@misc{MohamedRuanHeshmatHassanAbdelwahabetal., author = {Mohamed, Abdelrahim and Ruan, Hang and Heshmat Hassan Abdelwahab, Mohamed and Dorneanu, Bogdan and Xiao, Pei and Arellano-Garc{\´i}a, Harvey and Gao, Yang and Tafazolli, Rahim}, title = {An Inter-Disciplinary Modelling Approach in Industrial 5G/6G and Machine Learning Era}, series = {2020 IEEE International Conference on Communications Workshops (ICC Workshops)}, journal = {2020 IEEE International Conference on Communications Workshops (ICC Workshops)}, address = {Dublin, Ireland}, isbn = {978-1-7281-7440-2}, issn = {2474-9133}, doi = {10.1109/ICCWorkshops49005.2020.9145434}, pages = {1 -- 6}, abstract = {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.}, language = {en} } @misc{StephensonCarvalhoElleroSebastiaSaezetal., author = {Stephenson, Ted and Carvalho Ellero, Caio and Sebastia-Saez, Daniel and Klymenko, Oleksiy and Battley, Angela Maria and Arellano-Garc{\´i}a, Harvey}, title = {Numerical modelling of the interaction between eccrine sweat and textile fabric for the development of smart clothing}, series = {International Journal of Clothing Science and Technology}, volume = {32}, journal = {International Journal of Clothing Science and Technology}, number = {5}, issn = {0955-6222}, doi = {10.1108/IJCST-07-2019-0100}, pages = {761 -- 774}, abstract = {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.}, language = {en} } @misc{BaenaMorenoCidCastilloArellanoGarciaetal., author = {Baena-Moreno, Francisco Manuel and Cid-Castillo, N. and Arellano-Garc{\´i}a, Harvey and Ramirez Reina, Tomas}, title = {Towards emission free steel manufacturing - Exploring the advantages of a CO2 methanation unit to minimize CO2 emissions}, series = {Science of The Total Environment}, volume = {781}, journal = {Science of The Total Environment}, issn = {1879-1026}, doi = {10.1016/j.scitotenv.2021.146776}, abstract = {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.}, language = {en} } @misc{MechleriDorneanuArellanoGarcia, author = {Mechleri, Evgenia and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {A Model Predictive Control-Based Decision-Making Strategy for Residential Microgrids}, series = {Eng}, volume = {3}, journal = {Eng}, number = {1}, issn = {2673-4117}, doi = {10.3390/eng3010009}, pages = {100 -- 115}, abstract = {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.}, language = {en} } @misc{JurischkaDorneanuStollbergetal., author = {Jurischka, Constantin and Dorneanu, Bogdan and Stollberg, Christian and Arellano-Garc{\´i}a, Harvey}, title = {A novel approach to continuous extraction of active ingredients from essential oils through combined chromatography}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50129-6}, pages = {769 -- 774}, abstract = {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.}, language = {en} } @misc{EstradaManriqueSilupuIpanaqueetal., author = {Estrada, Carlos A. and Manrique-Silup{\´u}, Jos{\´e} and Ipanaqu{\´e}, William and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {A model-based approach for the prediction of banana rust thrips incidence from atmospheric variables}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50085-0}, pages = {505 -- 510}, abstract = {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.}, language = {en} } @misc{AmaoDorneanuArellanoGarcia, author = {Amao, Khalid and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Economic Analysis of Novel Pathways for Recovery of Lithium Battery Waste}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50271-X}, pages = {1621 -- 1626}, abstract = {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.}, language = {en} } @misc{DorneanuHeinzelmannSchnitzleinetal., author = {Dorneanu, Bogdan and Heinzelmann, Norbert and Schnitzlein, Klaus and Arellano-Garc{\´i}a, Harvey}, title = {A novel approach to modelling trickle bed reactors}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50047-3}, pages = {277 -- 282}, abstract = {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.}, language = {en} } @misc{CamposManriqueSilupuIpanaqueetal., author = {Campos, Jean C. and Manrique-Silup{\´u}, Jos{\´e} and Ipanaqu{\´e}, William and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Mechanistic modelling for thrips incidence in organic banana}, series = {Computer Aided Chemical Engineering}, volume = {51}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-95879-0.50046-1}, pages = {271 -- 276}, abstract = {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.}, language = {en} } @misc{KetabchiRamirezReinaDorneanuetal., author = {Ketabchi, Elham and Ramirez Reina, Tomas and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {An identification approach to a reaction network for an ABE catalytic upgrade}, series = {Computer Aided Chemical Engineering}, volume = {50}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-323-88506-5.50102-9}, pages = {643 -- 648}, abstract = {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.}, language = {en} } @misc{ClarkeDorneanuMechlerietal., author = {Clarke, Fiona and Dorneanu, Bogdan and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Optimal design of heating and cooling pipeline networks for residential distributed energy resource systems}, series = {Energy}, volume = {235}, journal = {Energy}, issn = {1873-6785}, doi = {10.1016/j.energy.2021.121430}, abstract = {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.}, language = {en} } @misc{SidnellDorneanuMechlerietal., author = {Sidnell, Tim and Dorneanu, Bogdan and Mechleri, Evgenia and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Effects of Dynamic Pricing on the Design and Operation of Distributed Energy Resource Networks}, series = {Processes}, volume = {9}, journal = {Processes}, number = {8}, issn = {2227-9717}, doi = {https://doi.org/10.3390/pr9081306}, abstract = {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.}, language = {en} } @misc{SidnellClarkeDorneanuetal., author = {Sidnell, Tim and Clarke, Fiona and Dorneanu, Bogdan and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Optimal design and operation of distributed energy resources systems for residential neighbourhoods}, series = {Smart Energy}, volume = {4}, journal = {Smart Energy}, issn = {2666-9552}, doi = {10.1016/j.segy.2021.100049}, abstract = {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.}, language = {en} } @misc{AnagnostopoulosSebastiaSaezCampbelletal., author = {Anagnostopoulos, Argyrios and Sebastia-Saez, Daniel and Campbell, Alasdair N. and Arellano-Garc{\´i}a, Harvey}, title = {Finite element modelling of the thermal performance of salinity gradient solar ponds}, series = {Energy}, volume = {203}, journal = {Energy}, issn = {1873-6785}, doi = {10.1016/j.energy.2020.117861}, abstract = {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.}, language = {en} } @misc{DeMelDemisDorneanuetal., author = {De Mel, Ishanki and Demis, Panagiotis and Dorneanu, Bogdan and Klymenko, Oleksiy and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Global Sensitivity Analysis for Design and Operation of Distributed Energy Systems}, series = {Computer Aided Chemical Engineering}, volume = {48}, journal = {Computer Aided Chemical Engineering}, issn = {1570-7946}, doi = {10.1016/B978-0-12-823377-1.50254-8}, pages = {1519 -- 1524}, abstract = {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.}, language = {en} } @misc{YusufFlagielloWardetal., author = {Yusuf, Ifrah and Flagiello, Fabio and Ward, Niel I. and Arellano-Garc{\´i}a, Harvey and Avignone-Rossa, Claudio and Felipe-Sotelo, Monica}, title = {Valorisation of banana peels by hydrothermal carbonisation: Potential use of the hydrochar and liquid by-product for water purification and energy conversion}, series = {Bioresource Technology Reports}, volume = {12}, journal = {Bioresource Technology Reports}, issn = {2589-014X}, doi = {10.1016/j.biteb.2020.100582}, abstract = {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.}, language = {en} } @misc{DeCarvalhoMirandaFloresPonceArellanoGarciaetal., author = {De Carvalho Miranda, Julio Cesar and Flores Ponce, Gustavo Henrique Santos and Arellano-Garc{\´i}a, Harvey and Maciel Filho, Rubens and Wolf Maciel, Maria Regina}, title = {Process design and evaluation of syngas-to-ethanol conversion plants}, series = {Journal of Cleaner Production}, volume = {269}, journal = {Journal of Cleaner Production}, issn = {0959-6526}, doi = {10.1016/j.jclepro.2020.122078}, abstract = {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.}, language = {en} } @misc{GonzalezCastanoGonzalezAriasBobadillaetal., author = {Gonzalez-Casta{\~n}o, Miriam and Gonzalez-Arias, Judith and Bobadilla, Luis F. and Ruiz-Lopez, E. and Odriozola, Jose Antonio and Arellano-Garc{\´i}a, Harvey}, title = {In-Situ Drifts Steady-State Study of Co2 and Co Methanation Over Ni-Promoted Catalysts}, series = {Fuel}, volume = {338}, journal = {Fuel}, issn = {1873-7153}, doi = {10.1016/j.fuel.2022.127241}, abstract = {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.}, language = {en} } @misc{TarifaRamirezReinaGonzalezCastanoetal., author = {Tarifa, Pilar and Ramirez Reina, Tomas and Gonz{\´a}lez-Casta{\~n}o, Miriam and Arellano-Garc{\´i}a, Harvey}, title = {Catalytic Upgrading of Biomass-Gasification Mixtures Using Ni-Fe/MgAl₂O₄ as a Bifunctional Catalyst}, series = {Energy and Fuels}, volume = {36}, journal = {Energy and Fuels}, number = {15}, issn = {1520-5029}, doi = {10.1021/acs.energyfuels.2c01452}, pages = {8267 -- 8273}, abstract = {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.}, language = {en} } @misc{RuanDorneanuArellanoGarciaetal., author = {Ruan, Hang and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey and Xiao, Pei and Zhang, Li}, title = {Deep Learning-Based Fault Prediction in Wireless Sensor Network Embedded Cyber-Physical Systems for Industrial Processes}, series = {IEEE Access}, volume = {10}, journal = {IEEE Access}, issn = {2169-3536}, doi = {10.1109/ACCESS.2022.3144333}, pages = {10867 -- 10879}, abstract = {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.}, language = {en} } @misc{SaavedraAlejandroParedesFloresSantosetal., author = {Saavedra, Stephy and Alejandro-Paredes, Luis and Flores-Santos, Juan Carlos and Flores-Fern{\´a}ndez, Carol Nathali and Arellano-Garc{\´i}a, Harvey and Zavaleta, Amparo Iris}, title = {Optimization of lactic acid production by Lactobacillus plantarum strain Hui1 in a medium containing sugar cane molasses}, series = {Agronom{\´i}a Colombiana}, volume = {39}, journal = {Agronom{\´i}a Colombiana}, number = {1}, issn = {0120-9965}, doi = {10.15446/agron.colomb.v39n1.89674}, pages = {98 -- 107}, abstract = {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.}, language = {en} } @incollection{DorneanuArellanoGarciaRuanetal., author = {Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey and Ruan, Hang and Mohamed, Abdelrahim and Xiao, Pei and Heshmat, Mohamed and Gao, Yang}, title = {Towards fault detection and self-healing of chemical processes over wireless sensor networks}, series = {Industry 4.0 - Shaping The Future of The Digital World}, booktitle = {Industry 4.0 - Shaping The Future of The Digital World}, edition = {1st edition}, publisher = {CRC Press}, address = {London, United Kingdom}, isbn = {9780367823085}, doi = {10.1201/9780367823085-02}, pages = {9 -- 14}, abstract = {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.}, language = {en} } @incollection{DorneanuArellanoGarciaHeshmatetal., author = {Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey and Heshmat, Mohamed and Gao, Yang}, title = {A framework for intelligent monitoring and control of chemical processes with multi-agent systems}, series = {Industry 4.0 - Shaping The Future of The Digital World}, booktitle = {Industry 4.0 - Shaping The Future of The Digital World}, edition = {1st edition}, publisher = {CRC Press}, address = {London, United Kingdom}, isbn = {9780367823085}, doi = {10.1201/9780367823085-04}, pages = {18 -- 23}, abstract = {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.}, language = {en} } @misc{KetabchiMechleriArellanoGarcia, author = {Ketabchi, Elham and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Increasing operational efficiency through the integration of an oil refinery and an ethylene production plant}, series = {Chemical Engineering Research and Design}, volume = {152}, journal = {Chemical Engineering Research and Design}, issn = {1744-3563}, doi = {10.1016/j.cherd.2019.09.028}, pages = {85 -- 94}, abstract = {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.}, language = {en} } @misc{KetabchiPastorPerezArellanoGarciaetal., author = {Ketabchi, Elham and Pastor-Perez, Laura and Arellano-Garc{\´i}a, Harvey and Ramirez Reina, Tomas}, title = {Influence of Reaction Parameters on the Catalytic Upgrading of an Acetone, Butanol and Ethanol (ABE) Mixture: Exploring New Routes for Modern Biorefineries}, series = {Frontiers in Chemistry}, volume = {7}, journal = {Frontiers in Chemistry}, issn = {2296-2646}, doi = {10.3389/fchem.2019.00906}, abstract = {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.}, language = {en} }