improvement of pest management actions. Y1 - 2022 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780323958790500461?via%3Dihub U6 - https://doi.org/10.1016/B978-0-323-95879-0.50046-1 SN - 1570-7946 VL - 51 SP - 271 EP - 276 ER - TY - GEN A1 - Ketabchi, Elham A1 - Ramirez Reina, Tomas A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - An identification approach to a reaction network for an ABE catalytic upgrade T2 - Computer Aided Chemical Engineering N2 - This contribution presents a kinetic study for the identification of the complex reaction mechanism occurring during the ABE upgrading, and the development of a kinetic model. Employing graph theory analysis, a directed bipartite graph is constructed to reduce the complexity of the reaction network, and the reaction rate constants and reaction orders are calculated using the initial rate method, followed by the calculation of the activation energy and frequency factor for an Arrhenius-type law. Subsequently, using general mass balancing a proposed mathematical model is produced to determine the apparent reaction rates, which are successfully in line with the experimental results. Y1 - 2021 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780323885065501029?via%3Dihub U6 - https://doi.org/10.1016/B978-0-323-88506-5.50102-9 SN - 1570-7946 VL - 50 SP - 643 EP - 648 ER - TY - GEN A1 - Clarke, Fiona A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Optimal design of heating and cooling pipeline networks for residential distributed energy resource systems T2 - Energy N2 - This paper presents a mixed integer linear programming model for the optimal design of a distributed energy resource (DER) system that meets electricity, heating, cooling and domestic hot water demands of a neighbourhood. The objective is the optimal selection of the system components among different technologies, as well as the optimal design of the heat pipeline network to allow heat exchange between different nodes in the neighbourhood. More specifically, this work focuses on the design, interaction and operation of the pipeline network, assuming the operation and maintenance costs. Furthermore, thermal and cold storage, transfer of thermal energy, and pipelines for transfer of cold and hot water to meet domestic hot water demands are additions to previously published models. The application of the final model is investigated for a case-study of a neighbourhood of five houses located in the UK. The scalability of the model is tested by also applying the model to a neighbourhood of ten and twenty houses, respectively. Enabling exchange of thermal power between the neighbours, including for storage purposes, and using separate hot and cold pipeline networks reduces the cost and the environmental impact of the resulting DER. Y1 - 2021 UR - https://www.sciencedirect.com/science/article/pii/S0360544221016789?via%3Dihub U6 - https://doi.org/10.1016/j.energy.2021.121430 SN - 1873-6785 SN - 0360-5442 VL - 235 ER - TY - GEN A1 - Sidnell, Tim A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Effects of Dynamic Pricing on the Design and Operation of Distributed Energy Resource Networks T2 - Processes N2 - This paper presents a framework for the use of variable pricing to control electricity im-ported/exported to/from both fixed and unfixed residential distributed energy resource (DER) network designs. The framework shows that networks utilizing much of their own energy, and importing little from the national grid, are barely affected by dynamic import pricing, but are encouraged to sell more by dynamic export pricing. An increase in CO2 emissions per kWh of energy produced is observed for dynamic import and export, against a baseline configuration utilizing constant pricing. This is due to feed-in tariffs (FITs) that encourage CHP generation over lower-carbon technologies. Furthermore, batteries are shown to be expensive in systems receiving income from FITs and grid exports, but for the cases when they sell to/buy from the grid using dynamic pricing, their use in the networks becomes more economical. Keywords: distributed energy resource (DER); dynamic pricing; mixed-integer linear programming (MILP); renewable heat incentive (RHI); feed-in tariff (FIT); electricity storage in batteries. Y1 - 2021 UR - https://www.mdpi.com/2227-9717/9/8/1306 U6 - https://doi.org/https://doi.org/10.3390/pr9081306 SN - 2227-9717 VL - 9 IS - 8 ER - TY - GEN A1 - Sidnell, Tim A1 - Clarke, Fiona A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Optimal design and operation of distributed energy resources systems for residential neighbourhoods T2 - Smart Energy N2 - Different designs of distributed energy resources (DER) systems could lead to different performance in reducing cost, environmental impact or use of primary energy in residential networks. Hence, optimal design and management are important tasks to promote diffusion against the centralised grid. However, current operational models for such systems do not adequately analyse their complexity. This paper presents the results of a mixed-integer linear programming (MILP) model of distributed energy systems in the residential sector which builds up on previous work in this field. A superstructure optimisation model for design and operation of DER systems is obtained, providing a more holistic overview of such systems by including the following novel elements: a) Design and utilisation of a network with integrated heating/cooling pipelines and microgrid connections between neighbourhoods; b) Exploration of use of feed-in tariffs (FITs), renewable heat incentives (RHIs) and the ability to buy/sell from/to the national grid. It is shown that the (DER network mitigates around 30–40% of the CO2 emissions per household, compared with “traditional generation”. Money from FITs, RHIs and sales to the grid, as well as reduced grid purchases, make DER networks far more economical, and even profitable, compared to the traditional energy consumption. Y1 - 2021 UR - https://www.sciencedirect.com/science/article/pii/S2666955221000496?via%3Dihub U6 - https://doi.org/10.1016/j.segy.2021.100049 SN - 2666-9552 VL - 4 ER - TY - GEN A1 - Anagnostopoulos, Argyrios A1 - Sebastia-Saez, Daniel A1 - Campbell, Alasdair N. A1 - Arellano-García, Harvey T1 - Finite element modelling of the thermal performance of salinity gradient solar ponds T2 - Energy N2 - Solar ponds are a promising technology to capture and store solar energy. Accurate, reliable and versatile models are thus needed to assess the thermal performance of salinity gradient solar ponds. A CFD simulation set-up has been developed in this work to obtain a fully versatile model applicable to any practical scenario. Also, a comparison between the results obtained with an existing one-dimensional MATLAB model and the two- and three-dimensional CFD models developed in this work has been carried out to quantify the gain in accuracy and the increase in computational resources needed. The two and three-dimensional models achieve considerably higher accuracy than the 1-D model. They are subsequently found to accurately evaluate the heat loss to the surroundings, the irradiance absorbed by the solar pond and the thermal performance of the pond throughout the year. Two geographic locations: Bafgh (Iran) and Kuwait City, have been evaluated. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/pii/S0360544220309683?via%3Dihub U6 - https://doi.org/10.1016/j.energy.2020.117861 SN - 1873-6785 SN - 0360-5442 VL - 203 ER - TY - GEN A1 - De Mel, Ishanki A1 - Demis, Panagiotis A1 - Dorneanu, Bogdan A1 - Klymenko, Oleksiy A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Global Sensitivity Analysis for Design and Operation of Distributed Energy Systems T2 - Computer Aided Chemical Engineering N2 - Distributed Energy Systems (DES) are set to play a vital role in achieving emission targets and meeting higher global energy demand by 2050. However, implementing these systems has been challenging, particularly due to uncertainties in local energy demand and renewable energy generation, which imply uncertain operational costs. In this work we are implementing a Mixed-Integer Linear Programming (MILP) model for the operation of a DES, and analysing impacts of uncertainties in electricity demand, heating demand and solar irradiance on the main model output, the total daily operational cost, using Global Sensitivity Analysis (GSA). Representative data from a case study involving nine residential areas at the University of Surrey are used to test the model for the winter season. Distribution models for uncertain variables, obtained through statistical analysis of raw data, are presented. Design results show reduced costs and emissions, whilst GSA results show that heating demand has the largest influence on the variance of total daily operational cost. Challenges and design limitations are also discussed. Overall, the methodology can be easily applied to improve DES design and operation. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/abs/pii/B9780128233771502548?via%3Dihub U6 - https://doi.org/10.1016/B978-0-12-823377-1.50254-8 SN - 1570-7946 VL - 48 SP - 1519 EP - 1524 ER - TY - GEN A1 - Yusuf, Ifrah A1 - Flagiello, Fabio A1 - Ward, Niel I. A1 - Arellano-García, Harvey A1 - Avignone-Rossa, Claudio A1 - Felipe-Sotelo, Monica T1 - Valorisation of banana peels by hydrothermal carbonisation: Potential use of the hydrochar and liquid by-product for water purification and energy conversion T2 - Bioresource Technology Reports N2 - Banana peels were used as feedstock to produce a carbon dense hydrochar for the removal of toxic metals from wastewater. Compared to the biomass feedstock (41.3% mass C), the banana peel hydrochar possesses higher carbon (54–72% mass C) and lower ash contents. The carbonised banana peels treated between 150 and 300 °C (1−2h) demonstrated an excellent ability to remove Cd²⁺ (5–100 mg L⁻¹), achieving 99% removal, in comparison with 75% for the raw peel. The liquid by-product generated in the carbonisation process was tested as feedstock in microbial electrochemical devices, showing significant reduction in the chemical oxygen demand levels (initially 10–25 10³ mg L⁻¹), associated with the production of electrical outputs; 81–85% reduction with microbial communities from compost, and 53–85% with anaerobic sludge. The results demonstrate the complete utilization of waste from mass cultivation of banana, providing a full-cycle solution for the pollution associated to this important crop. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/pii/S2589014X20302048?via%3Dihub U6 - https://doi.org/10.1016/j.biteb.2020.100582 SN - 2589-014X VL - 12 ER - TY - GEN A1 - De Carvalho Miranda, Julio Cesar A1 - Flores Ponce, Gustavo Henrique Santos A1 - Arellano-García, Harvey A1 - Maciel Filho, Rubens A1 - Wolf Maciel, Maria Regina T1 - Process design and evaluation of syngas-to-ethanol conversion plants T2 - Journal of Cleaner Production N2 - Synthesis gas (syngas) is mostly known by its use on ammonia (Harber-Bosch process) and hydrocarbons (Fischer-Tropsch process) production processes. However, a less explored route to produce chemical products, among them alcohols and other oxygenates, from syngas has been gaining attention over the last few years. In this route, an initial feedstock as biomass is firstly gasified to synthesis gas, which is reformed, cleaned, compressed and finally catalytically converted into a mixture of alcohols and oxygenated products. After separation steps, these products attain sufficient purity to be sold. In this work, the thermochemical route, is used aiming ethanol production from syngas. Using the commercial simulator ASPEN Plus, were proposed four study cases using 3 different categories of catalysts in 4 different process layouts. All the cases were evaluated regarding their productivity, energy consumption, and aspects of economic importance. The results show the technical viability to produce ethanol from syngas, proving an energy surplus of all processes and a reasonable production of the main product. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/pii/S0959652620321259?via%3Dihub U6 - https://doi.org/10.1016/j.jclepro.2020.122078 SN - 0959-6526 VL - 269 ER - TY - GEN A1 - Gonzalez-Castaño, Miriam A1 - Gonzalez-Arias, Judith A1 - Bobadilla, Luis F. A1 - Ruiz-Lopez, E. A1 - Odriozola, Jose Antonio A1 - Arellano-García, Harvey T1 - In-Situ Drifts Steady-State Study of Co2 and Co Methanation Over Ni-Promoted Catalysts T2 - Fuel N2 - Promoting the performance of catalytic systems by incorporating small amount of alkali has been proved effective for several reactions whilst controversial outcomes are reported for the synthetic natural gas production. This work studies a series of Ni catalysts for CO2 and CO methanation reactions. In-situ DRIFTS spectroscopy evidenced similar reaction intermediates for all evaluated systems and it is proposed a reaction mechanism based on: i) formate decomposition and ii) hydrogenation of lineal carbonyl species to methane. Compared to bare Ni, the enhanced CO2 methanation rates attained by NiFe/Al and NiFeK/Al systems are associated to promoted formates decomposition into lineal carbonyl species. Also for CO methanation, the differences in the catalysts’ performances were associated to the relative concentration of lineal carbonyl species. Under CO methanation conditions and opposing the CO2 methanation results where the incorporation of K delivered promoted catalytic behaviours, worsened CO methanation rates were discerned for the NiFeK/Al system. Y1 - 2023 UR - https://www.sciencedirect.com/science/article/pii/S0016236122040650?via%3Dihub U6 - https://doi.org/10.1016/j.fuel.2022.127241 SN - 1873-7153 VL - 338 ER - TY - GEN A1 - Tarifa, Pilar A1 - Ramirez Reina, Tomas A1 - González-Castaño, Miriam A1 - Arellano-García, Harvey T1 - Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl₂O₄ as a Bifunctional Catalyst T2 - Energy and Fuels N2 - Biomass gasification streams typically contain a mixture of CO, H2, CH4, and CO2 as the majority components and frequently require conditioning for downstream processes. Herein, we investigate the catalytic upgrading of surrogate biomass gasifiers through the generation of syngas. Seeking a bifunctional system capable of converting CO2 and CH4 to CO, a reverse water gas shift (RWGS) catalyst based on Fe/MgAl2O4 was decorated with an increasing content of Ni metal and evaluated for producing syngas using different feedstock compositions. This approach proved efficient for gas upgrading, and the incorporation of adequate Ni content increased the CO content by promoting the RWGS and dry reforming of methane (DRM) reactions. The larger CO productivity attained at high temperatures was intimately associated with the generation of FeNi3 alloys. Among the catalysts' series, Ni-rich catalysts favored the CO productivity in the presence of CH4, but important carbon deposition processes were noticed. On the contrary, 2Ni-Fe/MgAl2O4 resulted in a competitive and cost-effective system delivering large amounts of CO with almost no coke deposits. Overall, the incorporation of a suitable realistic application for valorization of variable composition of biomass-gasification derived mixtures obtaining a syngas-rich stream thus opens new routes for biosyngas production and upgrading. Y1 - 2022 UR - https://pubs.acs.org/doi/10.1021/acs.energyfuels.2c01452 U6 - https://doi.org/10.1021/acs.energyfuels.2c01452 SN - 1520-5029 SN - 0887-0624 VL - 36 IS - 15 SP - 8267 EP - 8273 ER - TY - GEN A1 - Ruan, Hang A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Xiao, Pei A1 - Zhang, Li T1 - Deep Learning-Based Fault Prediction in Wireless Sensor Network Embedded Cyber-Physical Systems for Industrial Processes T2 - IEEE Access N2 - This paper investigates the challenging fault prediction problem in process industries that adopt autonomous and intelligent cyber-physical systems (CPS), which is in line with the emerging developments of industrial internet of things (IIoT) and Industry 4.0. Particularly, we developed an end-to-end deep learning approach based on a large volume of real-time sensory data collected from a chemical plant equipped with wireless sensors. Firstly, a novel recursive architecture with multi-lookback inputs is proposed to perform autoregression on imbalanced time-series data as a preliminary prediction. In this process, a novel learning algorithm named recursive gradient descent (RGD) is developed for the proposed architecture to reduce cumulative prediction uncertainties. Subsequently, a classification model based on temporal convolutions over multiple channels with decay effect is proposed to perform multi-class classification for fault root cause identification and localization. The overall network is named the cumulative uncertainty reduction network (CURNet), for its superior capacity in reducing prediction uncertainties accumulated over multiple prediction steps. Performance evaluations show that CURNet is able to achieve superior performance especially in terms of fault prediction recall and fault type classification accuracy, compared to the existing techniques. Y1 - 2022 UR - https://ieeexplore.ieee.org/document/9684389 U6 - https://doi.org/10.1109/ACCESS.2022.3144333 SN - 2169-3536 VL - 10 SP - 10867 EP - 10879 ER - TY - GEN A1 - Saavedra, Stephy A1 - Alejandro-Paredes, Luis A1 - Flores-Santos, Juan Carlos A1 - Flores-Fernández, Carol Nathali A1 - Arellano-García, Harvey A1 - Zavaleta, Amparo Iris T1 - Optimization of lactic acid production by Lactobacillus plantarum strain Hui1 in a medium containing sugar cane molasses T2 - Agronomía Colombiana N2 - The aim of this study was to optimize lactic acid production by a native strain (Huil) of Lactobacillus plantarum isolated from a Peruvian Amazon fruit (Genipa americana) in a medium supplemented with an agroindustrial by-product such as sugar cane molasses. Optimization was performed though one-factor-at-a-time studies followed by the Placket-Burman and central composite designs. The data were analyzed by using the Statistica® 10 software. Several carbon, nitrogen and ion sources were tested, and the optimum concentration of lactic acid achieved was 84.2 g L-1 in a medium containing as follows (in g L-1): meat extract, 18.69; tryptone, 7.88; sugar cane molasses, 140; calcium carbonate, 15; dipotassium phosphate, 1; manganese phosphate, 0.03; sodium acetate, 5, and magnesium sulphate, 0.2. In addition, a high degree of conversion from sugar cane molasses to lactic acid was obtained (Yp/e 0.898 g g-1). These results indicate the potential of Lactobacil-lus plantarum strain Hui1 to produce lactic acid in a medium supplemented with sugar cane molasses, an underutilized industrial by-product. Y1 - 2021 UR - https://revistas.unal.edu.co/index.php/agrocol/article/view/89674 U6 - https://doi.org/10.15446/agron.colomb.v39n1.89674 SN - 0120-9965 SN - 2357-3732 VL - 39 IS - 1 SP - 98 EP - 107 ER - TY - CHAP A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Ruan, Hang A1 - Mohamed, Abdelrahim A1 - Xiao, Pei A1 - Heshmat, Mohamed A1 - Gao, Yang T1 - Towards fault detection and self-healing of chemical processes over wireless sensor networks T2 - Industry 4.0 – Shaping The Future of The Digital World N2 - This contribution introduces a framework for the fault detection and healing of chemical processes over wireless sensor networks. The approach considers the development of a hybrid system which consists of a fault detection method based on machine learning, a wireless communication model and an ontology-based multi-agent system with a cooperative control for the process monitoring. Y1 - 2020 UR - https://www.taylorfrancis.com/chapters/edit/10.1201/9780367823085-02/towards-fault-detection-self-healing-chemical-processes-wireless-sensor-networks-dorneanu-arellano-garcia-ruan-mohamed-xiao-heshmat-gao SN - 9780367823085 U6 - https://doi.org/10.1201/9780367823085-02 SP - 9 EP - 14 PB - CRC Press CY - London, United Kingdom ET - 1st edition ER - TY - CHAP A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Heshmat, Mohamed A1 - Gao, Yang T1 - A framework for intelligent monitoring and control of chemical processes with multi-agent systems T2 - Industry 4.0 – Shaping The Future of The Digital World N2 - Industry 4.0 is transforming chemical processes into complex, smart cyber-physical systems that require intelligent methods to support the operators in taking decisions for better and safer operation. In this paper, a multi-agent cooperative-based model predictive system for monitoring and control of a chemical process is proposed. This system uses ontology to formally represent the system knowledge. By integrating the cooperative-based model predictive controller with the multi-agent system, the control can be improved, and the process can be converted into a self-adaptive system. Y1 - 2020 UR - https://www.taylorfrancis.com/chapters/edit/10.1201/9780367823085-04/framework-intelligent-monitoring-control-chemical-processes-multi-agent-systems-dorneanu-arellano-garcia-heshmat-gao SN - 9780367823085 U6 - https://doi.org/10.1201/9780367823085-04 SP - 18 EP - 23 PB - CRC Press CY - London, United Kingdom ET - 1st edition ER - TY - GEN A1 - Ketabchi, Elham A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Increasing operational efficiency through the integration of an oil refinery and an ethylene production plant T2 - Chemical Engineering Research and Design N2 - In this work, the optimal integration between an oil refinery and an ethylene production plant has been investigated. Both plants are connected using intermediate materials aiming to remove, at least partially, the reliance on external sourcing. This integration has been proven to be beneficial in terms of quality and profit increase for both production systems. Thus, three mathematical models have been formulated and implemented for each plant individually as well as for the integrated system as MINLP models aiming to optimise all three systems. Moreover, a case study using practical data is presented to verify the feasibility of the integration within an industrial environment. Promising results have been obtained demonstrating significant profit increase in both plants. Y1 - 2019 UR - https://www.sciencedirect.com/science/article/pii/S0263876219304459?via%3Dihub U6 - https://doi.org/10.1016/j.cherd.2019.09.028 SN - 1744-3563 SN - 0263-8762 VL - 152 SP - 85 EP - 94 ER - TY - GEN A1 - Ketabchi, Elham A1 - Pastor-Perez, Laura A1 - Arellano-García, Harvey A1 - Ramirez Reina, Tomas T1 - Influence of Reaction Parameters on the Catalytic Upgrading of an Acetone, Butanol and Ethanol (ABE) Mixture: Exploring New Routes for Modern Biorefineries T2 - Frontiers in Chemistry N2 - Here we present a comprehensive study on the effect of reaction parameters on the upgrade of an acetone, butanol and ethanol mixture – key molecules and platform products of great interest within the chemical sector. Using a selected high performing catalyst, Fe/MgO-Al2O3, the variation of temperature, reaction time, catalytic loading and reactant molar ratio have been examined in this reaction. This work is aiming to not only optimise the reaction conditions previously used, but to step towards using less energy, time and material by testing those conditions and analysing the sufficiency of the results. Herein we demonstrate that this reaction is favoured at higher temperatures and longer reaction time. Also, we observe that increasing the catalyst loading had a positive effect on the product yields, while reactant ratios have shown to produce varied results due to the role of each reactant in the complex reaction network. In line with the aim of reducing energy and costs, this work showcases that the products from the upgrading route have significantly higher market value than the reactants; highlighting that this process represents an appealing route to be implemented in modern biorefineries. Y1 - 2020 UR - https://www.frontiersin.org/articles/10.3389/fchem.2019.00906/full U6 - https://doi.org/10.3389/fchem.2019.00906 SN - 2296-2646 VL - 7 ER - TY - GEN A1 - Ketabchi, Elham A1 - Pastor-Perez, Laura A1 - Ramirez Reina, Tomas A1 - Arellano-García, Harvey T1 - Catalytic upgrading of acetone, butanol and ethanol (ABE): A step ahead for the production of added value chemicals in bio-refineries T2 - Renewable Energy N2 - With the aim of moving towards sustainability and renewable energy sources, we have studied the production of long chain hydrocarbons from a renewable source of biomass to reduce negative impacts of greenhouse gas emissions while providing a suitable alternative for fossil fuel-based processes. Herein we report a catalytic strategy for Acetone, Butanol and Ethanol (ABE) upgrading using economically viable catalysts with potential impact in modern bio-refineries. Our catalysts based on transition metals such as Ni, Fe and Cu supported on MgO–Al2O3 have been proven to perform exceptionally with outstanding conversions towards the production of a broad range of added value chemicals from C2 to C15. Although all catalysts displayed meritorious performance, the Fe catalyst has shown the best results in terms conversion (89%). Interestingly, the Cu catalyst displays the highest selectivity towards long chain hydrocarbons (14%). Very importantly, our approach suppresses the utilization of solvents and additives resulting directly in upgraded hydrocarbons that are of use in the chemical and/or the transportation industry. Overall, this seminal work opens the possibility to consider ABE upgrading as a viable route in bio-refineries to produce renewably sourced added value products in an economically favorable way. In addition, the described process can be envisaged as a cross-link stream among bio and traditional refineries aiming to reduce fossil fuel sources involved and incorporate “greener” solutions. Y1 - 2020 UR - https://www.sciencedirect.com/science/article/pii/S096014812030690X?via%3Dihub U6 - https://doi.org/10.1016/j.renene.2020.04.152 SN - 1879-0682 SN - 0960-1481 VL - 156 SP - 1065 EP - 1075 ER - TY - GEN A1 - Yentumi, Richard A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Optimal Operation of an Industrial Natural Gas Fired Natural Draft Heater T2 - Chemical Engineering Journal Advances N2 - In this work, a custom dynamic mathematical model of an industrial vertical-cylindrical type natural gas fired natural draft heater is developed using gPROMS® ProcessBuilder®. The integrated model comprises sub-models for each of the distinct sections of the fired heater which are connected by mass and energy flows. The temperature profiles of the tubular coils and the process fluid, a heat transfer fluid (HTF) are modelled using the distributed parameter system (DPS) in the axial direction (1D). The flue gas temperature in each section is modelled using the lumped parameter approach. Published empirical methods and correlations are used for estimating some unknown model parameters. The resulting model is a system of partial differential-algebraic equations (PDAEs) and serves as a basis for conducting an optimisation study to aid decision-making and to identify the best operating conditions within the specified constraints that minimise the daily operational costs. Through process simulation studies, the model predictions are adjusted to closely approximate collected actual plant data. It is demonstrated through the optimisation study that significant reduction in fuel gas consumption can be achieved compared to the current operating consumption levels. The developed models can be extended for use by other hydrocarbon processing plant operators with slight modifications, by specifying geometric parameters, HTF thermophysical properties, fuel gas composition and properties, among others. Y1 - 2022 UR - https://www.sciencedirect.com/science/article/pii/S2666821122001144?via%3Dihub U6 - https://doi.org/10.1016/j.ceja.2022.100354 SN - 2666-8211 VL - 11 ER - TY - CHAP A1 - Sebastia-Saez, Daniel A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey ED - Ramirez Reina, Tomas ED - Arellano-García, Harvey ED - Odriozola, José Antonio T1 - Advancing CCSU Technologies with Computational Fluid Dynamics (CFD): A Look at the Future by Linking CFD and Process Simulations T2 - Engineering Solutions for CO2 Conversion N2 - This chapter discusses the state of the art of the numerical modeling for carbon capture, storage and utilization (CCSU) technologies, covering the entire chain. The chapter opens with a note on the different modeling techniques available depending on the length and time scale and focuses thereafter on the application of computational fluid dynamics to CCSU and their link to process simulations. The chapter intends to provide the reader with guidelines on the numerical techniques available and how these methods can help gain insight into features relevant to the design and performance evaluation in the field of CCSU. Y1 - 2021 U6 - https://doi.org/10.1002/9783527346523.ch2 SP - 29 EP - 84 PB - Wiley-VCH GmbH CY - Weinheim, Germany ET - 1st edition ER - TY - GEN A1 - De Mel, Ishanki A1 - Demis, Panagiotis A1 - Dorneanu, Bogdan A1 - Klymenko, Oleksiy A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Global sensitivity analysis for design and operation of distributed energy systems: A two-stage approach T2 - Sustainable Energy Technologies and Assessments N2 - Distributed Energy Systems (DES) can play a vital role as the energy sector faces unprecedented changes to reduce carbon emissions by increasing renewable and low-carbon energy generation. However, current operational DES models do not adequately reflect the influence of uncertain inputs on operational outputs, resulting in poor planning and performance. This paper details a methodology to analyse the effects of uncertain model inputs on the primary output, the total daily cost, of an operational model of a DES. Global Sensitivity Analysis (GSA) is used to quantify these effects, both individually and through interactions, on the variability of the output. A Mixed-Integer Linear Programming model for the DES design is presented, followed by the operational model, which incorporates Rolling Horizon Model Predictive Control. A subset of model inputs, which include electricity and heating demand, and solar irradiance, is treated as uncertain using data from a case study. Results show reductions of minimum 25% in the total annualised cost compared to a traditional design that purchases electricity from the centralised grid and meets heating demand using boilers. In terms of carbon emissions, the savings are much smaller, although the dependency on the national grid is drastically reduced. Limitations and suggestions for improving the overall DES design and operation are also discussed in detail, highlighting the importance of incorporating GSA into the DES framework. Y1 - 2023 UR - https://www.sciencedirect.com/science/article/pii/S2213138823000565?dgcid=author U6 - https://doi.org/10.1016/j.seta.2023.103064 SN - 2213-1388 VL - 56 ER - TY - GEN A1 - Ramirez Reina, Tomas A1 - Ketabchi, Elham A1 - Arellano-García, Harvey A1 - Pastor-Perez, Laura T1 - The Production of Long Chain Hydrocarbons through the Catalytic Upgrade of Biomass-Based Acetone, Butanol and Ethanol (ABE) T2 - 2019 AIChE Annual Meeting N2 - One of the main issues that many industrial sectors such as oil refineries have been facing nowadays is their sole dependency on fossil fuel. Not only have price fluctuations affected the products, but their environmental impact is an ever present problem that should be addressed. This has led to the search for alternatives such as biomass based processes in order to reduce the dependency on fossil fuel. Bio-refinery processes, fed by biomass, produce high value chemicals and materials with the advantage of reduced environmental drawbacks, such as CO2 emissions, when compared to the conventional refinery. For the benefit of both systems, an integration approach has been considered connecting bio-refining and conventional refining processes together. In this work we focus on the production of long chain hydrocarbons while maintaining production of chemicals that already originate from biomass such as Acetone, Butanol and Ethanol (ABE). The ABE used for this process is obtained as a product of sugar fermentation using the bacteria genus Clostridium. Through the upgrading and conversion of ABE, the products obtained will then be incorporated in the proposed integration system, connecting the conventional oil refinery to this process. A reaction involving a complex reaction network towards upgrading ABE with the aim of producing valuable products using economically viable catalysts has been carried out. The vast majority of research in this area either involves the separation of ABE after fermentation to be used in the chemical/or transportation industry that incurs large costs, or noble metal catalysts are used to upgrade this feed, which would also not be economically viable. However, our research has surpassed the necessity of noble metals, leading to a significant cost decrease that also produces outstanding results. The catalysts required for this process were synthesised successfully through the wetness incipient method and characterised by XRD, Raman, BET, TPR and N2 Isotherm. The reaction consists of the self-condensation and cross condensation of the alcohols and acetone, respectively, using a variety of active metals on basic supports as catalysts, at high temperatures and pressure in a batch reactor. The results have shown exceptional performance for the catalysts in terms of conversion and selectivity, having conversions as high as 90%. The catalysts have proven to yield a range of C3-C15 hydrocarbons identified to be of need in the chemical industry. In conclusion, our route has produced valuable chemicals proven to have a considerably higher market value than the simple alcohol reactants, useful for both the petrochemical and the transportation industries, through the use of novel and economically favourable catalysts. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/39f-production-long-chain-hydrocarbons-through-catalytic-upgrade-biomass-based-acetone-butanol-and SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Hamdan, Mustapha A1 - Arellano-García, Harvey A1 - Sebastia-Saez, Daniel T1 - A Novel Circulating Fluidised Bed Solar Receiver Design for Thermal Energy Conversion and Storage T2 - 2019 AIChE Annual Meeting N2 - he middle east and northern Africa (MENA) regions rely heavily on fossil fuels as an energy source. The region consumes high amounts of energy for their air cooling and water desalination needs. For the GCC region this amounts to 60-70% of their energy consumption and has one of the highest carbon dioxide emissions per capita in the world. The GCC countries are in an area of high direct normal irradiance from the sun and thus, investigating the use of solar power as an alternative energy source is valid. Concentrated Solar Power (CSP) technology is a promising energy capture technology that uses optical devices to concentrate the power of the sun on to a surface and in turn generates power by means of a thermal-to-electric conversion. CSP technology integrates Thermal Energy Storage (TES) materials to store heat and thus enable power production in the absence of sunlight, at night or in poor weather conditions. While CSP technology is a promising alternative energy source its high levelized cost of energy (LCOE) is a drawback to its widespread implementation. A major factor to the high LCOE is the use of molten salts as the TES material carrying with it, high capital costs and high operating and maintenance cost. This is due to molten salts being corrosive and having a low working temperature limiting its thermal-to-electric efficiency. This contribution introduces a novel conceptual design of a circulating fluidised bed as the solar receiver for a CSP plant. The use of raw desert sand as an alternative TES material was investigated. An optimum heat transfer fluid (HTF) was selected from Carbon dioxide, Nitrogen, Argon and Air. This work will also argue that these changes to current CSP plants will significantly reduce the LCOE. The results of this study show that the proposed design can allow up to six times higher mass flowrates of the heat transfer fluid to circulate the sand than current designs. Moreover, 1000 oC uniform outlet temperature was also achieved. For this purpose, Carbon dioxide was found to be the optimum HTF, achieving the highest heat transfer rates. Thus, the new configuration of a fluidised bed receiver proves desert sand to be an effective alternative TES material leading to high thermal energy outputs per m2 and a substantial reduction in the LCOE for CSP technology. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/572a-novel-circulating-fluidised-bed-solar-receiver-design-thermal-energy-conversion-and-storage SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Ketabchi, Elham A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Towards Sustainable Industries: Industrial Symbiosis of an Oil Refinery and a Petrochemical Plant T2 - 2019 AIChE Annual Meeting N2 - A common factor that can be seen in the history of all manufacturing and production sectors is that they all go through significant changes to keep them operating efficiently, thus a constant cycle of system development, obsolescence and advancement is formed. These sectors must be able to maintain the balance between the energy consumption and efficiency to keep the system optimised and preserve the opportunity to create value. Oil refineries are a prime example of one of these sectors that play an important role in our day-to-day lives. Due to an oil refineries’ major dependency on crude oil, the price fluctuation of which, has a profound impact on this industry. Thusly, this drives up prices and forcing a rise in the search for alternative solutions to tackle these efficacy and economic problems. Therefore, in this work, an integration approach has been considered based on the Industrial Symbiosis concept to connect an oil refinery with a petrochemical plant. One main feature of the larger chemical industry that should be considered, is that they require careful management of material and energy to obtain valuable products. Of course, the processes key to the generation of the valuable products also produce fewer desirable chemicals, which have no value as waste products. Some of these waste materials can be used as feed-stock for other processes; turning probable costly chemical disposal into an economic boon. This “greener” approach opens avenues of improvement compatible with the idea of industrial symbiosis; where the waste from one process can be a feed-stock, useful for another. Taking this into account, a case study is presented involving the connection of an oil refinery with an ethylene production plant through material exchange and stream combination to benefit both plants. As a result, we were able to improve not only product quality but the overall profit of both plants by a significant margin, while also decreasing dependency on outside sources for material supply. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/564b-towards-sustainable-industries-industrial-symbiosis-oil-refinery-and-petrochemical-plant SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Heshmat, Mohamed A1 - Gao, Yang T1 - Ontology Based Decision Making for Process Control T2 - 2019 AIChE Annual Meeting N2 - In the context of Industry 4.0, engineering systems and manufacturing processes are becoming increasingly complex, combining the physical world of the processing units with the cyber world of the wireless sensing and communication networks, big data analytics, ubiquitous computing and other elements that the Industrial Internet of Things technologies. The fields of ontology, knowledge management and decision-making systems have matured significantly in the recent years and their integration with the cyber-physical system (CPS) facilitates and improves the effectiveness of decision-support systems (DSS) [1]. Yet, this comes with an increase in the system’s complexity and a need for deployment of intelligent systems for process systems engineering (PSE) applications, that should adapt to the continuously new requirements of Industry 4.0. Considering the large number of devices existent in a CPS, distributed methods are required to transfer the computational load from centralised to local (decentralised) controllers. This has led to the motivation of applying multi-agent systems (MASs) methodologies as a solution to distributed control as a computational paradigm [2]. An agent can be defined as an entity placed in an environment that can sense different parameters used to make a decision based on the goals of the entity. A MAS is a computerised system composed of multiple interacting agents exploited to solve a problem. Their salient features, which include efficiency, low cost, flexibility, and reliability, make it an effective solution for solving tasks [3]. Usually, DSS adopt a rule-based or logic-based representation scheme [4]. For this reason, ontologies have attracted the attention of the PSE community as a convenient means for knowledge representation [1, 5]. An ontology is a formal representation of a set of concepts within a domain and the relationships between those concepts, and it serves as a library of knowledge to efficiently build intelligent systems and as a shared vocabulary for communication between interacting human and/or software agents [6]. In this paper, a multi-agent cooperative-based model predictive control (MPC) system for monitoring and control of a chemical process is proposed. The system uses ontology to formally represent the system knowledge at process, communication and decision-making level. The application of the proposed framework is discussed for a chemical process that produces iso-octane. A cooperative MPC is implemented to achieve the control of the plant. This protocol is defined using a simple algorithm to reach an agreement regarding the state of a number of N agents [7]. The monitoring feature is defined by means of a MAS, consisting of follower agents (FAs), a coordinator agent (CA) and a monitor agent (MoA), that is integrated with the MPC. The MAS has two main tasks: a) decide optimal connectivity between the distributed MPCs for safer and better operation; and b) monitor the system and detect any deviation in the behaviour. The addition of the MAS makes the cooperative MPC controller more efficient by taking advantage of the communication between the various elements of the CPS. Using the knowledge form the ontology and the agents’ sharing capabilities, the system can detect faster any deviation compared to standard operation. The framework can easily be adapted for other control approaches by very simple modifications in the structure and objectives. A practical demonstration in a pilot plant environment is envisaged for the future. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/145e-ontology-based-decision-making-process-control SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Yusuf, Ifrah A1 - Dorneanu, Bogdan A1 - Avignone-Rossa, Claudio A1 - Arellano-García, Harvey T1 - Synthesis and Characterization of Hydrochars Produced By Hydrothermal Carbonization of Banana Peels T2 - 2019 AIChE Annual Meeting N2 - Hydrothermal carbonisation (HTC) is a thermochemical process which imitates the natural coalification of biomass. If the natural process requires some hundred to some million years, depending on the type of coal produced, HTC needs less than half a day for the transformation of biomass into materials quite similar to brown coal [1].The organic feedstock is reacted with water at mild temperature (130-300 0C) compared to other thermochemical processes such as pyrolysis, gasification, or flash carbonisation, and under autogenous pressures (10-96 bar). The result is a homogeneous carbon-rich solid, a high-strength process liquid, and a gaseous product mainly consisting of CO2 [2]. Compared to the biomass feedstock, biochar possesses a higher heating value and higher carbon content, has a lower ash content, more surface oxygen-containing groups, and it can lead to lower emissions of greenhouse gases [3]. The difference in chemical composition of the final products depend on the reaction mechanisms that occur during HTC, which include hydrolysis, dehydration, decarboxylation, aromatization and re-condensation. Although these processes generally occur in this order, they do not operate in a successive manner; instead they occur simultaneously during HTC and are interconnected with each other [4]. The main purpose of this work is to evaluate the technological feasibility of converting banana peel residues in useful products using the HTC, towards a localised production strategy to harness the value of the waste for improving the livelihoods of rural agricultural communities. A study of the prevailing reactions, their rates and products from banana peel processing through HTC is used to support the optimisation of the reactor design. The products’ yield is influenced by factors such as temperature, feed solid content, the nature of the biomass, and residence time. A detailed characterisation of all the products obtained from HTC is conducted. Considerable effort is needed to comprehend their stability and quality and thereby the ongoing process reactions and upgrading needs. Characterisation methods, such as GC/MS NMR, and HPLC for product analysis are critical to understand the nature of the reactive species influencing product quality and yield. Additionally, as efficient separation from an aqueous phase increases the yield of useful products, the separation of the main products and water is investigated. Furthermore, the feasibility of the recycle and re-use of the process water is analysed. The improvement and reuse of the hydrochar are appealing for applications such as solid fuel, pre-cursor for activated carbon, adsorbent, soil amendment or carbon sequestering biochar. Moreover, the use of HTC to convert banana peels into products such as hydrochar or bio-oil will enable the local rural communities create value from something they are discarding as waste. The hydrochar, processed into pellet form to increase its bulk density in order to reduce storage and transportation costs, can be directly used as a solid fuel that can be burned for energy. This is particularly effective for small and medium farms dispersed over extended areas, due to the significant reduction of expenses and environmental impact. The hydrochar can be added to soil to enhance the effects of the fertilisers, by reducing the amount of fertiliser lost through surface run-off. In addition, it increases the amount of water that can be retained by sandy soils, with a low available water capacity. The use of banana peels will produce highly effective sorbent hydrochars to be used for heavy metals removal from water. Moreover, our results suggest that the liquid fraction obtained from the hydrothermal processing of banana peel is a good feedstock for Microbial Fuel Cells. The hydrochar obtained in the process has shown to present several properties, such as the removal of various types of pollutants from contaminated waters. Therefore, the integration of HTC to convert banana peels into hydrochar and the utilization of the liquid by-product as feedstock for bioelectrochemical system (BES) technology enables full utilization of an otherwise recalcitrant waste. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/397d-synthesis-and-characterization-hydrochars-produced-hydrothermal-carbonization-banana-peels SN - 978-0-8169-1112-7 ER - TY - GEN A1 - De Mel, Ishanki A1 - Mechleri, Evgenia A1 - Demis, Panagiotis A1 - Dorneanu, Bogdan A1 - Klymenko, Oleksiy A1 - Arellano-García, Harvey T1 - A Methodology for Global Sensitivity Analysis for the Operation of Distributed Energy Systems Using a Two-Stage Approach T2 - 2019 AIChE Annual Meeting N2 - Optimisation-based models are often employed for the design and operation of distributed energy systems (DES). A two-stage approach often involves the optimisation of the design of a distributed energy system for a specified location or scale, and the subsequent optimisation of the operational model based on the structure recommended by the design model. The structure includes what types of generation and storage technologies should be used in the operation, related capacities and sizes, and potential locations. Often, both design and operational models are deterministic in nature, as either past or fictitious data is fed into the models to minimise an objective function such as the total cost or environmental impact due to carbon emissions. Consequently, the operational models encounter challenges when real-time data is fed, as time-variant input variables such as electricity demand, heating demand and solar insolation can be deemed uncertain. These variables could have unexpected and significant impacts on the total costs involved with the operation of distributed energy systems, leading to sub-optimality or even infeasibilities. Identifying these input variables, quantifying their uncertainties (which are then described in the models), and evaluating the influence of these variables on the outputs can lead to the design of more robust models. Such models can then be used to design and operate optimal distributed energy systems. This paper presents a novel methodology for using global sensitivity analysis (GSA) on an operational optimisation-based model of a distributed energy system. The operational model also utilises Model Predictive Control (MPC) rolling horizon concepts (as done by [1]) to determine hourly total operational costs. The paper also addresses how some challenges and limitations encountered in the operational model can be attributed to the deterministic design model on which the structure of the operational model has been based. Furthermore, the research explores how the design can be improved to support more robust operation. Another novel aspect of this paper highlights the use of the optimisation tool GAMS alongside SobolGSA, a global sensitivity analysis software [2]. This software uses the variance-based Sobol method to generate N samples and perform global sensitivity analysis, allowing users to understand how variations in the inputs can influence the outputs, whilst accounting for the different combinations of the uncertain parameters without varying one uncertain parameter at a time. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/373ah-methodology-global-sensitivity-analysis-operation-distributed-energy-systems-using-two-stage SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Mechleri, Evgenia A1 - Shafiei, Zarif A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Klymenko, Oleksiy T1 - A Blockchain Model for Residential Distributed Energy Resources Networks T2 - 2019 AIChE Annual Meeting N2 - The energy production landscape is reshaped by distributed energy resources (DERs) – photovoltaic (PV) panels, combined heat and power (CHP), wind turbines (WT), fuel cells or battery storage systems, to name just a few [1]. Microgrids, collections of units or DERs that are locally controlled, close to the consumption point and cooperating with each other and the centralised grid [2], allow for the reduction in energy losses compared to traditional generation due to the close proximity to end users. Due to its volatility, the integration of this non-controllable generation poses severe challenges to the current energy system and ensuring a reliable balance of energy becomes an increasingly demanding task [3]. The optimal design and scheduling of the DERs and subsequent microgrid is of high importance in order to increase the reliability and determine their effectiveness in reducing losses, emissions and costs compared to conventional generation so that they may be implemented at faster rates to reduce global emissions and fossil fuel usage. In distributed energy systems, individual users typically have flexible tariffs while they also have the capability not only to use, but also to store and trade electric power. Direct transactions schemes can save money for end users, generate revenues for producers, reduce transmission losses and promote the use of renewable energy [4]. But it must be a robust, efficient and low-cost trading system to handle the rapid changes of information and value in the system. The blockchain technology can fulfil these requirements by enabling the implementation of optimal energy management strategies through distributed databases. Since its introduction as the underlying technology of Bitcoin, the blockchain technology has emerged from its use as a verification mechanism for cryptocurrencies and heads to a broader field of applications. Blockchain-based systems are basically a combination of a distributed ledger, a decentralised consensus mechanism, and cryptographic security measures [5]. More precisely, it allows the resolution of conflicts and dismantles information asymmetries by providing transparent and valid records of past transactions that cannot be altered retrospectively [6]. With the help of specific algorithms and applications, multiple operations can be performed automatically on the blockchain, using this information together with information from the Internet or the real world (e.g. on whether, energy pricing, etc.). Furthermore, smart contracts can be implemented between the nodes of the microgrid. This paper introduces a model for the implementation of a blockchain and smart contracts into the scheduling of a residential DER network. The blockchain is implemented in terms of energy rather than voltages [7], to allow for the decentralised operation of the microgrid without a centralised microgrid aggregator. Thus, the model will minimise only the operational cost. Furthermore, the DER network model is improved by the addition of more detailed transmission losses and costs within the microgrid and between the microgrid and the national grid. The resulted energy flows are stored and information on the availability/demand are exchanged between the network nodes. To appropriately compensate the DER operators in the microgrid for their services and to charge the consumers for withdrawals, nodal clearing prices are determined and implemented through smart contracts. The resulting MILP model minimises the overall investment and operating costs of the system. Y1 - 2019 UR - https://www.aiche.org/conferences/aiche-annual-meeting/2019/proceeding/paper/373ai-blockchain-model-residential-distributed-energy-resources-networks SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Hajizeinalibioki, Sahar A1 - Sebastia-Saez, Daniel A1 - Klymenko, Oleksiy A1 - Arellano-García, Harvey T1 - Investigation of Two-Phase Flow Characteristics in a Fractal-Branching Microchannel T2 - AIChE Annual Meeting, November 10, 2019 to November 15, 2019 N2 - Inspiration from nature to solve advanced engineering problems has attracted the interests of engineers, designers and scientists. Biomimetics is to imitate and apply the elements, systems and mechanisms from nature to solve technological challenges as stated by Gleich et al. (2009). They also added that one of nature’s solution which is being explored is fractal shapes. Fractal shapes appeared in a variety of cases such as snowflakes, blood vessels and plant root systems in nature. Fractal shapes consistently appear in situations which require mass or heat transfer throughout a large space. The optimal spreading and transfer throughout the space characteristics of fractal shapes, making them a practical solution to design more efficient heat and mass transfer devices. Fractal shapes were first employed to improve fluid mechanics designs by West et al. (1997) to minimise the workflow for bulk fluid transportation through a network of branching tubes. On the other hand, two-phase flow in microscale channels has great applicability due to its diverse range of applications. As expressed by Serizawa et al. (2002), modern and advanced technologies such as micro-electro-mechanical systems, chemical process engineering, medical engineering and electronic cooling utilise multiphase flow in microchannels. This work aims to investigate the application of nature-inspired fractal geometries as multiphase microscale flow passage using CFD analysis. ANSYS Fluent software has been utilised to investigate the flow characteristics numerically in order to improve the pressure drop and heat transfer. Also, this question will be raised whether two-phase flow patterns in fractal microchannels are different from straight channels or not. Y1 - 2019 UR - https://aiche.confex.com/aiche/2019/meetingapp.cgi/Paper/577654 SN - 978-0-8169-1112-7 ER - TY - GEN A1 - Merino, Manuel A1 - Carrasco, Laura A1 - Dorneanu, Bogdan A1 - Manrique, Jose A1 - Menzhausen, Robert A1 - Arellano-García, Harvey T1 - Control Strategies for a Vapour Compression Refrigeration System Used in Mango Exports: An Alternative to Traditional on-Off Controllers T2 - AIChE Annual Meeting N2 - ropical fruits are important products on the global market. The change to a healthier nutrition, the development of new products and great availability led to a rise in their consumption during the last decade [1-2]. Due to their perishable nature they are stored at lower temperature. To achieve a rapid and efficient decrease in product temperature, refrigeration systems are employed, using vapor compression refrigeration plants. They consist of four main components: the compressor, the condenser, the expansion valve and the evaporator. Within the system a refrigerant is circulating. Though designed to satisfy maximum load, these plants usually work at part-load for much of their life, generally regulated by on/off cycles of the compressor, working at nominal frequency of 50 Hz [3]. The high cost involved in developing cold storage or controlled atmosphere storage is a pressing problem in several developing countries [4]. This contribution presents development and comparison of various strategies for the control of a refrigeration plant used for fruit cooling. The starting point is a model of the plant which is able to simulate both the chamber and the fruit temperature. The model is based on energy balances for each section of the refrigeration system and the fruits. Y1 - 2020 UR - https://www.aiche.org/academy/conferences/aiche-annual-meeting/2020/proceeding/paper/340c-control-strategies-vapour-compression-refrigeration-system-used-mango-exports-alternative SN - 978-0-8169-1114-1 ER - TY - GEN A1 - Miah, Sayeef A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Multi-Objective Design Optimisation of a Distributed Energy System through 3E (economic, environmental and exergy) Analysis T2 - 2020 Virtual AIChE Annual Meeting, November 20, 2020 N2 - To facilitate the commitments of reducing greenhouse gas emissions will require the utilisation of renewable energy resources, as well as shifting away from a centralised generation. Distributed energy systems (DESs) are a promising alternative to conventional centralised layouts. Thus, there is a need for the development of models able to optimally design DES which show savings in cost as well as having a low carbon impact. Current literature focuses on the design optimisation of a DES through economical and environmental cost minimisation [1-4]. However, these two criteria alone do not show the complete picture and do not satisfy the long-term sustainability priorities. The inclusion of exergy analysis allows for the satisfaction of this criteria through the rational use of energy resources. The use of exergy analysis within DESs was first studied by [5], with a multiobjective approach whereby cost and exergy efficiency are considered. The novelty of this paper is twofold. The first is the investigation of exergy DES design optimisation through a multiobjective approach whilst considering the economic and environmental cost, thus making this work the first to simultaneously minimise three objective functions in the context of DES. Y1 - 2020 UR - https://www.aiche.org/academy/conferences/aiche-annual-meeting/2020/proceeding/paper/340o-multi-objective-design-optimisation-distributed-energy-system-through-3e-economic-environmental SN - 978-0-8169-1114-1 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Heshmat, Mohamed A1 - Mohamed, Abdelrahim A1 - Ruan, Hang A1 - Xiao, Pei A1 - Gao, Yang A1 - Arellano-García, Harvey T1 - Stepping Towards the Industrial Sixth Sense T2 - AIChE Annual Meeting, November 20, 2020 N2 - Industry 4.0 is transforming chemical processes into complex, smart cyber-physical systems, by the addition of elements such as smart sensors, Internet of Things, big data analytics or cloud computing. Modern engineering systems and manufacturing processes are operating in highly dynamic environments, and exhibiting scale, structure and behaviour complexity. Under these conditions, plant operators find it extremely difficult to manage all the information available, infer the desired conditions of the plant and take timely decisions to handle abnormal operation1. Human beings acquire information from the surroundings through sensory receptors for vision, sound, smell, touch, and taste, the Five Senses. The sensory stimulus is converted to electrical signals as nerve impulse data communicated with the brain. When one or more senses fail, the humans are able to re-establish communication and improve the other senses to protect from incoming dangers. Furthermore, a mechanism of ‘reasoning’ has been developed during evolution, which enable analysis of present data and generation of a vision of the future, which might be called the Sixth Sense. As industrial processes are already equipped with five senses: ‘hearing’ from acoustic sensors, ‘smelling’ from gas and liquid sensors, ‘seeing’ from camera, ‘touching’ from vibration sensors and ‘tasting’ from composition monitors, the Sixth Sense could be achieved by forming a sensing network which is self-adaptive and self-repairing, carrying out deep-thinking analysis with even limited data, and predicting the sequence of events via integrated system modelling. This contribution introduces the development of an intelligent monitoring and control framework for chemical process, integrating the advantages of Industry 4.0 technologies, cooperative control and fault detection via wireless sensor networks. Y1 - 2020 UR - https://www.aiche.org/academy/videos/conference-presentations/stepping-towards-industrial-sixth-sense SN - 978-0-8169-1114-1 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Towards smart distributed energy systems T2 - Jahrestreffen der ProcessNet-Fachgemeinschaften "Prozess-, Apparate- und Anlagentechnik" (PAAT) N2 - A distributed energy resource (DER) system is an energy generation system located in the vicinity of the end users, simultaneously providing electricity, cooling and heating to meet the demands of the local users1. Unlike conventional, centralized energy supply, a DER system typically employs a wide range of technologies such as photovoltaics, wind turbines, gas turbines, biomass boilers, combined heating and power, absorption chillers, etc. In addition, energy storage technologies (batteries, hot/cold water storage) are available as well. DER systems can potentially play a vital role as the energy sector faces unprecedented challenges to reduce emissions by increasing energy generation using renewable and low-carbon energy resources. Different designs of the DER systems could lead to different performance in reducing the costs, the environmental impact or the use of primary energy. Hence, optimal design and management of complex DER systems are important tasks to promote their diffusion against the centralized grid. However, current operational models for DERs do not adequately analyse the complexity of such systems. This contribution presents a set of models for the optimal design and operation of residential DER systems, which build up on previous work in this field, and aims to provide a more holistic overview of such systems. For each node in the DER system, there is an option of installing the following ten technologies: wind turbines, photovoltaics arrays, combined heating and power units, absorption chillers, air-conditioning units, gas boilers, biomass boilers, gas heaters, batteries and thermal storage. Only one of each item may be installed in each home. There is also the option to connect a house to another via a combined hot and cold water pipeline and/or a microgrid cable, to share thermal and electrical energy, respectively. Due to increased availability of government incentives such as the feed-in tariffs (FIT) and renewable heat incentives (RHI) payments, these are included in the model as well. The increased penetration of Internet of Things technology and their potential to better control and optimize DER systems enable its use to help stabilize national grids. To this end, the models include the use of dynamic pricing, a strategy in which national grids publish in real time variable prices for electricity within given time periods. Furthermore, as current literature’s focus on economic and environmental cost minimization, which do not satisfy long-term sustainability priorities through the rational use of energy resources, the introduction of a third criteria, exergy, is investigated. A third novelty of this contribution is the consideration of a multi-objective optimization which simultaneously includes the three objectives: the economic, the environmental and exergetic criteria in the design and operation of the residential DER system. Additionally, a novel methodology to analyse the effect of uncertain input variables on the total daily cost of the DER operational models. The methodology combines the operational model with model predictive control to predict the current state of the model. A subset of the model inputs (i.e., electricity demand, heating demand, and insolation) are considered uncertain. Global sensitivity analysis is conducted to quantify and understand how the uncertain variables influence, both individually and through interactions, the total daily cost. Finally, the implementation of blockchain technology and smart contracts within optimally designed and scheduled DER systems is investigated, to assess the advantages of smart technologies on the efficiency of residential DERs. Challenges, limitations and suggestions for improving the overall design and operation are also discussed in detail. All models are developed as mixed-integer linear programming models implemented and solved in GAMS, and show significant reduction of costs for all considered criteria when compared to the centralised grid and the classical approach towards the modelling of DER systems. Y1 - 2023 UR - https://www.researchgate.net/publication/388185482_Towards_smart_distributed_energy_systems ER - TY - GEN A1 - Gonzalez-Arias, Judith A1 - Gonzalez-Castano, Miriam A1 - Arellano-García, Harvey T1 - Utilization of CO2-Rich Residues for Syngas Production: Strategies for Catalyst Design T2 - AIChE Annual Meeting, November 15, 2021 N2 - Compared to a Reverse Water Gas Shift (RWGS) process carried out under ideal conditions, the valorization of CO2-rich residues involve additional challenges. Indeed, for an ideal RWGS reaction unit, the CO2 methanation reaction and the constitution of carbon deposits via Boudouard reaction are the main side reactions to take into consideration. For CO2-rich residues derived from biomass treatment and heavy metal industries, the presence of CH4 and CO species (among others) constitute an, although often disregarded, much complex panorama where side reactions like CO methanation, dry reforming of methane, the forward Water Gas Shift reaction and the decomposition of CO and CH4 resulting in carbon deposits, are occurring to some extent within the catalytic reactor. This work aimed at designing advanced catalytic systems capable of converting the CO2/CO/CH4 feedstocks into syngas mixtures. Thus, with the RWGS reaction considered as the major process, this work focusses on the side reactions involving CO/CH4 species. In this context, a series Cu-MnOx/Al2O3 spinel derived catalysts were optimized for syngas production in presence of CO and CH4 fractions. Once the optimal active phase was determined, the optimal Cu contents and the impact of the support nature (Al2O3, SiO2-Al2O3 and CeO2-Al2O3) was evaluated for the valorization of realistic CO2-rich feedstocks. Remarkably, the obtained outcomes underline operative strategies for developing catalytic systems with advanced implementation potential. For that aim, the catalyst design should present, along with an active and selective phase for RWGS reaction, superior cooking resistances, activities towards methane reforming and low tendencies towards the forward WGS reaction. Further developments should tackle difficult tasks like improving the RWGS reaction rate while inhibiting the forwards WGS reaction as well as improving the CH4 conversion to CO without affecting the process selectivity. Strategies towards advancing catalytic systems capable of operating under variable conditions also arise as appealing routes. Y1 - 2021 UR - https://www.aiche.org/academy/conferences/aiche-annual-meeting/2021/proceeding/paper/661v-utilization-co2-rich-residues-syngas-production-strategies-catalyst-design UR - https://plan.core-apps.com/aiche2021/event/30d89249d0653ff1de80a79e11b79a16 SN - 978-0-8169-1116-5 ER - TY - GEN A1 - Arellano-García, Harvey A1 - El Bari, Hassan A1 - Kalibe Fanezoune, Casimir A1 - Dorneanu, Bogdan A1 - Majozi, Thokozani A1 - Elhenawy, Yasser A1 - Bayssi, Oussama A1 - Hirt, Ayoub A1 - Peixinho, Jorge A1 - Dhahak, Asma A1 - Gadalla, Mamdouh A. A1 - Khashaba, Nourhan H. A1 - Ashour, Fatma T1 - Catalytic Fast Pyrolysis of Lignocellulosic Biomass: Recent Advances and Comprehensive Overview T2 - Journal of Analytical and Applied Pyrolysis N2 - Using biomass as a renewable resource to produce biofuels and high-value chemicals through fast pyrolysis offers significant application value and wide market possibilities, especially in light of the current energy and environmental constraints. Bio-oil from fast-pyrolysis has various conveniences over raw biomass, including simpler transportation and storage and a higher energy density. The catalytic fast pyrolysis (CFP) is a complex technology which is affected by several parameters, mainly the biomass type, composition, and the interaction between components, process operation, catalysts, reactor types, and production scale or pre-treatment techniques. Nevertheless, due to its complicated makeup, high water and oxygen presence, low heating value, unstable nature, elevated viscosity, corrosiveness, and insolubility within conventional fuels, crude bio-oil has drawbacks. In this context, catalysts are added to reactor to decrease activation energy, substitute the output composition, and create valuable compounds and higher-grade fuels. The study aim is to explore the suitability of lignocellulosic biomasses as an alternative feedstock in CFP for the optimization of bio-oil production. Furthermore, we provide an up-to-date review of the challenges in bio-oil production from CFP, including the factors and parameters that affect its production and the effect of used catalysis on its quality and yield. In addition, this work describes the advanced upgrading methods and applications used for products from CFP, the modeling and simulation of the CFP process, and the application of life cycle assessment. The complicated fluid dynamics and heat transfer mechanisms that take place during the pyrolysis process have been better understood due to the use of CFD modeling in studies on biomass fast pyrolysis. Zeolites have been reported for their superior performance in bio-oil upgrading. Indeed, Zeolites as catalyses have demonstrated significant catalytic effects in boosting dehydration and cracking process, resulting in the production of final liquid products with elevated H/C ratios and small C/O ratios. Combining ex-situ and in-situ catalytic pyrolysis can leverage the benefits of both approaches. Recent studies recommend more and more the development of pyrolysis-based bio-refinery processes where these approaches are combined in an optimal way, considering sustainable and circular approaches. KW - Catalytic fast pyrolysis KW - Lignocellulosic Biomass KW - Bio-Oil KW - Modelling Y1 - 2024 U6 - https://doi.org/10.1016/j.jaap.2024.106390 SN - 0165-2370 VL - Vol. 178 ER - TY - GEN A1 - Arellano-García, Harvey A1 - Safdar, Muddasar A1 - Shezad, Nasir A1 - Akhtar, Farid T1 - Development of Ni-doped A-site lanthanides-based perovskite-type oxide catalysts for CO2 methanation by auto-combustion method T2 - RSC Advances N2 - Engineering the interfacial interaction between the active metal element and support material is a promising strategy for improving the performance of catalysts toward CO2 methanation. Herein, the Ni-doped rare-earth metal-based A-site substituted perovskite-type oxide catalysts (Ni/AMnO3; A = Sm, La, Nd, Ce, Pr) were synthesized by auto-combustion method, thoroughly characterized, and evaluated for CO2 methanation reaction. The XRD analysis confirmed the perovskite structure and the formation of nano-size particles with crystallite sizes ranging from 18 to 47 nm. The Ni/CeMnO3 catalyst exhibited a higher CO2 conversion rate of 6.6 × 10−5 molCO2 gcat−1 s−1 and high selectivity towards CH4 formation due to the surface composition of the active sites and capability to activate CO2 molecules under redox property adopted associative and dissociative mechanisms. The higher activity of the catalyst could be attributed to the strong metal–support interface, available active sites, surface basicity, and higher surface area. XRD analysis of spent catalysts showed enlarged crystallite size, indicating particle aggregation during the reaction; nevertheless, the cerium-containing catalyst displayed the least increase, demonstrating resilience, structural stability, and potential for CO2 methanation reaction. KW - perovskite KW - CO2 methanation KW - lanthanide KW - auto-combustion method Y1 - 2024 UR - https://pubs.rsc.org/en/content/articlelanding/2024/ra/d4ra02106a U6 - https://doi.org/10.1039/d4ra02106a VL - 2024 IS - 14 SP - 20240 EP - 20253 ER - TY - GEN A1 - Medina Méndez, Juan Ali A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Homogeneous modeling for laminar flows in structured catalysts: CO2 methanation T2 - Book of Abstracts zur Jahrestagung der DECHEMA/VDI-Fachgruppe Fluidverfahrenstechnik, 04. – 06. März 2024 Y1 - 2024 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Medina_2024_AbstractDechemaFluidverfahrenstechnik_Catalysts.pdf PB - Ruhr Universität CY - Bochum ER - TY - GEN A1 - Medina Méndez, Juan Ali A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Homogeneous modeling for laminar flows in structured catalysts: CO2 methanation Y1 - 2024 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Medina_2024_Poster_DECHEMA2024_Fluidverfahrenstechnik.pdf CY - Bochum ER - TY - GEN A1 - Medina Méndez, Juan Ali A1 - Dorneanu, Bogdan A1 - Schmidt, Heiko A1 - Arellano-García, Harvey T1 - Revisiting homogeneous modeling with volume averaging theory: structured catalysts for steam reforming and CO2 methanation T2 - Journal of Physics: Conference Series N2 - Progress in the modeling of structured catalysts is crucial for enhancing efficiency and scalability in industrial applications. Extensive research has investigated reactive flows over catalyst surfaces, covering chemical kinetics analysis and (direct) numerical simulations of the complete fluid flow in fixed-bed or structured catalysts. Nonetheless, this comes at a high computational cost. This study focuses on the homogeneous modeling of structured catalysts utilizing volume-averaging theory (VAT) as a more efficient method for representing the behaviour of such systems. We discuss modeling strategies for both 1-D and 3-D simulations. For steady 1-D flow simulations, we assess the influence of simplified gas chemical kinetics versus detailed surface chemistry, comparing with experimental data from the literature for a CO2 methanation processes. We also simulate 3-D flows of a steam reforming process, previously studied in the literature, using models which rely on different assumptions regarding the nature of the porous catalyst. Our findings reveal significant discrepancies based on different modeling assumptions, underscoring the necessity for accurate modeling of permeability and diffusivity tensors in homogeneous models. Y1 - 2024 U6 - https://doi.org/10.1088/1742-6596/2899/1/012004 SN - 1742-6596 VL - 2899/2024 ER - TY - GEN A1 - Medina Méndez, Juan Alí A1 - Dorneanu, Bogdan A1 - Schmidt, Heiko A1 - Arellano-García, Harvey T1 - Revisiting homogeneous modeling with volume averaging theory: structured catalysts for steam reforming and CO2 methanation T2 - Book of Abstracts XXVI Fluid Mechanics Conference (FMC 2024), Warsaw, Poland, September 10-13, 2024 Y1 - 2024 UR - https://www-docs.b-tu.de/fg-stroemungsmodellierung/public/Medina_2024_AbstractFMC26_Catalysts.pdf PB - University of Technology CY - Warsaw ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Mappas, Vassileios A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Novel parametric gradient calculation method for multistage systems with generalized constraints T2 - 2024 AIChE Annual Meeting N2 - Sensitivity and gradient evaluations are essential for understanding the variability of a system subject to changes in input parameters, aiding in applications such as optimization, control, or decision-making processes (Castillo et al., 2008; Logsdon and Biegler, 1989, Horn and Tsai, 1967). Various approaches are available for the gradient evaluation in the simulation of large-scale steady-state systems, utilizing techniques such as automatic differentiation, sensitivity analysis, optimization or machine learning (Amaran et al., 2016). The term large-scale refers to problems with a substantial number of design variables, structural state variables, or constraint functions, or a combination thereof, necessitating significant high-performance parallel computing resources to solve within a reasonable timeframe (Kennedy and Martins, 2014). However, the evaluation of gradients in large-scale multistage systems simulation poses significant challenges due to computational complexity, numerical instability, scalability issues, and the limitations of the traditional differentiation techniques. Additionally, model complexity, sensitivity to noise, and data requirements of machine learning-based approaches further amplify these challenges. Overcoming these obstacles necessitates the development of efficient, scalable and robust gradient evaluation techniques that can effectively handle the characteristics of large-scale systems while offering reliable insights for a wide array of applications. This contribution focuses on re-examining and advancing the evaluation of parametric sensitivities within the context of simulating highly complex, hierarchical multiscale modular systems of very large size. The models being analyzed may necessitate sensitivity evaluations concerning their response to parametric inputs. These evaluations serve not only to test and verify their robustness, but also to integrate them into modular structures within a comprehensive optimization framework. Such an optimization framework aims to enhance system performance based on selected criteria, while simultaneously adhering to essential optimality constraints. While gradient-free optimization methods have been successfully applied to important design problems, their applications typically involve no more than O(102) design variables, and these methods exhibit very poor scalability with the dimensionality of the design variables (Kennedy and Martins, 2014). For large-scale, high-fidelity applications, gradient-based methods are deemed more suitable, although the challenges related to computational time and accuracy need to be addressed. To address these challenges, the use of either sensitivities or appropriately generalized adjoint equations for efficient calculation of constraint and objective functions gradients for generalized multistage systems, irrespective of whether they are dynamic in nature or they are steady-state. The proposed approach adopts a generalized modular strategy suitable for any type of system, starting from a traditional sensitivity-based calculations initially, and subsequently developing a novel generalized adjoint-based method. The resulting algorithm comprises a sequence of forward and backward sweep computational steps, which are entirely equivalent, and serve as a generalization of the adjoint-based calculation methods for gradients of constraints. These methods find application in various numerical analysis computations related to dynamical systems, including optimal control problems. It has to be noted that the model is regarded as a general modular representation of any coupled system, without making a distinction between dynamic or steady-state systems. In this context, a dynamic system is perceived as having state profiles as private internal variables, while interacting with its external environment through the input of initial conditions and parameter values. Its output consists of final conditions or any internal trajectory points that require reporting to the external environment during dynamic simulation. The proposed strategy using a novel adjoint scheme generalizes this approach to any multistage system model, of which the stages need not be of dynamic nature, such as in the use of adjoint equations in optimal control of multistage Differential- Algebraic Equation (DAE) systems (Morison and Sargent, 1986). The choice between the use of the adjoint- and the sensitivity-based approach depends on the balance between the number of constraints/functions requiring gradient evaluation, and the number of states in the underlying dynamical system. The adjoint-based approach may be advantageous when dealing with a smaller number of constraints than state variables that require gradient evaluation, whereas the sensitivity-based approach could be more computationally efficient for a larger number of constraints than state variables in the modular treatment of the underlying dynamic system. The simulation of a multistage system is demonstrated using an example consisting of steady-state feedforward blocks, employing both the sensitivity- and the proposed adjoint-based approach. The results obtained reveal that the numerical values derived from the gradient evaluation are identical for both methods. Therefore, it can be concluded that the newly introduced approach for general multistage sequential systems is entirely non-restrictive. This indicates its effectiveness and applicability, offering flexibility and robustness in gradient evaluation for such systems. Y1 - 2024 UR - https://www.researchgate.net/publication/388185581_Novel_parametric_gradient_calculation_method_for_multistage_systems_with_generalized_constraints ER - TY - GEN A1 - Safdar, Muddasar A1 - Dorneanu, Bogdan A1 - Santos da Silva, Jefferson A1 - Santos Mascarenhas, Artur Jose A1 - Valverde Pontes, Karen A1 - Arellano-García, Harvey T1 - Advancements in CO2 methanation: customized heterogeneous Ni-Perovskite catalyst for sustainable SNG production T2 - Annual Meeting on Reaction Engineering and Electrochemical Processes 2024 Y1 - 2024 UR - https://www.researchgate.net/publication/388185658_Advancements_in_CO2_methanation_Customized_Heterogeneous_Ni-Perovskite_Catalyst_for_Sustainable_SNG_Production ER - TY - GEN A1 - Mappas, Vassileios A1 - Dorneanu, Bogdan A1 - Heinzelmann, Norbert A1 - Schnitzlein, Klaus A1 - Arellano-García, Harvey T1 - A unified modular framework for modeling multiphase reactors T2 - Annual Meeting of Process Engineering and Materials Technology 2024 Y1 - 2024 UR - https://www.researchgate.net/publication/388143505_A_unified_modular_framework_for_modeling_multiphase_reactors ER - TY - GEN A1 - Jafari, Mitra A1 - Shafiee, Parisa A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Towards efficient material design: use of machine learning to predict chemical reactions and retrosynthesis T2 - Annual Meeting of Process Engineering and Materials Technology 2024 Y1 - 2024 UR - https://www.researchgate.net/publication/388143384_Towards_efficient_material_design_Use_of_Machine_Learning_to_predict_chemical_reactions_and_retrosynthesis ER - TY - GEN A1 - Yentumi, Richard A1 - Jurischka, Constantin A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Optimal design of a thermochemical hydrogen storage and release system via the reversible redox of iron oxide/iron T2 - Annual Meeting of Process Engineering and Materials Technology 2024 Y1 - 2024 UR - https://www.researchgate.net/publication/388143925_Thermochemical_Hydrogen_Storage_via_the_Reversible_Reduction_and_Oxidation_of_Metal_Oxides ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Vassiladis, Vassilios S. A1 - Arellano-García, Harvey T1 - A novel approach to staggered training of deep learning networks T2 - Annual Meeting of Process Engineering and Materials Technology 2024 Y1 - 2024 UR - https://www.researchgate.net/publication/388143628_A_novel_approach_to_staggered_training_of_deep_learning_networks ER - TY - GEN A1 - Safdar, Muddasar A1 - Safdar, Mutahar A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Process intensification by additive manufacturing strategies for power-to-X conversion application: Case studies T2 - 16th International Conference on Gas–Liquid and Gas–Liquid–Solid Reactor Engineering Y1 - 2024 UR - https://www.researchgate.net/publication/388185473_Process_Intensification_by_Additive_Manufacturing_Strategies_for_Power-to-X_Conversion_Application_Case_Studies ER - TY - GEN A1 - Jafari, Mitra A1 - Mbuya, Christel-Olivier Lenge A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Sustainable aviation fuel production through Fischer-Tropsch synthesis and hydrocracking integration using Co bifunctional catalysts: Support effects T2 - 18th International Congress on Catalysis N2 - Considering the increasing demand for clean and sustainable aviation fuel, in this study, cobalt bifunctional catalysts are used to convert syngas from biomass to aviation fuel. Y1 - 2024 UR - https://www.researchgate.net/publication/388109868_Sustainable_aviation_fuel_production_through_Fischer-Tropsch_synthesis_and_hydrocracking_integration_using_Co_bifunctional_catalysts_Support_effects ER - TY - GEN A1 - Alves Amorim, Ana Paula A1 - Valverde Pontes, Karen A1 - Dorneanu, Bogdan A1 - Arellano-Garcia, Harvey T1 - Optimizing microgrid design and operation : a decision-making framework for residential distributed energy systems in Brazil T2 - Chemical Engineering Research and Design N2 - This paper explores the optimization of microgrid design and operation for residential distributed energy systems in Brazil, addressing the growing demand for sustainable energy in the context of climate change. A decision-making framework based on Mixed-Integer Nonlinear Programming (MINLP) is proposed to integrate distributed energy resources (DERs) such as solar, wind, and biogas. Key challenges include managing the variability of renewable resources and complying with local regulations, while also addressing gaps in literature, particularly the impact of time-dependent efficiency profiles on energy sharing within microgrids. By employing innovative analyses and clustering techniques, the research optimizes microgrid configurations, accounting for seasonal demand fluctuations and the influence of incentive policies on system feasibility. The findings reveal that incorporating a time-dependent efficiency model can reduce total costs by 45 %. This reduction underscores the importance of accurate efficiency predictions, as the model captures variations in energy generation and utilization efficiency over time, improving system optimization. Additionally, the findings reveal that a well-structured optimization model can meet 100 % of electricity and hot water demands across all scenarios, with customized incentives playing a crucial role in reducing costs and promoting sustainability. Y1 - 2025 UR - https://www.sciencedirect.com/science/article/pii/S0263876224007123?via%3Dihub U6 - https://doi.org/https://doi.org/10.1016/j.cherd.2024.12.033 SN - 0263-8762 VL - 214 (2025) IS - February 2025 SP - 251 EP - 268 PB - Elsevier ER - TY - GEN A1 - Shafiee, Parisa A1 - Dorneanu, Bogdan A1 - Arellano-Garcia, Harvey T1 - Towards Machine Learning-driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis T2 - Chemical Engineering Transactions N2 - Fischer-Tropsch synthesis (FTS) offers a promising route for producing sustainable jet fuels from syngas. However, optimizing the catalyst design and operating conditions to maximize the desired C8-C16 jet fuel range is a challenging task. This study introduces the application of a machine learning (ML) framework to guide the design of Co/Fe-supported FTS catalysts and operating conditions for enhanced fuel selectivity. A comprehensive dataset was constructed with 21 input features spanning catalyst structure, preparation method, activation procedure, and FTS operating parameters. The random forest ML algorithm was evaluated for predicting CO conversion and C8-C16 selectivity using this dataset. Feature engineering identified the most significant descriptors influencing performance. A principal component analysis reduced the dataset dimensionality prior to ML modelling. The random forest algorithm achieved high prediction accuracy for the conversion of CO (R2 = 0.92) and C8-C16 selectivity (R2 = 0.90). In addition to confirming the known effects of operating conditions, key roles of Co/Fe-supported properties were elucidated. This ML framework provides a powerful tool for the rational design of FTS catalysts and operating windows to maximize jet fuel productivity Y1 - 2024 UR - https://www.cetjournal.it/cet/24/114/098.pdf U6 - https://doi.org/10.3303/CET24114098 SN - 2283-9216 VL - 114 SP - 583 EP - 588 ER - TY - GEN A1 - Mappas, Vasileios K. A1 - Dorneanu, Bogdan A1 - Heinzelmann, Norbert A1 - Arellano-Garcia, Harvey T1 - Multiphase Catalytic Reactors: a Modular Approach T2 - Chemical Engineering Transactions N2 - Currently, state-of-the-art approaches to simulating the behaviour of trickle-bed reactors (TBRs) have focused solely on methods requiring high computational time and are unable to tackle systems with a large number of particles. In this work, a modular methodology based on a Lagrangian approach to TBR modelling is presented, which overcomes these drawbacks by implementing a simulation framework where different modules are interconnected and relevant information is transferred between them. The novelty of this framework stems from its adaptable configuration and its modular and unified setup, enabling it to accommodate both local and global multiscale events. The proposed methodology includes modules for the packing generation, liquid flow simulation, and of reaction system modelling within the reactor. To illustrate the procedure, a case study is discussed while demonstrating the potential of the presented approach. The results were validated against data obtained from a purpose-built experimental setup showing good agreement. The main advantages of this approach lie in its efficiency, the interrelation between different modules, and its ability to capture a wide range of information and phenomena. Y1 - 2024 UR - https://www.cetjournal.it/cet/24/114/097.pdf U6 - https://doi.org/10.3303/CET24114097 SN - 2283-9216 VL - 114 SP - 577 EP - 582 ER - TY - CHAP A1 - Jafar Khan, Maria A1 - Safdar, Muddasar A1 - Jafari, Mitra A1 - Arellano-Garcia, Harvey T1 - Methods of indirect conversion of CO2 to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - The promptly increasing CO2 concentration in the atmosphere causes a major climate change, requiring effective way of its mitigation. The indirect conversion of CO2 to methanol via syngas is a promising strategy to control greenhouse gas emissions and produce valuable feedstock's and chemicals. This chapter focuses on different indirect CO2 conversion methods to methanol, multistep processes that involve capturing of carbon dioxide, intermediate formation syngas, type of catalyst used, and then hydrogenation to methanol. Indirect conversion of CO2 involves two steps, the production of syngas which is known as a mixture of carbon monoxide and hydrogen followed by methanol integration and catalyst-based hydrogenation of CO2. The economic feasibility, the effectiveness of different methods, development, and optimization of catalysts along with reaction conditions are thoroughly discussed in this chapter. The chapter concluded with the direction of suitable methods to convert carbon dioxide into methanol along with the future research development in the methodology to reduce greenhouse emissions and advance the production of sustainable chemicals. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00155-5 VL - 2024 PB - Elsevier ER - TY - CHAP A1 - Shafiee, Parisa A1 - Arellano-Garcia, Harvey T1 - Photocatalysts in CO2 direct conversion to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - The escalating global industrialization has led to fossil fuel scarcity and environmental deterioration, with CO2 levels rising significantly. To combat climate change, researchers are focusing on renewable energy and carbon capture technologies. This chapter reviews recent progress on photocatalytic conversion of CO2 to methanol, a promising approach for greenhouse gas reduction and sustainable energy production. Methanol, a versatile chemical feedstock and potential renewable fuel, can be synthesized from CO2 using solar energy and semiconductor photocatalysts. This chapter covers the fundamentals, mechanisms, materials development, photocatalysts design strategies, and preparation processes for this technology. Despite challenges in achieving high efficiency, CO2 photocatalytic reduction to methanol offers an attractive green alternative to traditional fossil-based methanol production. This comprehensive overview consolidates the current research landscape, providing insights to guide future advancements towards scalable and economically viable CO2 photocatalytic methanol synthesis. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00121-X VL - 2024 ER - TY - CHAP A1 - Shafiee, Parisa A1 - Arellano-Garcia, Harvey T1 - Heterogeneous and Homogeneous Catalysts in CO2 Direct Conversion to Methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - Catalytic conversion of CO2 into valuable products offers a promising solution to mitigate climate change by closing the carbon cycle. However, activating the thermodynamically stable and kinetically inert CO2 molecule remains a significant scientific challenge. This chapter focuses on homogeneous and heterogeneous catalysts for the direct conversion of CO2 to methanol, a valuable chemical feedstock and potential fuel. It introduces the importance of this process for reducing carbon emissions and outlines the chapter's objectives. The fundamentals of heterogeneous catalysis and catalyst design principles for methanol synthesis from CO2 are discussed. Various types of heterogeneous catalysts are examined, along with the mechanisms involved in CO2 activation and hydrogenation to methanol. Strategies to enhance catalyst selectivity, product distribution, and performance are explored, as well as challenges and future research directions. This comprehensive chapter serves as a guide to understanding the pivotal role of heterogeneous catalysts in the direct catalytic conversion of CO2 to methanol. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00119-1 VL - 2024 PB - Elsevier ER - TY - CHAP A1 - Jafari, Mitra A1 - Arellano-Garcia, Harvey T1 - CO2 sources and features for direct CO2 conversion to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - In recent years, global concern over climate change caused by the accumulation of atmospheric CO2 has intensified. While various technologies for capturing CO2 have been proposed, utilizing captured CO2 from power plants is gaining popularity due to the concerns about the safety and effectiveness of underground and ocean storage methods. This article explores several techniques for utilizing CO2 from exhaust gases emitted by power plants. It provides a comprehensive review of current and emerging technologies worldwide that aim to harness CO2 for beneficial purposes. The conversion of CO2 into chemicals and energy products represents a promising approach to not only mitigate CO2 emissions but also enhance economic value. However, since CO2 lacks hydrogen, which is essential for many chemical processes, the development of clean, sustainable, and cost-effective hydrogen sources is crucial. This chapter delves into the literature surrounding the production of biofuels derived from microalgae cultivated using captured CO2, the conversion of CO2 combined with hydrogen into various chemicals, specially methanol and the exploration of sustainable hydrogen sources. These efforts collectively underscore the potential of CO2 utilization as a pivotal strategy in the battle against climate change and for fostering sustainable industrial practices. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00127-0 VL - 2024 ER - TY - CHAP A1 - Jafari, Mitra A1 - Arellano-Garcia, Harvey T1 - Shift from syngas to CO2 for methanol production T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - This chapter delves into diverse methodologies for converting carbon dioxide (CO2) into methanol, employing homogeneous and heterogeneous catalysts through hydrogenation, photochemical, electrochemical, and photo-electrochemical techniques. Given the significant contribution of CO2 to global warming, utilizing it for fuel and chemical production stands as a sustainable approach to environmental conservation. However, due to high stability and low reactivity of CO2, the development of appropriate methods and catalysts is crucial for breaking its bonds to yield valuable chemicals like methanol. Also, in this chapter various methods and their mechanisms for CO2 conversion to methanol are described. Finally, new types of catalyst and their characteristics for CO2 hydrogenation to methanol are introduced and discussed in detail. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00126-9 VL - 2024 ER - TY - CHAP A1 - Shafiee, Parisa A1 - Arellano-Garcia, Harvey T1 - Electrocatalysts in CO2 direct conversion to methanol T2 - Reference Module in Chemistry, Molecular Sciences and Chemical Engineering N2 - By now, atmospheric CO2 levels necessitate new ways of reducing them more than ever with increasing global warming and climate change. Converting CO2 into valuable products like methanol fuel presents a solution by reducing atmospheric CO2 while creating economic opportunities. This chapter reviews the state-of-the-art in electrocatalytic CO2-to-methanol conversion technologies, covering basic electrocatalysis principles, electrocatalyst materials, design strategies, performance optimization, mechanistic pathways, catalyst compositions, technological hurdles, and potential solutions. It also examines environmental impacts, economic aspects, and scaling up possibilities, aiming to provide a comprehensive technological, economic and environmental overview of this sustainable energy solution for climate change mitigation, highlighting the critical role of innovation in addressing global challenges for a more sustainable future. Y1 - 2024 U6 - https://doi.org/https://doi.org/10.1016/B978-0-443-15740-0.00120-8 VL - 2024 ER - TY - GEN A1 - Mappas, Vassileios A1 - Dorneanu, Bogdan A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Multistage optimal control and nonlinear programming formulation for automated control loop selection T2 - Computer Aided Chemical Engineering N2 - Control loop design, as well as controller tuning, constitute the pillars of process control to achieve design specifications and smooth process operation, and to meet predefined performance criteria. Currently, state-of-the-art approaches have focused on methods that yield only the pairings between input and output methods, and are not able to incorporate path and end-point constraints. This work introduces a novel strategy based on the multistage optimal control formulation of the control loop selection problem. This approach overcomes the drawbacks of traditional methods by producing an automated integrated solution for the task of control loop design. Furthermore, it obviates the need for any form of combinatorial optimization and incorporating path and terminal constraints. The results show that the proposed solution framework produces the same control loops as in the case of traditional approaches, however the inclusion of path and end-point constraints improves the performance of the control profiles. Y1 - 2024 U6 - https://doi.org/10.1016/B978-0-443-28824-1.50327-6 SN - 1570-7946 VL - 53 SP - 1957 EP - 1962 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Keykha, Mina A1 - Arellano-García, Harvey T1 - Assessment of parameter uncertainty in the maintenance scheduling of reverse osmosis networks via a multistage optimal control reformulation T2 - Computer Aided Chemical Engineering N2 - In this work, the influence of uncertain parameters on the maintenance scheduling of Reverse Osmosis Networks (RONs) is explored. Based on a foundation of successful applications in various maintenance optimization domains, this paper extends the methodology to the domain of RON regeneration actions planning, highlighting its adaptability to diverse areas of dynamic processes with planning uncertainty. Traditional approaches in membrane cleaning scheduling have predominantly relied on MixedInteger Nonlinear Programming (MINLP), often leading to combinatorial problems that fail to capture the dynamic nature of the system. As part of this study, a novel approach based on the Multistage Integer Nonlinear Optimal Control Problem (MSINOCP) formulation is used to automate and optimize membrane cleaning scheduling without requiring combinatorial optimization. To evaluate the consequences of parameter uncertainty, 26 scenarios are considered in which the cost of the energy unit is considered as variable based on a random distribution, and these results are compared to a scenario where a fixed cost parameter is assumed. The findings show that when the cost of energy is considered as an uncertain parameter, the optimization process requires more frequent cleaning measures. Y1 - 2024 U6 - https://doi.org/10.1016/B978-0-443-28824-1.50326-4 SN - 1570-7946 VL - 53 SP - 1951 EP - 1956 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Zhang, Sushen A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Optimizing deep neural networks through hierarchical multiscale parameter tuning T2 - Computer Aided Chemical Engineering N2 - Deep neural networks (DNNs) are frequently employed for information extraction in big data applications across various domains; however, their application in real-time industrial systems is hindered by constraints such as limited computational, storage capacity, energy availability, and time constraints. This contribution introduces the development of a novel hierarchical multiscale framework for the training of DNNs that incorporates neural sensitivity analysis for the automatic and selective training of neurons evaluated to be the most effective. This alternative training methodology generates local minima that closely match or surpass those achieved by traditional approaches, such as the backpropagation method, utilizing identical starting points for comparative purposes. Y1 - 2024 U6 - https://doi.org/10.1016/B978-0-443-28824-1.50155-1 SN - 1570-7946 VL - 53 SP - 925 EP - 930 ER - TY - GEN A1 - Vassiliadis, Vassilios S. A1 - Mappas, Vassileios A1 - Espaas, Tomas A. A1 - Dorneanu, Bogdan A1 - Isafiade, Adeniyi A1 - Möller, Klaus A1 - Arellano-García, Harvey T1 - Reloading process systems engineering within chemical engineering T2 - Chemical Engineering Research and Design N2 - Established as a sub-discipline of Chemical Engineering in the 1960s by the late Professor R.W.H. Sargent at Imperial College London, Process Systems Engineering (PSE) has played a significant role in advancing the field, positioning it as a leading engineering discipline in the contemporary technological landscape. Rooted in Applied Mathematics and Computing, PSE aligns with the key components driving advancements in our modern, information-centric era. Sargent’s visionary foresight anticipated the evolution of early computational tools into fundamental elements for future technological and scientific breakthroughs, all while maintaining a central focus on Chemical Engineering. This paper aims to present concise and concrete ideas for propelling PSE into a new era of progress. The objective is twofold: to preserve PSE’s extensive and diverse knowledge base and to reposition it more prominently within modern Chemical Engineering, while also establishing robust connections with other data-driven engineering and applied science domains that play important roles in industrial and technological advancements. Rather than merely reacting to contemporary challenges, this article seeks to proactively create opportunities to lead the future of Chemical Engineering across its vital contributions in education, research, technology transfer, and business creation, fully leveraging its inherent multidisciplinarity and versatile character. Y1 - 2024 UR - https://www.sciencedirect.com/science/article/pii/S0263876224004568?via%3Dihub U6 - https://doi.org/10.1016/j.cherd.2024.07.066 VL - 209 SP - 380 EP - 398 ER - TY - GEN A1 - Quinlan, Laura A1 - Brooks, Talia A1 - Ghaemi, Nasrin A1 - Arellano-García, Harvey A1 - Irandoost, Maryam A1 - Sharifianjazi, Fariborz A1 - Amini Horri, Bahman T1 - Synthesis and characterisation of nanocrystalline CoxFe1−xGDC powders as a functional anode material for the solid oxide fuel cell T2 - Materials N2 - The necessity for high operational temperatures presents a considerable obstacle to the commercial viability of solid oxide fuel cells (SOFCs). The introduction of active co-dopant ions to polycrystalline solid structures can directly impact the physiochemical and electrical properties of the resulting composites including crystallite size, lattice parameters, ionic and electronic conductivity, sinterability, and mechanical strength. This study proposes cobalt–iron-substituted gadolinium-doped ceria (CoxFe1-xGDC) as an innovative, nickel-free anode composite for developing ceramic fuel cells. A new co-precipitation technique using ammonium tartrate as the precipitant in a multi-cationic solution with Co2+, Gd3+, Fe3+, and Ce3+ ions was utilized. The physicochemical and morphological characteristics of the synthesized samples were systematically analysed using a comprehensive set of techniques, including DSC/TGA for a thermal analysis, XRD for a crystallographic analysis, SEM/EDX for a morphological and elemental analysis, FT-IR for a chemical bonding analysis, and Raman spectroscopy for a vibrational analysis. The morphological analysis, SEM, showed the formation of nanoparticles (≤15 nm), which corresponded well with the crystal size determined by the XRD analysis, which was within the range of ≤10 nm. The fabrication of single SOFC bilayers occurred within an electrolyte-supported structure, with the use of the GDC as the electrolyte layer and the CoO–Fe2O3/GDC composite as the anode. SEM imaging and the EIS analysis were utilized to examine the fabricated symmetrical cells. KW - Co KW - SOFC anode KW - solid oxide fuel cell KW - electrical conductivity KW - SOFC materials Y1 - 2024 U6 - https://doi.org/10.3390/ma17153864 SN - 1996-1944 VL - 17 IS - 15 PB - MDPI ER - TY - GEN A1 - Sohail, Norman A1 - Riedel, Ramona A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Prolonging the Life Span of Membrane in Submerged MBR by the Application of Different Anti-Biofouling Techniques T2 - Membranes N2 - The membrane bioreactor (MBR) is an efficient technology for the treatment of municipal and industrial wastewater for the last two decades. It is a single stage process with smaller footprints and a higher removal efficiency of organic compounds compared with the conventional activated sludge process. However, the major drawback of the MBR is membrane biofouling which decreases the life span of the membrane and automatically increases the operational cost. This review is exploring different anti-biofouling techniques of the state-of-the-art, i.e., quorum quenching (QQ) and model-based approaches. The former is a relatively recent strategy used to mitigate biofouling. It disrupts the cell-to-cell communication of bacteria responsible for biofouling in the sludge. For example, the two strains of bacteria Rhodococcus sp. BH4 and Pseudomonas putida are very effective in the disruption of quorum sensing (QS). Thus, they are recognized as useful QQ bacteria. Furthermore, the model-based anti-fouling strategies are also very promising in preventing biofouling at very early stages of initialization. Nevertheless, biofouling is an extremely complex phenomenon and the influence of various parameters whether physical or biological on its development is not completely understood. Advancing digital technologies, combined with novel Big Data analytics and optimization techniques offer great opportunities for creating intelligent systems that can effectively address the challenges of MBR biofouling. KW - Membrane bioreactor (MBR) KW - quorum sensing (QS) KW - quorum quenching (QQ) KW - moving bed biofilm reactor (MBBR) KW - moving bed biofilm membrane reactor (MBBMR) KW - model-based anti-fouling strategies Y1 - 2023 UR - https://www.mdpi.com/2077-0375/13/2/217 U6 - https://doi.org/10.3390/membranes13020217 SN - 2077-0375 VL - 13 IS - 2 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Heinzelmann, Norbert A1 - Schnitzlein, Klaus A1 - Arellano-García, Harvey T1 - BasMo - An interactive approach to modelling of trickle bed reactors T2 - Jahrestreffen der "Prozess-, Apparate- und Anlagentechnik", 21.–22. November 2022, Frankfurt am Main N2 - The trickle bed reactor (TBR), in which gas and liquid flow downward through a packed bed to undergo chemical reactions, is a frequently used solution for industrial multiphase exothermic catalytic reactions (e.g., hydrogenation, oxidation, etc.) due to flexibility and simplicity of operation and large annual throughput (Tan et al., 2021). They have significant advantages with respect to other solutions, but they also show complex behaviour, with uncertainties in catalyst heterogeneity, packing, fluid flow, and transport parameters, resulting in its modelling being highly challenging (Azarpour et al., 2021). In this contribution, the development of an interactive toolbox for the simulation of TBRs, based on the work of Schwidder & Schnitzlein (2012) is introduced. The implementation uses a modular and flexible setup, mirroring the multiscale nature of the phenomena tacking place in the reactor, from large scale of the reactor to the medium and low scale of the particle bed, fluid flow, as well as fluid-solid and fluid-fluid interactions, including chemical reactions. The toolbox enables implementation of complex geometries of the catalyst particles, enabled by a novel representation of the surface mesh. Validation using experimental data shows that the model is able to reliably predict the performance of the catalytic TBR. Y1 - 2022 UR - https://dechema.de/PAAT2022_Themen/_/_1_Programm_PAAT_2022_ezl.pdf ER - TY - GEN A1 - Straub, Adrian A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Towards a novel concept for solid energy storage T2 - Computer Aided Chemical Engineering N2 - In this contribution, the model-based development of a novel process concept for the storage and release of ammonia in solids is proposed. The concept is validated by means of the Aspen Plus® process simulator. As a promising prospect, Hexaaminenickel(II) chloride is selected. After a preparative stage, the process can cycle between the storage and release of energy. The process is split in a reaction and a separation section, in such a way that the same equipment is used for both storage and release steps. Sensitivity analysis and design parameter optimization are used to determine key process parameters. The operation ranges from standard conditions (25 °C and 1 atm) to temperatures not higher than 120 °C. Moreover, the simulation results show that it is possible to store over 50% of the base material in form of ammonia, equivalent to almost 10 wt.% hydrogen, placing the concept within the specific system targets set by the U.S. Department of Energy. KW - Process design KW - Process modelling KW - Aspen Plus Y1 - 2023 U6 - https://doi.org/10.1016/B978-0-443-15274-0.50472-8 SN - 1570-7946 VL - Vol. 52 SP - 2965 EP - 2970 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Miah, Sayeef A1 - Mechleri, Evgenia A1 - Arellano-García, Harvey T1 - Multiobjective optimization of distributed energy systems design through 3E (economic, environmental and exergy) analysis T2 - Computer Aided Chemical Engineering N2 - Distributed energy systems (DES) are promising alternative to conventional centralized generation, with multiple financial incentives in many parts of the world. Current approaches focus on the design optimization of a DES through economic and environmental cost minimization. However, these two criteria alone do not satisfy long-term sustainability priorities of the system. The novelty of this paper is the simultaneous investigation of economic, environmental and exergetic criteria in the modelling of DES through the two most commonly used solution methodologies for solving multi-objective optimization problems – the weighted sum and the epsilon-constraint methods. Out of the set of Pareto optimal solutions, a best-compromised solution is chosen using the fuzzy-based method. Numerical results reveal reduction of around 93% and 89-91% in environmental and primary exergy input, respectively. KW - Multiobjective optimization KW - Distributed energy systems KW - Exergy KW - Mixed-integer linear programming KW - Fuzzy-based methods Y1 - 2023 U6 - https://doi.org/10.1016/B978-0-443-15274-0.50473-X SN - 1570-7946 VL - Vol. 52 SP - 2971 EP - 2976 ER - TY - GEN A1 - Alves Amorim, Ana Paula A1 - Dorneanu, Bogdan A1 - Valverde Pontes, Karen A1 - Arellano-García, Harvey T1 - A framework for decision-making to encourage utilization of residential distributed energy systems in Brazil T2 - Computer Aided Chemical Engineering N2 - The Distributed Energy Systems (DES) or microgrid arose from the need to reduce greenhouse gases (GHG) emitted into the atmosphere by burning fossil fuels to generate energy. Reduction of energy losses, reconfiguration of the protection system and reduction of costs, and optimizing the configuration of these systems is recommended. Despite new research in literature, there is still a lack of optimization models that address the Brazilian reality. Therefore, the objective of this work is to introduce a decision-making framework for the design and operation of residential DES that takes into account the particularities of Brazil, based on mixed-integer programming models. The applicability of the framework is tested on a case study of a residential DES of 5 houses, located in Salvador, and used to compare scenarios pre- and post-COVID-19. The results show significant reduction in total annual cost and GHG emissions versus the base case without DES. This indicates that, although the country has a mostly “clean” energy matrix due to the use of hydroelectric plants, DES can enable improvement in residential electricity generation. KW - Distributeed energy systems KW - Microgrid KW - Mixed-integer non-linear programming KW - Net metering Y1 - 2023 U6 - https://doi.org/10.1016/B978-0-443-15274-0.50481-9 SN - 1570-7946 VL - Vol. 52 SP - 3019 EP - 3024 ER - TY - GEN A1 - Tarifa, Pilar A1 - Gonzalez-Castano, Miriam A1 - Cazana, Fernando A1 - Monzon, Antonio A1 - Arellano-García, Harvey T1 - Hydrophobic RWGS catalysts: valorization of CO2-rich streams in presence of CO/H2O T2 - Catalysis Today N2 - Nowadays, the majority of the Reverse Water Gas Shift (RWGS) studies assume somehow model feedstock (diluted CO2/H2) for syngas production. Nonetheless, biogas streams contain certain amounts of CO/H2O which will decrease the obtained CO2 conversion values by promoting the forward WGS reaction. Since the rate limiting step for the WGS reaction concerns the water splitting, this work proposes the use of hydrophobic RWGS catalysts as an effective strategy for the valorization of CO2-rich feedstock in presence of H2O and CO. Over Fe-Mg catalysts, the different hydrophilicities attained over pristine, N- and B-doped carbonaceous supports accounted for the impact on the activity of the catalyst in presence of CO/H2O. Overall, the higher CO productivity (4.12 μmol/(min·m2)) attained by Fe-Mg/CDC in presence of 20% of H2O relates to hindered water adsorption and unveil the use of hydrophobic surfaces as a suitable approach for avoiding costly pre-conditioning units for the valorization of CO2-rich streams based on RWGS processes in presence of CO/H2O. Y1 - 2023 U6 - https://doi.org/10.1016/j.cattod.2023.114276 SN - 1873-4308 VL - Vol. 423 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Masham, Elliot A1 - Keykha, Mina A1 - Mechleri, Evgenia A1 - Cole, Rosanna A1 - Arellano-García, Harvey T1 - Assessment of centralised and localised ice cream supply chains using neighbourhood flow configuration models T2 - Supply Chain Analytics N2 - Traditional food supply chains are often centralised and global in nature, entailing substantial resource consumption. However, in the face of growing demand for sustainability, this strategy faces significant challenges. Adoption of localised supply chains is deemed a more sustainable option, yet its efficacy requires verification. Supply chain analytics methodologies provide invaluable tools to guide decisions regarding inventory management, demand forecasting and distribution optimisation. These solutions not only enhance facilitate operational efficiency, but also pave the way for cost reduction, further aligning with sustainability objectives. This research introduces a novel decision-making approach anchored in mixed integer linear programming (MILP) and neighbourhood flow models defined in cellular automata to compare the environmental benefits and vulnerability to disruption of these two chain configurations. Additionally, a comprehensive cost analysis is integrated to assess the economic feasibility of incorporating layout changes that enhance supply chain sustainability. The proposed framework is applied on an ice cream supply chain across England over a one-year timeframe. The findings indicate the superiority of the localised configuration in terms of economic benefits, leading to savings exceeding £ 1 million, alongside important reductions in environmental impact. However, in terms of resilience, the traditional configuration remains superior in three out of the four examined scenarios. KW - supply chain management KW - flow configuration model KW - ice cream KW - Mixed-integer linear programming Y1 - 2023 UR - https://www.sciencedirect.com/science/article/pii/S2949863523000420 U6 - https://doi.org/10.1016/j.sca.2023.100043 VL - Vol. 4 ER - TY - GEN A1 - Cunha Cordeiro, José Luiz A1 - Safdar, Muddasar A1 - Aquino, Gabrielle S. A1 - Silva, Jefferson S. A1 - Paff, Jessica Sophie A1 - Valverde Pontes, Karen A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey A1 - Mascarenhas, Artur José T1 - Sustainable hydrogen production via biogas reforming over NiO-MxOy - Al2O3 catalysts (M = Na, K, Ca and Mg) T2 - 22 Congreso Brasileiro de Catalise N2 - A sustainable way to generate hydrogen is through dry biogas reforming, which uses methane gas and carbon dioxide to produce hydrogen. This study reveals partial results of the dry reforming of biogas in NiO-MxOy-Al2O3 catalysts (M=Na, K, Ca and Mg). The CO2 conversion varied between 79% and 94%, the CH4 conversion between 58% and 75%, the H2/CO ratio between 0.98 and 1.15 and the H2 yield between 37% and 45%. These values ​​surpass literary references and the industrial catalyst, highlighting the promise of these materials for sustainable hydrogen production. The catalyst with Ca stood out due to its higher surface basicity, exhibiting the best conversion results and yield in H2. Y1 - 2023 UR - https://submissao.cbcat.sbcat.org.br/index.php/2023-cbcat/article/view/409 ER - TY - GEN A1 - Safdar, Muddasar A1 - Shezad, Nasir A1 - Dorneanu, Bogdan A1 - Jafari, Mitra A1 - Shashank Bhat, Sharvendu A1 - Akhtar, Farid A1 - Arellano-García, Harvey T1 - Dry Reforming of Methane for the Syngas Production Catalyzed by Ni-doped Perovskites T2 - 15Th European Congress on Katakysis EUROPACAT2023 N2 - different perovskite-type supports considering ABO3 (such as A= Al, La with B=Ce and A=Mg, Mn with B=Zr) were prepared via the sol-gel method. Ni metal loading of 10 wt.% was deposited on prepared perovskite supports via the impregnation method. The catalysts were characterized using XRD and FTIR techniques. The DRM activity was carried out in a tubular reactor as described in our previous study [5]. The catalytic performance was assessed in the temperature range of 500–700 ◦C, CH4/CO2 = 1/1 and under GHSV of 12,000 h–1. Among the prepared catalysts, Ni-doped perovskite combination (i.e. A=Mg with B=Zr)O3-δ exhibited higher (CH4, CO2) conversion ca. (69, 59) percent and syngas yield of ca. (H2/CO =0.72) at 700 oC. This indicates that the magnesium zirconate perovskite catalyst established strong interfacial metal-support interaction, redox properties and surface basic sites that linked with good performance of the catalyst during DRM process. KW - Dry reforming of methane (DRM) KW - Ni-Perovskites KW - Syngas production KW - Greenhouse gases (GHGs) Y1 - 2023 ER - TY - GEN A1 - Mappas, Vassileios A1 - Vassiliadis, Vassilios S. A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Use of Multistage Optimal Control Principles for Novel Design and Implementation of Classical Controllers T2 - AIChE Annual Meeting N2 - Classical controllers, such as Proportional-Integral (PI) and Proportional-Integral Derivative (PID) controllers, are the most long-established and widely used in industry. Various methods for tuning these types of controllers exist (Ziegler et al., 1942; Blondin et al., 2018; Do et al., 2021), and up to this point, there is no fruitful avenue to improve their performance. In this contribution, a new approach for PI and PID controller implementation, based on a Multistage Optimal Control (MSOCP) approach is introduced. Our approach incorporates path and end-point constraints during its controller tuning phase, as well as parameter and disturbance uncertainty. The proposed framework is applied for different case studies and is able to reject any disturbances introduced to the examined systems, with or without uncertainty, satisfies end-point constraints and exhibits quicker response for switching steady states, compared to classical methods. Other aspects of controller design and incorporation within industrial process models, as related to using rigorous optimization methodologies and implementations, will further be highlighted within the context of the PI and PID controllers. Y1 - 2021 UR - https://aiche.confex.com/aiche/2021/meetingapp.cgi/Paper/630692 ER - TY - GEN A1 - Mappas, Vassileios A1 - Vassiliadis, Vassilios S. A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Automated Control Loop Selection Via Multistage Optimal Control Formulation and Nonlinear Programming T2 - Chemical Engineering Research and Design N2 - In this work, a novel approach based on the multistage optimal control formulation of the control loop selection problem is introduced. Currently, state-of-the-art approaches for controller loop design have been focused on data that yield only the pairings between input-output variables, and are not able to incorporate path and end-point constraints. Thus, they only produce the optimal loops for control purposes, without the simultaneous consideration of their optimal tuning. This formulation overcomes these drawbacks by producing an automated integrated solution for the task of control loop design, which also obviates the need for any form of combinatorial optimisastion to be used. To illustrate the procedure, as well as the advantages of the proposed scheme, different practical case studies are discussed and the results compared with those obtained with standard controller loop selection methods and their tuning. The results of the proposed approach show improved performance over previous methodologies found in the literature. Furthermore, the framework is extended to the selection of the control loops that must obey path and end-point constraints imposed by the underlying dynamical process. This task is usually difficult for classical methods, which violate them or exhibit underdamped response in some cases. KW - control loop selection KW - controller tuning KW - feasible path approach KW - multistage integer nonlinear optimal control problem (MSINOCP) KW - dynamic constraints Y1 - 2023 U6 - https://doi.org/10.1016/j.cherd.2023.05.041 SN - 1744-3563 VL - 195 SP - 76 EP - 95 ER - TY - GEN A1 - Jafari, Mitra A1 - Safdar, Muddasar A1 - Dorneanu, Bogdan A1 - Gonzalez-Castaño, Miriam A1 - Arellano-García, Harvey T1 - Green and sustainable fuel from syngas via the Fischer-Tropsch synthesis process: Bifunctional cobalt-based catalysts T2 - 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology N2 - This paper reviews and compares state-of-the-art cobalt-based catalysts and catalytic systems used to produce green and sustainable fuels using FTS. Being focused on comparing the effect of the catalyst formulation and synthesis method, the reactor type and operating parameters, as well as the quality of the obtained fuels, the aim is to identify the research gaps between these relevant research areas concerning production of green and sustainable fuels. Y1 - 2023 UR - https://dechema.converia.de/frontend/index.php?page_id=15565&additions_conferenceschedule_action=detail&additions_conferenceschedule_controller=paperList&pid=44228&hash=be231d3139d7d89da32b1610b7a0d1af3770c06640f246348e3ca8cfa7dd324a ER - TY - GEN A1 - Plattfaut, Julia A1 - Suckow, Matthias A1 - Klepel, Olaf A1 - Erlitz, Marcel A1 - Arellano-García, Harvey T1 - Modellierung und Simulation der templatgestützten Synthese von porösen Kohlenstoffgerüsten mittels COMSOL Multiphysics T2 - Chemie Ingenieur Technik N2 - Mithilfe einer templatgestützten Synthese wurden poröse Kohlenstoffgerüste unter Verwendung von Silicagel als Templat hergestellt. Die chemische Gasphaseninfiltration (CVI) wurde hierbei als Synthese verwendet. Unter Variation verschiedener Reaktionsparameter zur Optimierung der Kohlenstoffabscheidung wurde dieser Prozess mathematisch modelliert and simuliert. Dabei konnten die experimentellen Ergebnisse gut mit den Modellen nachgebildet werden. Die zusätzliche Beschreibung der laminaren Strömung verbessert die Übereinstimmung deutlich. Y1 - 2023 U6 - https://doi.org/10.1002/cite.202300014 SN - 1522-2640 VL - 96(2024) IS - 3 SP - 318 EP - 328 ER - TY - GEN A1 - Zhang, Sushen A1 - Vassiliadis, Vassilios S. A1 - Dorneanu, Bogdan A1 - Arellano-García, Harvey T1 - Hierarchical multi-scale parametric optimization of deep neural networks T2 - Applied Intelligence N2 - Traditionally, sensitivity analysis has been utilized to determine the importance of input variables to a deep neural network (DNN). However, the quantification of sensitivity for each neuron in a network presents a significant challenge. In this article, a selective method for calculating neuron sensitivity in layers of neurons concerning network output is proposed. This approach incorporates scaling factors that facilitate the evaluation and comparison of neuron importance. Additionally, a hierarchical multi-scale optimization framework is proposed, where layers with high-importance neurons are selectively optimized. Unlike the traditional backpropagation method that optimizes the whole network at once, this alternative approach focuses on optimizing the more important layers. This paper provides fundamental theoretical analysis and motivating case study results for the proposed neural network treatment. The framework is shown to be effective in network optimization when applied to simulated and UCI Machine Learning Repository datasets. This alternative training generates local minima close to or even better than those obtained with the backpropagation method, utilizing the same starting points for comparative purposes within a multi-start optimization procedure. Moreover, the proposed approach is observed to be more efficient for large-scale DNNs. These results validate the proposed algorithmic framework as a rigorous and robust new optimization methodology for training (fitting) neural networks to input/output data series of any given system. KW - Deep neural networks KW - Hierarchical multi-scale search KW - Scaling factor KW - Sensitivity analysis KW - Finite difference KW - Automatic differentiation Y1 - 2023 U6 - https://doi.org/10.1007/s10489-023-04745-8 SN - 1573-7497 VL - 53 IS - 21 SP - 24963 EP - 24990 ER - TY - GEN A1 - Arellano-García, Harvey A1 - Safdar, Muddasar A1 - Shezad, Nasir A1 - Dorneanu, Bogdan A1 - Akhtar, Farid T1 - Synthesis and Characterizations of Ni-doped Perovskite-Type Oxides for Effective CO2 methanation T2 - 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology N2 - This work proposes Ni metal supported over rare earth-based emerging perovskite-type oxides as potential catalysts for the CO2 methanation. Presence of oxygen vacancies in perovskite-like materials enable them to exhibit higher catalytic activity. Furthermore, to tune the surface basicity, metal-support interaction and to enhance the activation of CO2, rare earth metals (La, Ce, etc.) are considered best candidates. Moreover, different perovskite-type supports (AxMnxO3, A= La, Ce) based on A-side substitution of rare earth metals were prepared with Ni metal loading of 10 wt.% via impregnation method. Y1 - 2023 UR - https://dechema.converia.de/frontend/index.php?page_id=13659&v=List&do=15&day=all&ses=9628# U6 - https://doi.org/10.5281/zenodo.10376612 ER - TY - GEN A1 - Dorneanu, Bogdan A1 - Nolasco, Eduardo A1 - Vassiliadis, Vassilios S. A1 - Arellano-García, Harvey T1 - Quantum annealing for global optimization in Chemical Engineering T2 - Jahrestreffen "Prozess-, Apparate- und Anlagentechnik" - PAAT 2023, Frankfurt am Main N2 - Classical computing has experienced rapid growth in computational power, driven by the need to address increasingly complex industrial problems. The domain of global optimization plays a vital role in various applications, including optimal control, scheduling and assignment problems, or machine learning parameter selection. Currently, deterministic optimization techniques based on classical computing fail to deliver reasonable solutions within practical time constraints. Consequently, reliance on heuristic methods becomes common, albeit with no guarantee of solution quality. While ongoing algorithmic refinements lead to gradual enhancements in global optimization, they do little to address the fundamental issue of computational intractability. With the advent of quantum computing, a natural question arises: Can quantum methods offer advancements beyond classical approaches? Quantum annealing emerges as a promising subfield within quantum computing, necessitating the reformulation of problems as quadratic unconstrained binary optimization (QUBO) problems. In this contribution, a novel approach is introduced to transform relevant problems in Chemical Engineering into QUBO at two distinct levels of granularity. Subsequently, these problem systems are embedded within virtual quantum machines employing two different architectures. Additionally, a comparative analysis is performed, wherein the same problem is solved utilizing both classical global optimization methods based on metaheuristics and a hypothetical quantum annealer. The findings indicate that annealing-based solving methods exhibit the most potential, indicating their applicability to the transformed formulation Chemical Engineering problems. Y1 - 2023 UR - https://dechema.de/PAAT2023_Prg/_/__Progr_PAAT_2023_final.pdf SP - 15 ER -