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 -