@misc{MedinaMendezGonzalezCastanoBaenaMorenoetal., author = {Medina M{\´e}ndez, Juan Ali and Gonz{\´a}lez-Casta{\~n}o, Miriam and Baena-Moreno, Francisco Manuel and Arellano-Garc{\´i}a, Harvey}, title = {CO2 methanation: on the modeling of reacting laminar flows in structured Ni/MgAl2O4 catalysts}, series = {XXV Fluid Mechanics Conference, Rzesz{\´o}w, Poland, 7-9 September 2022, Book of Abstracts}, journal = {XXV Fluid Mechanics Conference, Rzesz{\´o}w, Poland, 7-9 September 2022, Book of Abstracts}, editor = {Kmiotek, M. and Kordos, A.}, publisher = {Publishing House of Rzesz{\´o}w University of Technology}, address = {Rzesz{\´o}w, Poland}, isbn = {978-83-7934-590-8}, pages = {98 -- 100}, language = {en} } @misc{MedinaMendezGonzalezCastanoBaenaMorenoetal., author = {Medina M{\´e}ndez, Juan Ali and Gonz{\´a}lez-Casta{\~n}o, Miriam and Baena-Moreno, Francisco Manuel and Arellano-Garc{\´i}a, Harvey}, title = {CO2 methanation: on the modeling of reacting laminar flows in structured Ni/MgAl2O4 catalysts}, series = {Journal of Physics: Conference Series}, journal = {Journal of Physics: Conference Series}, number = {2367}, publisher = {IOP Publishing}, doi = {10.1088/1742-6596/2367/1/012015}, pages = {8}, language = {en} } @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{RamirezReinaKetabchiArellanoGarciaetal., author = {Ramirez Reina, Tomas and Ketabchi, Elham and Arellano-Garc{\´i}a, Harvey and Pastor-Perez, Laura}, title = {The Production of Long Chain Hydrocarbons through the Catalytic Upgrade of Biomass-Based Acetone, Butanol and Ethanol (ABE)}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {One of the main issues that many industrial sectors such as oil refineries have been facing nowadays is their sole dependency on fossil fuel. Not only have price fluctuations affected the products, but their environmental impact is an ever present problem that should be addressed. This has led to the search for alternatives such as biomass based processes in order to reduce the dependency on fossil fuel. Bio-refinery processes, fed by biomass, produce high value chemicals and materials with the advantage of reduced environmental drawbacks, such as CO2 emissions, when compared to the conventional refinery. For the benefit of both systems, an integration approach has been considered connecting bio-refining and conventional refining processes together. In this work we focus on the production of long chain hydrocarbons while maintaining production of chemicals that already originate from biomass such as Acetone, Butanol and Ethanol (ABE). The ABE used for this process is obtained as a product of sugar fermentation using the bacteria genus Clostridium. Through the upgrading and conversion of ABE, the products obtained will then be incorporated in the proposed integration system, connecting the conventional oil refinery to this process. A reaction involving a complex reaction network towards upgrading ABE with the aim of producing valuable products using economically viable catalysts has been carried out. The vast majority of research in this area either involves the separation of ABE after fermentation to be used in the chemical/or transportation industry that incurs large costs, or noble metal catalysts are used to upgrade this feed, which would also not be economically viable. However, our research has surpassed the necessity of noble metals, leading to a significant cost decrease that also produces outstanding results. The catalysts required for this process were synthesised successfully through the wetness incipient method and characterised by XRD, Raman, BET, TPR and N2 Isotherm. The reaction consists of the self-condensation and cross condensation of the alcohols and acetone, respectively, using a variety of active metals on basic supports as catalysts, at high temperatures and pressure in a batch reactor. The results have shown exceptional performance for the catalysts in terms of conversion and selectivity, having conversions as high as 90\%. The catalysts have proven to yield a range of C3-C15 hydrocarbons identified to be of need in the chemical industry. In conclusion, our route has produced valuable chemicals proven to have a considerably higher market value than the simple alcohol reactants, useful for both the petrochemical and the transportation industries, through the use of novel and economically favourable catalysts.}, language = {en} } @misc{HamdanArellanoGarciaSebastiaSaez, author = {Hamdan, Mustapha and Arellano-Garc{\´i}a, Harvey and Sebastia-Saez, Daniel}, title = {A Novel Circulating Fluidised Bed Solar Receiver Design for Thermal Energy Conversion and Storage}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {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.}, language = {en} } @misc{KetabchiMechleriArellanoGarcia, author = {Ketabchi, Elham and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Towards Sustainable Industries: Industrial Symbiosis of an Oil Refinery and a Petrochemical Plant}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {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{\^a}€™ 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 {\^a}€œgreener{\^a}€ 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.}, language = {en} } @misc{DorneanuArellanoGarciaHeshmatetal., author = {Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey and Heshmat, Mohamed and Gao, Yang}, title = {Ontology Based Decision Making for Process Control}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {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{\^a}€™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{\^a}€™ 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.}, language = {en} } @misc{YusufDorneanuAvignoneRossaetal., author = {Yusuf, Ifrah and Dorneanu, Bogdan and Avignone-Rossa, Claudio and Arellano-Garc{\´i}a, Harvey}, title = {Synthesis and Characterization of Hydrochars Produced By Hydrothermal Carbonization of Banana Peels}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {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{\^a}€™ 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.}, language = {en} } @misc{DeMelMechleriDemisetal., author = {De Mel, Ishanki and Mechleri, Evgenia and Demis, Panagiotis and Dorneanu, Bogdan and Klymenko, Oleksiy and Arellano-Garc{\´i}a, Harvey}, title = {A Methodology for Global Sensitivity Analysis for the Operation of Distributed Energy Systems Using a Two-Stage Approach}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {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.}, language = {en} } @misc{MechleriShafieiDorneanuetal., author = {Mechleri, Evgenia and Shafiei, Zarif and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey and Klymenko, Oleksiy}, title = {A Blockchain Model for Residential Distributed Energy Resources Networks}, series = {2019 AIChE Annual Meeting}, journal = {2019 AIChE Annual Meeting}, isbn = {978-0-8169-1112-7}, abstract = {The energy production landscape is reshaped by distributed energy resources (DERs) {\^a}€" 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.}, language = {en} } @misc{HajizeinalibiokiSebastiaSaezKlymenkoetal., author = {Hajizeinalibioki, Sahar and Sebastia-Saez, Daniel and Klymenko, Oleksiy and Arellano-Garc{\´i}a, Harvey}, title = {Investigation of Two-Phase Flow Characteristics in a Fractal-Branching Microchannel}, series = {AIChE Annual Meeting, November 10, 2019 to November 15, 2019}, journal = {AIChE Annual Meeting, November 10, 2019 to November 15, 2019}, isbn = {978-0-8169-1112-7}, abstract = {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.}, language = {en} } @misc{MerinoCarrascoDorneanuetal., author = {Merino, Manuel and Carrasco, Laura and Dorneanu, Bogdan and Manrique, Jose and Menzhausen, Robert and Arellano-Garc{\´i}a, Harvey}, title = {Control Strategies for a Vapour Compression Refrigeration System Used in Mango Exports: An Alternative to Traditional on-Off Controllers}, series = {AIChE Annual Meeting}, journal = {AIChE Annual Meeting}, isbn = {978-0-8169-1114-1}, abstract = {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.}, language = {en} } @misc{MiahDorneanuMechlerietal., author = {Miah, Sayeef and Dorneanu, Bogdan and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Multi-Objective Design Optimisation of a Distributed Energy System through 3E (economic, environmental and exergy) Analysis}, series = {2020 Virtual AIChE Annual Meeting, November 20, 2020}, journal = {2020 Virtual AIChE Annual Meeting, November 20, 2020}, isbn = {978-0-8169-1114-1}, abstract = {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.}, language = {en} } @misc{DorneanuHeshmatMohamedetal., author = {Dorneanu, Bogdan and Heshmat, Mohamed and Mohamed, Abdelrahim and Ruan, Hang and Xiao, Pei and Gao, Yang and Arellano-Garc{\´i}a, Harvey}, title = {Stepping Towards the Industrial Sixth Sense}, series = {AIChE Annual Meeting, November 20, 2020}, journal = {AIChE Annual Meeting, November 20, 2020}, isbn = {978-0-8169-1114-1}, abstract = {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.}, language = {en} } @misc{DorneanuMechleriArellanoGarcia, author = {Dorneanu, Bogdan and Mechleri, Evgenia and Arellano-Garc{\´i}a, Harvey}, title = {Towards smart distributed energy systems}, series = {Jahrestreffen der ProcessNet-Fachgemeinschaften "Prozess-, Apparate- und Anlagentechnik" (PAAT)}, journal = {Jahrestreffen der ProcessNet-Fachgemeinschaften "Prozess-, Apparate- und Anlagentechnik" (PAAT)}, pages = {1}, abstract = {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.}, language = {en} } @misc{GonzalezAriasGonzalezCastanoArellanoGarcia, author = {Gonzalez-Arias, Judith and Gonzalez-Castano, Miriam and Arellano-Garc{\´i}a, Harvey}, title = {Utilization of CO2-Rich Residues for Syngas Production: Strategies for Catalyst Design}, series = {AIChE Annual Meeting, November 15, 2021}, journal = {AIChE Annual Meeting, November 15, 2021}, isbn = {978-0-8169-1116-5}, abstract = {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.}, language = {en} } @misc{MedinaMendezDorneanuArellanoGarcia, author = {Medina M{\´e}ndez, Juan Ali and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Homogeneous modeling for laminar flows in structured catalysts: CO2 methanation}, series = {Book of Abstracts zur Jahrestagung der DECHEMA/VDI-Fachgruppe Fluidverfahrenstechnik, 04. - 06. M{\"a}rz 2024}, journal = {Book of Abstracts zur Jahrestagung der DECHEMA/VDI-Fachgruppe Fluidverfahrenstechnik, 04. - 06. M{\"a}rz 2024}, publisher = {Ruhr Universit{\"a}t}, address = {Bochum}, pages = {2}, language = {en} } @misc{MedinaMendezDorneanuSchmidtetal., author = {Medina M{\´e}ndez, Juan Al{\´i} and Dorneanu, Bogdan and Schmidt, Heiko and Arellano-Garc{\´i}a, Harvey}, title = {Revisiting homogeneous modeling with volume averaging theory: structured catalysts for steam reforming and CO2 methanation}, series = {Book of Abstracts XXVI Fluid Mechanics Conference (FMC 2024), Warsaw, Poland, September 10-13, 2024}, journal = {Book of Abstracts XXVI Fluid Mechanics Conference (FMC 2024), Warsaw, Poland, September 10-13, 2024}, publisher = {University of Technology}, address = {Warsaw}, pages = {2}, language = {en} } @misc{DorneanuMappasVassiliadisetal., author = {Dorneanu, Bogdan and Mappas, Vassileios and Vassiliadis, Vassilios S. and Arellano-Garc{\´i}a, Harvey}, title = {Novel parametric gradient calculation method for multistage systems with generalized constraints}, series = {2024 AIChE Annual Meeting}, journal = {2024 AIChE Annual Meeting}, pages = {3}, abstract = {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.}, language = {en} } @misc{SafdarDorneanuSantosdaSilvaetal., author = {Safdar, Muddasar and Dorneanu, Bogdan and Santos da Silva, Jefferson and Santos Mascarenhas, Artur Jose and Valverde Pontes, Karen and Arellano-Garc{\´i}a, Harvey}, title = {Advancements in CO2 methanation: customized heterogeneous Ni-Perovskite catalyst for sustainable SNG production}, series = {Annual Meeting on Reaction Engineering and Electrochemical Processes 2024}, journal = {Annual Meeting on Reaction Engineering and Electrochemical Processes 2024}, language = {en} } @misc{MappasDorneanuHeinzelmannetal., author = {Mappas, Vassileios and Dorneanu, Bogdan and Heinzelmann, Norbert and Schnitzlein, Klaus and Arellano-Garc{\´i}a, Harvey}, title = {A unified modular framework for modeling multiphase reactors}, series = {Annual Meeting of Process Engineering and Materials Technology 2024}, journal = {Annual Meeting of Process Engineering and Materials Technology 2024}, language = {en} } @misc{JafariShafieeDorneanuetal., author = {Jafari, Mitra and Shafiee, Parisa and Dorneanu, Bogdan and Arellano-Garc{\´i}a, Harvey}, title = {Towards efficient material design: use of machine learning to predict chemical reactions and retrosynthesis}, series = {Annual Meeting of Process Engineering and Materials Technology 2024}, journal = {Annual Meeting of Process Engineering and Materials Technology 2024}, language = {en} }