Harvey Arellano-Garcia

Professor Harvey Arellano-Garcia

Director of Research; Professor of Chemical Engineering

Academic and research departments

Department of Chemical and Process Engineering.


Research interests

My research expertise includes the application of mathematical methods to optimise process design, control and operation as well as model-based experimental analysis in process and energy systems. My current research activities are concentrated on the development and application of systems engineering approaches for process intensification and integration including dynamic process simulation, model-based analysis and experimental verification, modelling and optimization of complex chemical and biological production systems, and energy conversion systems with large structural diversity and a high number of elements. Particular attention is paid to the holistic view of the involved processes phenomena, micro and macro processes, process design and the final experimental verification using miniplant technologies including improved control and monitoring.


Media Contacts

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Phone: +44 (0)1483 684380 / 688914 / 684378
Out-of-hours: +44 (0)7773 479911
Senate House, University of Surrey
Guildford, Surrey GU2 7XH

My publications


Sebastia Saez J, Reina T, Arellano-Garcia H (2017) Numerical Modelling of Braiding and Meandering Instabilities in Gravity-Driven Liquid Rivulets, Chemie Ingenieur Technik 89 (11) pp. 1515-1522 Wiley-VCH Verlag
Rivulet instabilities appear in many engineering applications. In absorption equipment, they affect the interface area available for mass transfer, and thus, reducing the efficiency. Here, computational fluid dynamics are used to reproduce the meanders and braids in rivulets flowing down an inclined channel. Fast oscillations of the meander (f = 5.6 Hz) are observed at low flow rates. At greater flow rates, an analysis of the transversal velocity in the retraction waves shows the effect of the surface tension, which causes the braiding phenomenon, and thus, the reduction in gas-liquid interface area.
Isaule F, Arellano-Garcia H, Rios Huguet A (2016) Di?neutrons in neutron matter within Brueckner?Hartree?Fock approach, Physical Review C: Nuclear Physics 94 034004 American Physical Society
We investigate the appearance of di?neutron bound states in pure neutron matter within the Brueckner?Hartree?Fock approach at zero temperature. We consider the Argonne v18 and Paris bare interactions as well as chiral two? and three?nucleon forces. Self?consistent single?particle potentials are calculated by controlling explicitly singularities in the g matrix associated with bound states. Di?neutrons are loosely bound, with binding energies below 1 MeV, but are unambiguously present for Fermi momenta below 1 fm?1 for all interactions. Within the same framework we are able to calculate and characterize di?neutron bound states, obtaining mean radii as high as
Patel R, Dawson K, Butterfield R, Khan A, Ahada B, Arellano-Garcia H (2014) Process for Synthesis of Biodiesel from Used Cooking Oil: Feasibility and Experimental Studies, Computer Aided Chemical Engineering 33 pp. 1111-1116 Elsevier
Biodiesel has turned out to be an integral part of the discussion of renewable energy sources and has diverse advantages in terms of its flexibility and applicability. Considering the characteristics of the transesterification reaction, a laboratory-scale system has been developed in this work. Waste Vegetable Oil (WVO), mainly sunflower oil, from local sources has been used and the transesterification carried out using methanol in the presence of sodium hydroxide catalyst. Characterisation of the biodiesel produced has been carried out using a number of different techniques including rheology, calorimetry, and gas liquid chromatography. The main factors affecting the % yield of biodiesel are temperature, catalyst, and alcohol to triglyceride ratio. Thus, experimental work has been carried out so as to study the rate and yield of the reaction as a function of those factors. A model has also been developed to validate the experimental data and this should help in increasing the efficiency of these processes and reducing the energy input. Moreover, the novel use of ultrasound as a method of measuring progression of the reaction is correlated with in-situ pH monitoring of the reaction process.
Yakut N, Barz T, López Cárdenas DC, Arellano-Garcia H, Wozny G (2013) Online model-based redesign of experiments for parameter estimation applied to closed-loop controller tuning, Chemical Engineering Transactions 32 (June) pp. 1195-1200 The Italian Association of Chemical Engineering
We present an approach to closed-loop online model-based redesign of experiments for system
identification. Special attention is given to the compliance with safety restrictions and operating
requirements during online experiments. For doing so, we propose the integration of a controller into the
system identification algorithm. To avoid numerical problems regarding ill-conditioned matrices an
algorithm for local parameter identifiability analysis is used. In order to demonstrate the benefits of our
approach, the proposed procedure is validated in a real case study. Additionally, a PI-controller is tuned for
the identified system. Moreover, the accuracy of the system parameters estimated by the proposed
strategy was compared with results for a conventional open-loop step response technique.
Arellano-Garcia H, Müller D, Hoang Minh D, Merchan VA, Kasaka Y, Müller M, Schomäcker R, Wozny G (2013) Towards a novel process concept for the hydroformylation of higher alkenes: Mini-plant operation strategies via model development and optimal experimental design, Chemical Engineering Science 115 (August 2014) pp. 127-138 Elsevier
When developing a new process with expensive and dangerous reaction partners, it is often of interest to keep pilot plant operation time low. A model of the process can aid in achieving this goal. However, the model is generally prone to errors, and thus, leading to deviations from the actual operation. In this contribution, the focus is set on the modeling of a novel process concept for the hydroformylation of long-chained alkenes with particular interest laid on the three phase micellar system. Moreover, a methodology is presented to support operators in determining suitable operating policies for mini-plant operation. Two models of the core units, reactor and decanter, of the constructed mini-plant are presented and linked. With these, an operation policy for the minimization of model parameter uncertainty is determined.
Baran N, Wozny G, Arellano-Garcia H (2012) Model-based system identification and PI controller tuning using closed-loop set-point response, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 755-759 Elsevier
In this work, a new approach to model identification and PI controller tuning based on model-based experimental design is presented. In the proposed strategy, system identification relies on a closed-loop set-point response. For this purpose, experiments are first exemplarily executed with a P-controller. Therefore, in this specific case only one design variable is considered that is represented by the controller gain. Additionally, we use the results achieved in the system identification step for the calculation of controller settings. In order to validate our approach and demonstrate the benefits of the proposed strategy, different scenarios are simulated.
Bournazou MN, Hooshiar K, Arellano-Garcia H, Wozny G, Lyberatos G (2013) Model based optimization of the intermittent aeration profile for SBRs under partial nitrification., Water research 47 (10) pp. 3399-3410
In this paper, a fast and accurate optimization framework is proposed to compute optimal aeration policies in SBR processes under partial nitrification. The optimization framework aims to determine an optimal intermittent aeration profile which minimizes both the operation time of the SBR cycle and the energy required for aeration. Special consideration is given to the fact that the results not only need to be accurate but also to converge within a short time. Moreover, methods to avoid nitrate formation are analyzed and implemented. It is demonstrated that the implementation of a nonlinear model "5-state" and the reduction of the optimization problem to three control variables are the keystones to an efficient solution strategy which achieves fast, robust, and accurate computation of the optimal intermittent aeration profile for any given conditions of the process. The optimization approach is so efficient that it can also be implemented with more complex models such as the ASM3 extended for a two-step nitrification-denitrification process.
Zhang S, Müller D, Arellano-Garcia H, Wozny G (2013) CFD simulation of the fluid hydrodynamics in a continuous stirred-tank reactor, Chemical Engineering Transactions 32 (June) pp. 1441-1446 The Italian Association of Chemical Engineering
Continuous stirred-tank reactors (CSTR) are widely applied in the chemical, food, and pharmaceutical
engineering fields. The micro-scale fluid dynamics are important for the optimal processing study since
they have a dominating influence on the overall performance of the reactor. In this article, 3-dimensional
Computational Fluid Dynamics (CFD) simulations are carried out to portray the flow characters in the
CSTR of the mini-plant of the Collaborative Research Center InPROMPT coordinated by the Technische
Universität Berlin. In InPROMPT, the reactor is used to perform a rhodium-catalyzed hydroformylation of
long chain alkenes. In this study, cases of a vessel with and without baffles are compared. The results
show the existence of a high speed velocity toroidal zone in different horizontal sections in the CSTR
without baffles, comparing to the common pervasive conception which is the assumption of a complete
uniformity of the fluid velocity magnitude in a CSTR at the final steady state. Moreover, under the rotation
speed of 400 rpm, the baffles in the CSTR can significantly prevent the formation of a surface vortex, for
the mean tangential velocity magnitude is dramatically decreased. On the other hand, the mean radial and
axial velocity is tremendously increased when the baffles are added. Therefore, the baffles in the tank lead
to a greater vertical fluid exchange in CSTR. Besides, in the specific domain of CSTR region, both the fluid
velocity direction and magnitude carry on a cyclical variation, when the baffles are inserted into the CSTR.
Vassiliadis VS, Fiorelli F, Arellano-Garcia H (2015) A Novel Quantisation-based Integration Method for ODEs, Computer Aided Chemical Engineering 37 pp. 473-478 Elsevier
Integration of Ordinary Differential Equations (ODE's) plays a paramount role in the dynamic simulation of a wide spectrum of processes in Chemical Engineering. This paper presents a novel approach within our discipline, namely the Quantised State Integration technique (QSI) (also known as Quantised State Simulation, QSS) which was introduced in its raw form several decades ago within Electrical Engineering for the simulation of electrical and electronic circuits in dynamic operation. While traditionally integration of ODE's considers time to be the coordinating parameter and it is discretised to allow the calculation of the state variables evolution, in QSS methods the states are discretised and time is calculated at points states go state events (changes by an amount equal to the discretisation level for each of them)-this allows effectively the decoupling of the state integration within accuracy tolerances. In the current work, we present significant theoretical and implementational extensions to the method, rendering it capable of handling large- to huge-scale applications involving stiff systems, state discontinuities (discrete events in hybrid systems) as well as the efficient calculation of sensitivity equations-all aspects that have previously been impossible to incorporate in the QSS suite of techniques presented over the years. Overall, all theoretical and preliminary computational demonstrations show it to be a very promising and powerful integration technique with a strong potential for future evolution and contributions. A multitude of areas that can benefit from this technique are identified in the paper
Wu X, Arellano-Garcia H, Hong W, Wozny G (2013) Improving the Operating Conditions of Gradient Ion-Exchange Simulated Moving Bed for Protein Separation, Industrial and Engineering Chemistry Research pp. 5407-5417
Chromatographic separation processes such as simulated moving bed (SMB) are widely used in the petrochemical, fine chemical, sugar, and pharmaceutical industries. Their separation efficiency can be improved by optimizing the components? adsorptivity in the different unit sections through, e.g., the use of solvent, temperature, or PH gradients. In this work, the salt gradient ion-exchange SMB used to separate two proteins, ²-lactoglobulins A and B, is theoretically analyzed, where the protein adsorption is described by the steric mass action model. Detailed model-based sequential optimization studies have been carried out for both closed-loop isocratic SMB as well as closed and open-loop gradient ion-exchange SMB. The separation efficiency is described by the throughput. Different gradient cases were analyzed to find out the influence factors. The results show that the gradient SMB is more efficient than the isocratic SMB in terms of startup time, throughput, and desorbent-to-throughput ratio. Moreover, it can be known that using open-loop gradient ion-exchange SMB to separate proteins is more effective than using closed-loop gradient SMB. The influencing factors such as the mass transfer efficiency and the maximum flow rate on separation efficiency are discussed according to different cases.
López DC, Hoyos LJ, Uribe A, Chaparro S, Arellano-Garcia H, Wozny G (2012) Improvement of crude oil refinery gross margin using a NLP model of a crude distillation unit system, Computer Aided Chemical Engineering, vol.30 - proceedings of the 22nd European Symposium on Computer Aided Process Engineering (ESCAPE22) 30 pp. 987-991 Elsevier
This work presents a Non Linear Programming (NLP) model developed to optimize simultaneously a crude oil distillation unit (CDU) system and several cases of application run in a refinery as well. This model optimizes feedstock composition and operational conditions for a CDU System (ECOPETROL S.A.). The NLP Model uses a Metamodeling approach so as to represent Atmospheric Distillation Towers (ADT). The Vacuum Distillation Towers (VDT) are implemented assuming perfect separation (assay cuttings). The defined objective function is given by an economic profit. The CDU system consists basically of five industrial units and fourteen Colombian Crude Oils. Each Metamodel uses as independent variables: crude oil flow rates, operational conditions, Jet EBP, and Diesel T95% from ASTM D-86 distillation curve. The output variables of the Metamodels are product flows, temperatures, and qualities.

The developed NLP model was implemented in GAMS. The time needed for its solution is around 60s while using the CONOPT solver. The NLP model results were successfully applied to a Colombian refinery for 3 consecutive weeks. The model was able to find the best use of installed equipments in CDUs through the preparation of a crude oil charge quasi-constant quality without matter the time period of the optimization. In each week, optimal crude oil flow rates towards each CDU (like new scenarios implemented in the refinery) were evaluated in a refinery global simulator with all downstream refining schemes in order to calculate the Refinery Gross Margin (RGM). In each analyzed case, the obtained RGM for new crude oil feeds was however better than that case without optimization with a economic benefit of up to 0.043 US$/bl equivalent to US$ 3.870.000 per year. This shows the effectiveness of a CDU NLP model within short term planning in the petroleum industry.

Wallau W, Schlawitschek C, Arellano-Garcia H (2016) Electric Field Driven Separation of Oil-Water Mixtures: Model Development and Experimental Verification, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 55 (16) pp. 4585-4598 AMER CHEMICAL SOC
Lopez D, Barz T, Arellano-Garcia H, Wozny G, Villegas A, Ochoa S (2012) Subset selection for improved parameter identification in a bio-ethanol production process, Czasopismo Techniczne. Mechanika 109 (1-M) pp. 137-147 Interdisciplinary Centre for Mathematical and Computational Modelling
A systematic approach for system identification is applied to experimental data of ethanol production from cellulose. Special attention is given to the identification of model parameters, which can be reliably estimated from available measurements. For this purpose, an identifiable parameter subset selection algorithm for nonlinear least squares parameter estimation is used. The procedure determines the parameters whose effects are unique and have a strong effect on the predicted (measurement variables) output variables. The system is described by a generic process model for the simultaneous saccharification and fermentation including three enzyme-catalyzed reactions. The process model is clearly over-parameterized. By applying the subset selection approach the parameter space is reduced to a reasonable subset, whose estimated parameters are still able to predict the experimental data accurately.
Kuntsche S, Barz T, Kraus R, Arellano-Garcia H, Wozny G (2011) MOSAIC a web-based modeling environment for code generation., Computers & Chemical Engineering 35 11 pp. 2257-2273
Wallau W, Patel R, Mujtaba I, Arellano-Garcia H (2014) Electric Field Driven Separation of Oil-water Mixtures: Model Development, Computer Aided Chemical Engineering 33 pp. 1615-1620 Elsevier
Coalescence enhancement of water droplets in oil emulsions is commonly contemplated for the separation of an aqueous phase dispersed in a dielectric oil phase with a considerably lower dielectric constant than that of the dispersed phase. The characteristics and geometry of the electrode system have a large impact on the performance of an electrostatic coalescer and are actually strictly linked to the type of the applied electric field and the emulsion used. Furthermore, addition of chemicals and heating has also been revealed to further enhance the electrocoalescence of water droplets. In this work, the coalescence of two water drops sinking in a dielectric oil phase at an applied high voltage, pulsed dc electric field, in particular with regards to the effects of pressure and temperature on coalescence performance is investigated. The developed model should help to recognise and prove approaches to electrocoalescence mechanisms, the dispersion flow direction with respect to the applied electric field, as well as the electric field configuration.
Müller D, Höser S, Kahrs O, Arellano-Garcia H, Wozny G (2012) Optimization of process operation strategies by combining process models with plant operating data, Chemical Engineering Transactions 29 (August) pp. 1495-1500 The Italian Association of Chemical Engineering
Competition, cost pressure, and market fluctuations lead to a persistent increase in complexity and degree of integration of chemical plants. The utilization of accurate process models facilitate plant efficiency optimization in real-time and improve process transparency for the plant personnel. To reduce development time and costs, existing models from the process development phase of the chemical plant can be used. Next to the general availability of a plant model and plant operating data, a systematic strategy is helpful to successfully implement a validated process model into the process control system of a chemical plant.
This contribution presents a strategy to develop a technology platform with a validated process model containing the following steps: analysis of the economic potential, software selection, process analysis, steady-state detection, parameter identification, and process optimization. The presented strategy is applied to an industrial plant of BASF SE in Ludwigshafen, Germany. The application of this platform exposes great economic potential. Firstly, a significant cost reduction can be achieved by reusing existing models during the development phase. Secondly, with the help of the technology platform soft-sensors are created, bottlenecks identified, and an optimization of process operating strategies is undertaken.
Vassiliadis VS, Wang Y, Yuan Y, Arellano-Garcia H (2015) A Novel Rigorous Mathematical Programming Approach to Construct Phenomenological Models, Computer Aided Chemical Engineering 37 pp. 707-712 Elsevier
The automated construction of physical laws from raw experimental measurements poses a great challenge in modern modelling and remains an open question. The work here presents a novel generalized Mixed-Integer Nonlinear Programming (MINLP) approach, which constitutes a rigorous theoretical formulation that best fits the given data. The proposal is based on the use of generic representation of analytical functions as binary evaluation trees which are Directed Acyclic Graphs (DAG) utilized to allow the construction of a superstructure out of which the optimal fitting model can be identified by solving the resulting (non-convex) MINLP problems. The trees are constructed in a way that their nodes are comprised of a linear combination of basic atomic functions, either arithmetic or unary, weighted by binary decision variables. Both single-input single-output (SISO) and multiple-input multiple-output systems are considered, as well as more complex models comprised of differential equations or even described by series summation of algebraic terms. The aim and contribution proposed methodology in this paper is to present the most general theoretical formulatioon of how models are constructed for systems quantification via analytical function forms, irrespective of the source of data. The constructed formulation is shown to contain all formulations thus far presented in the open literature, comprising a starting point either for direct fitting or for the derivation of simplified approaches.
Arellano-Garcia H, Wozny G (2009) Chance constrained optimization of process systems under uncertainty: I. Strict monotonicity., Computers & Chemical Engineering 33 10 pp. 1568-1583
Salerno D, Arellano-Garcia H, Wozny G (2012) Techno-Economic Analysis for the Synthesis of Downstream Processes from the Oxidative Coupling of Methane Reaction, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 Elsevier
Due to the huge methane deposits worldwide and the great need for the chemical process industry to have new alternatives for olefins production, especially ethylene as starting raw material for numerous products, the direct conversion of methane to ethylene has attracted considerable interest. The main reason that motivates the realization of this new approach is to exploit the availability of un-reacted methane, coming from the exit flue gas products of the OCM reactor, and thus, design an alternative process for methanol and formaldehyde production via OCM and the co-generation of electricity that can make the process economically attractive and designed so as to be industrially implemented. The total project investment, based on total equipment cost, as well as variable and fixed operating costs, was developed based on mass and energy balance information taken from Aspen® Process Economic Analyzer simulation results. The feasibility was evaluated in terms of energy savings, CO2- emission reductions and costs, in comparison to the separate production of methanol with conventional technology alone. Before starting the economic study of the OCM process a preliminary analysis of possible plant locations has been developed. Natural gas is a commodity which price varies strongly from one region to another. Moreover, not only the price of raw materials is affected by the location of the plant but also the costs associated with the production, namely: steam, refrigeration, electricity, fuel, wages, etc., affecting strongly the profitability of a petrochemical project. Due to low natural gas prices in Venezuela, which has the highest production potential in South America, and the highest ethylene sales for the European market, this geographical location has been chosen for economic analysis of this project. Kinetic data of the OCM reaction were taken from the experimental fluidized bed reactor values that has been build in our facilities at TU-Berlin, which reflect promising conversion, selectivity and yield values, testing different catalysts developed at the Institute of Chemistry inside the scope of the UNICAT project. This analysis suggests areas for research focus that might improve the profitability of natural gas conversion, and the results have also been used for the design of the pilot plant which is now being operational at our department.
Li P, Arellano-Garcia H, Wozny G (2008) Chance constrained programming approach to process optimization under uncertainty., Computers & Chemical Engineering 32 1-2 pp. 25-45
Hoang DM, Merchan VA, Barz T, Biegler L, Arellano-Garcia H, Wozny G (2013) Model-Based Experimental Design: A Comparison between Sequential and Simultaneous Optimization approaches, Proceedings of WCCE9: 9th World Congress of Chemical Engineering
Mathematical models are essential for chemical processes since they contribute to both identification and manipulation of process mechanisms, e.g. in reaction systems, separation processes and process controls. The methodologies of model-based experiment design aim at reducing the uncertainties of estimated model parameters, and thus, make the identification and use of these models possible. Up to now, sequential optimization approaches have been applied to solve the related extended optimal control problem. In this contribution, a substantial comparison between the sequential and the simultaneous optimization approach for optimal model-based experimental design is presented with respect to convergence behavior and computational load. Moreover, both approaches are compared regarding high order and continuous control trajectories as well as restrictions from the process. Process restrictions, especially regarding state variables and continuity of control trajectories have a tremendous importance with respect to the practical implementation, but are mostly just touched or totally neglected during the optimization steps so far. The results are discussed by the application on a CSTR example.
Chan MSC, del Rio-Chanona EA, Fiorelli F, Arellano-Garcia H, Vassiliadis VS (2016) Construction of global optimization constrained NLP test cases from unconstrained problems, CHEMICAL ENGINEERING RESEARCH & DESIGN 109 pp. 753-769 INST CHEMICAL ENGINEERS
Lenhart E, Esche E, Arellano-Garcia H, Biegler LT (2012) Oxidative Coupling of Methane: Optimal Operating Policies for a Membrane Reactor Network, Chemie Ingenieur Technik 84 (11) pp. 1980-1988 WILEY-VCH Verlag GmbH & Co.
The oxidative coupling of methane (OCM), in which methane is turned into ethylene and ethane, presents an opportunity for using natural gas to produce desired C2 hydrocarbons. The main challenge for the successful implementation of the process is the reduction of undesired by-products, such as CO2. This contribution deals with the optimization of a membrane reactor network for the OCM process with the goal of maximizing yield while maintaining simultaneously a high selectivity in C2 products. The network consists of a plug flow/fixed-bed reactor, a conventional packed-bed membrane reactor and a so-called proposed packed-bed membrane reactor.
Merchan VA, Kraus R, Barz T, Arellano-Garcia H, Wozny G (2012) Generation of first and higher order derivative information out of the documentation level, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 950-954 Elsevier
The accurate and efficient evaluation of first and higher order derivative information of mathematical process models plays a major role in the field of Process Systems Engineering. Although it is well known that the chosen methods for derivative evaluation may have a major impact on solution efficiency, a detailed assessment of these methods is rarely made by the modeler. Since standard modeling tools and some solvers normally only support own default methods for derivative evaluation, the evaluation of further methods can be a tedious work, and thus requiring the connection of different tools.

In this contribution the implementation of a general method for generation of derivative information out of the documentation level is presented. Exploiting the possibility of code generation given by the web-based modeling environment MOSAIC (Kuntsche et al. 2011), derivative information of model equations is generated either by symbolic derivatives or by coupling the models with state of the art automatic differentiation (AD) tools. This offers the modeler different methods of getting exact derivative values and opens the possibility of integrating the assessment of derivative evaluations within the modeling and simulation workflow.

Werk S, Barz T, Wozny G, Arellano-Garcia H (2012) An approach to process monitoring under probabilistic constraints, Computer Aided Chemical Engineering, vol.30 - proceedings of the 22nd European Symposium on Computer Aided Process Engineering (ESCAPE22) 30 pp. 1252-1256 Elsevier
Operators in chemical plants are confronted with several different measured process variables and parameters. Although the precision of measuring rose, individual measurements remained uncertain. This might affect real measurements such as temperature or pressure, where the measured value is more an expected value, with the real value within a range around it or also process dynamics, which hold exactly only under certain circumstances. Within the process monitoring and control, the operator has to take such uncertainties into account; on the one hand to not risk the violation of safety regulations, on the other hand to not use a too conservative control and give away product or quality. Even though an experienced and skilled operator might be able to handle single uncertain parameters and variables quiet efficiently, the outcome of multiple uncertain parameters is difficult. To handle multiple uncertain parameters simultaneously in optimisation, the concept of chance-constrained optimisation has been developed and extended over the last years. In this work, we present developed techniques of chance-constrained optimisation for process monitoring and control. It will allow to calculate potential key performance indicators out of uncertain variables and parameters, which can help operators in the decision making process. However, one drawback of using chance-constraints techniques is the required computation time for calculation. It requires a significant amount of individual calculations. Therefore, algorithmic improvements were required to meet the requirements of online monitoring and control. The talk will present the application of the developed chance-constrained approach on uncertain parameters in process monitoring and control, give an insight how the computing time improvements were fulfilled and show results of a practical evaluation.
Esche E, Arellano-Garcia H, Biegler LT (2014) Optimal operation of a membrane reactor network, AIChE Journal 60 (1) pp. 170-180 American Institute of Chemical Engineers
In this contribution, the operation of a membrane reactor network (MRN) for the oxidative coupling of methane is optimized. Therefore, three reactors, a fixed bed reactor (FBR) and two packed bed-membrane reactors, are modeled. For the (CPBMR), a two-dimensional (2-D) model is presented. This model incorporates radial diffusion and thermal conduction. In addition, two 10 cm long cooling segments for the CPBMR are implemented based on the idea of a fixed cooling temperature positioned outside the reactor shell. The model is discretized using a newly developed 2-D orthogonal collocation on finite elements with a combination of Hermite for the radial and Lagrangian polynomials for the axial coordinate. Membrane thickness, feed compositions, temperatures at the inlet and for the cooling, diameters, and the amount of inert packing in the reactors are considered as decision variables. The optimization results in C2 yields of up to 40% with a selectivity in C2 products of more than 60%. The MRN consisting of an additional packed-bed membrane reactor with an alternative feeding policy and a FBR shows a lower yield than the individual CPBMR.
Godini H, Jaao S, Xiao S, Arellano-Garcia H, Wozny G (2012) Methane Oxidative Coupling: Synthesis of Membrane Reactor Networks, Industrial and Engineering Chemistry Research 51 (22) pp. 7747-7761 American Chemical Society
In this work, the performance of the methane oxidative coupling process based on different alternative reactor structures including fixed-bed reactor, two different feeding-structures of porous packed bed membrane reactor, and different conceptual network combinations of them was analyzed in a comprehensive model-based study. In this context, a contour-based graphical visualizing method accompanied by multiscenario generation and examination approach was exploited so as to systematically screen out the high achievable process performances and the corresponding reactor network specifications. As performance indicators, several objective measures including the highest achievable values for yield, selectivity and methane conversion were applied over a high number of design scenarios. Thereby, several sets of structural and operating parameters were evaluated. The investigated parameters are temperature, membrane thicknesses, types of catalysts, amount of inert packing in the catalyst bed, the flow rate of oxygen-rich stream entering the reactor system (total methane to oxygen ratio), distribution of the oxygen rich stream through the reactor blocks (local methane to oxygen ratio), distribution of the total methane-rich feed stream into the reactor blocks, and the contact time represented by the reactor length. A high C2-yield of 31% and 88% C2-selectivity were observed at the same time, and thus, highlighting the performance potential of the reactor network. Moreover, the proposed method enables one to consider operating aspects such as hot spot formation during the analysis and screening procedure.
Li B, Nguyen VH, Ng CL, del Rio-Chanona EA, Vassiliadis VS, Arellano-Garcia H (2016) ICRS-Filter: A randomized direct search algorithm for constrained nonconvex optimization problems, Chemical Engineering Research and Design 106 pp. 178-190
This work presents a novel algorithm and its implementation for the stochastic optimization of generally constrained Nonlinear Programming Problems (NLP). The basic algorithm adopted is the Iterated Control Random Search (ICRS) method of Casares and Banga (1987) with modifications such that random points are generated strictly within a bounding box defined by bounds on all variables. The ICRS algorithm serves as an initial point determination method for launching gradient-based methods that converge to the nearest local minimum. The issue of constraint handling is addressed in our work via the use of a filter based methodology, thus obviating the need for use of the penalty functions as in the basic ICRS method presented in Banga and Seider (1996), which handles only bound constrained problems. The proposed algorithm, termed ICRS-Filter, is shown to be very robust and reliable in producing very good or global solutions for most of the several case studies examined in this contribution.
Barz T, López Cárdenas DC, Arellano-Garcia H, Wozny G (2013) Experimental evaluation of an approach to online redesign of experiments for parameter determination, AIChE Journal 59 (6) pp. 1830-2266 American Institute of Chemical Engineers
The online redesign of experiments for parameter determination of nonlinear dynamic systems has been studied recently by different research groups. In this article, this technique is assessed in a real case study for the first time. The presented algorithm adopts well-known concepts from model-based control. Compared to previous studies, special attention is given to the efficient treatment of the underlying nonlinear and possibly ill-conditioned parameter estimation and experiment design problems. These problems are solved with single shooting and gradient-based nonlinear programming (NLP) solvers. We use an initial value solver, which generates first- and second-order sensitivities to compute exact derivatives of the problem functions. As a special feature, we propose the integration of a local parameter identifiability analysis and a corresponding algorithm that generates well-conditioned problems. The practical applicability is demonstrated by experimental application to a chromatography column system where A, D, and E optimal experiments are performed.
Barz T, Kuntsche S, Wozny G, Arellano-Garcia H (2011) An efficient sparse approach to sensitivity generation for large-scale dynamic optimization., Computers & Chemical Engineering 35 10 pp. 2053-2065
Esche E, Arellano-Garcia H, Wozny G, Biegler LT (2012) Optimal Operation of a Membrane Reactor Network, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 1321-1325 Elsevier
In this work, a two-dimensional model for a conventional packed-bed membrane reactor (CPBMR) is developed for the oxidative coupling of methane, which uses a nonselective porous membrane to continuously feed oxygen to the catalytic bed. The model incorporates radial diffusion and thermal conduction and assumes convective transport for the axial direction. In addition, two 10 cm long cooling segments for the CPBMR were implemented based on the idea of a fixed cooling temperature outside the reactor shell. The resulting model is discretized using two-dimensional orthogonal collocation on finite elements with a combination of Hermite polynomials for the radial and Lagrangian polynomials for the axial coordinate. The simulation study shows that it is necessary to make all transport coefficients dependent on local temperatures and compositions. This leads to a simulation with roughly 130,000 variables, which is then used to generate initial points for the optimization of the CPBMR stand-alone operation. In addition, inequality constraints and variable bounds are introduced so as to avoid potentially hazardous mixtures of methane and oxygen in both shell and tube as well as to keep the temperatures below levels stressing reactor materials (
Hoang MD, Wozny G, Brunsch Y, Behr A, Markert J, Hamel C, Seidel-Morgenstern A, Arellano-Garcia H (2012) Model-Based Optimal Design of Experiments for Determining Reaction Network Structures, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 705-709 Elsevier
A new approach for optimal experimental design has been developed to support the work of chemists and process engineers in determining reaction kinetics of complex reaction networks. The methodology is applied on sub-networks of the hydroformylation process of 1-dodecene with a Biphephos-modified rhodium catalyst in a DMF-decane thermomorphic solvent system (TMS). The isomerization and hydrogenation sub-networks are systematically analyzed with respect to parameter estimability. They are determined in a sequential approach using model-based optimal experimental design via perturbations with respect to temperature and synthesis gas pressure, and subsequently used to build up the reaction network. The focus of this contribution is the parameter estimation procedure at the very early investigation stage where model uncertainties are high. Sensitivities of sensitive parameters are increased while others are suppressed, which are carried over from the estimated sub-networks or structurally more difficult to determine. This subsequently leads to more reliable parameter estimations.
Kiedorf G, Hoang DM, Müller A, Jörke A, Markert J, Arellano-Garcia H, Seidel-Morgenstern A, Hamel C (2013) Kinetics of 1-dodecene hydroformylation in a thermomorphic solvent system using a rhodium-biphephos catalyst, Chemical Engineering Science 115 (August 2014) pp. 31-48 Elsevier
The hydroformylation of 1-dodecene on a rhodium-biphephos catalyst complex exploiting a thermomorphic multicomponent solvent system was studied experimentally in a batch reactor in order to describe the kinetics of the main and the most relevant side reactions. The formation of the active catalyst was studied in preliminary experiments. Based on a postulated catalytic cycle mechanistic kinetic models were developed considering isomerization, hydrogenation and hydroformylation reactions as well as the formation of not catalytically active Rh-species. The complex overall network was decomposed to support parameter estimation. The isomerization of 1-dodecene, the hydrogenations of iso- and 1-dodecene and the hydroformylations of iso-dodecene and 1-dodecene were investigated as a function of temperature, total pressure and partial pressures of carbon monoxide and hydrogen, respectively. These four sub-networks of increasing size and the total network were analyzed sequentially in order to identify kinetic models and to estimate the corresponding parameters applying model reduction techniques based on singular value decomposition combined with rank revealing QR factorization.
Cruz Bournazou MN, Junne S, Neubauer P, Barz T, Arellano-Garcia H, Kravaris C (2014) An approach to mechanistic event recognition applied on monitoring organic matter depletion in SBRs, AIChE Journal 60 (10) pp. 3460-3472
A fundamental practice in process engineering is monitoring the state dynamics of a system. Unfortunately, observability of some states is related to high costs, time, and efforts. The mechanistic event recognition (MER) aims to detect an event (defined as a change of the system with specific significance to the operation of the process) that cannot be directly observed but has some predictable effect on the dynamics of the systems. MER attempts to apply fault diagnosis techniques using mechanistic ?recognition? models to describe the process. A systematic method for building recognition models using optimal experimental design tools is presented. As proof of concept, the MER approach to detect organic matter depletion in sequencing batch reactors, measuring only ammonia, dissolved oxygen, and nitroxides is applied. The event, that is, consumption of organic matter to a level below 50 gCOD/m3, was successfully detected even though microbial activity is known to continue after organic matter depletion.
Jaao S, Sadjadi S, Godini H, Simon U, Arndt S, Görke O, Berthold A, Arellano-Garcia H, Schubert H, Schomäcker R, Wozny G (2012) Experimental investigation of fluidized-bed reactor performance for oxidative coupling of methane, Journal of Natural Gas Chemistry 21 (5) pp. 534-543 Elsevier
Performance of the oxidative coupling of methane in fluidized-bed reactor was experimentally investigated using Mn-Na2WO4/SiO2, La2O3/CaO and La2O3-SrO/CaO catalysts. These catalysts were found to be stable, especially Mn-Na2WO4/SiO2 catalyst. The effect of sodium content of this catalyst was analyzed and the challenge of catalyst agglomeration was addressed using proper catalyst composition of 2%Mn-2.2%Na2WO4/SiO2. For other two catalysts, the effect of Lanthanum-Strontium content was analyzed and 10%La2O3?20%SrO/CaO catalyst was found to provide higher ethylene yield than La2O3/CaO catalyst. Furthermore, the effect of operating parameters such as temperature and methane to oxygen ratio were also reviewed. The highest ethylene and ethane (C2) yield was achieved with the lowest methane to oxygen ratio around 2. 40.5% selectivity to ethylene and ethane and 41% methane conversion were achieved over La2O3-SrO/CaO catalyst while over Mn-Na2WO4/SiO2 catalyst, 40% and 48% were recorded, respectively. Moreover, the consecutive effects of nitrogen dilution, ethylene to ethane production ratio and other performance indicators on the down-stream process units were qualitatively discussed and Mn-Na2WO4/SiO2 catalyst showed a better performance in the reactor and process scale analysis.
Stünkel S, Bittig K, Godini H-R, Jaso S, Martini W, Arellano-Garcia H, Wozny G (2012) Process development in a miniplant scale - A multilevel - multiscale PSE approach for developing an improved Oxidative Coupling of Methane process, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 1692-1696 Elsevier
The oxidative coupling of methane (OCM) is a promising alternative route to olefins that converts methane to higher hydrocarbons and open up a new feedstock for the oil based industry. However, due to yield limitations of available catalysts and high separation costs for conventional gas processing, the OCM process has not been applied yet in the industry. Starting with process simulation and sensitivity studies a flexible mini-plant was built in this research so as to demonstrate technical feasibility of an efficient OCM process, model validity and to study long term effects. By this means a concurrent engineering approach was applied for the whole process while investigating each unit parallel. Moreover, catalyst with several reactor concepts like the fluidized bed and membrane reactor were investigated by CFD simulation, process simulation and experiments, in order to study catalyst life time, operation conditions and technical feasibility. Thus, the reaction section was improved from 16% yield to 18%. Furthermore, the separation part of the OCM process was energetically improved by an integrated down streaming unit for the CO2. Thus, an energetic improvement of more than 40% in comparison to a benchmark absorption - desorption based CO2 separation process was achieved. In addition to this, novel absorbents were studied starting with molecular simulation up to process simulation and experimental validation for the CO2 separation. The results of the integrated process development and optimization process for the OCM will be presented and an overview of the multi scale and multilevel Process System Engineering (PSE) approach will be given for the case study.
Barz T, Löffler V, Arellano-Garcia H, Wozny G (2010) Optimal determination of steric mass action model parameters for beta-lactoglobulin using static batch experiments., Journal of chromatography. A 1217 (26) pp. 4267-4277
In this work, parameters of the steric mass-formalism SMA are optimally ascertained for a reliable determination of the adsorption isotherms of beta-lactoglobulin A and B under non-isocratic conditions. For this purpose, static batch experiments are used in contrast to the protocols based on different experimental steps, which use a chromatographic column. It is shown that parameters can already be determined for a small number of experiments by using a systematic procedure based on optimal model-based experimental design and an efficient NLP-solver. The in different works observed anti-Langmuir shape of the isotherm for small concentrations of beta-lactoglobulin A was corroborated. Moreover, we also found indications for a porosity variation with changing protein concentrations.
Kraus R, Merchan VR, Arellano-Garcia H, Wozny G (2013) Hierarchical Simulation of integrated Chemical Processes with a Web based Modeling Tool, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 155-159
A novel approach for the systematic and hierarchical derivation of process models is presented. Model candidates for different unit phenomena are collected and rated on the basis of the model structure, origin and the modeler's belief. The process model is created as a superstructure with the competing partial models. Thereby, it is possible to determine the best possible combination through optimization with respect to different objective functions. The systematic procedure has been implemented into the online web modeling platform MOSAIC. Based on the superstructure, optimization code for the state-of-the art optimization and simulation software can automatically be created. Based on two case studies, the new approach is demonstrated, namely a process model for the hydroformylation of long-chain olefins and a model for the pressure drop in packed columns with foaming components.
Miranda JCC, Ponce GHSF, Arellano-Garcia H, Maciel F. R, Wolf M. MR (2015) Energy and Yield Evaluation of an Alcohols and Hydrocarbons Production Plant using Rh-based Catalysts with Different Promoters, Computer Aided Chemical Engineering 37 pp. 1271-1276 Elsevier
Synthesis gas (syngas), mainly constituted by carbon monoxide (CO) and hydrogen gas (H2), is produced mostly through biomass gasification and methane reforming. In the last decade, the thermochemical route to produce ethanol and higher alcohols from syngas has been gaining space as a possible route to produce synthetic fuels and additives. This kind of process presents a series of advantages as: short-time reaction, abundant and lower-price feedstocks, the use of lignin and the almost complete conversion of syngas, having the potential to exceed ethanol production by fermentative route. Aiming to produce ethanol through thermochemical route, a singular process (a small-scale plant with capacity to process 100 kmol/h of syngas) was proposed for a first evaluation using the commercial simulator ASPEN Plus v7.3. Four different Rh-based catalysts were tested in the process (RhFe, RhLa, RhLaV, and RhLaFeV), trying to take advantage of the characteristics of Rh-based catalysts as high ethanol selectivity and hydrocarbons production. The process design took into account the reactor selectivity and conversion. Through sensitivity analysis, the downstream process were configured searching for the best possible design of separation steps, making possible to obtain ethanol (>99 % wt.), methanol (>90 % wt.), Liquified Petroleum Gas (LPG, mixture of C2H6, C3H8 and C4H10, > 99 % wt.) and pentane (>95% wt.).
Arellano-Garcia H, Carmona I, Wozny G (2008) A new operation mode for reactive batch distillation in middle-vessel columns: Start-up and operation., Computers & Chemical Engineering 32 1-2 pp. 161-169
Cruz Bournazou MN, Arellano-Garcia H, Wozny G, Lyberatos G, Caravaris C (2012) ASM3 extended for two-step nitrification?denitrification: a model reduction for sequencing batch reactors, Journal of Chemical Technology and Biotechnology 87 (7) pp. 887-896 Wiley
BACKGROUND: The ASM3 extended for two-step nitrification?denitrification represents the most accurate model for the description of the activated sludge process with nitrate bypass nitrification?denitrification. This model includes 20 reaction rates, 15 state variables, and more than 35 parameters, which make its calculation costly and difficult to estimate. The lack of a fast and accurate model able to predict both concentration of nitrite and nitrate over time is the principal obstacle for efficient model-based optimization and model-based control.

RESULTS: In this work, a fast and accurate model for the activated sludge process in a sequencing batch reactor is proposed. For this purpose, the ASM3 extended for two-step nitrification?denitrification, a 15-state variable model built for a general description of the ASP, is reduced to match the specific conditions of sequencing batch reactor systems with shortcut biological nitrogen removal to a nine-state model and then further to a six-state and five-state model under appropriate assumptions. The proposed model maintains the two-step nitrification?denitrification process feature of the original model and can thus describe the bypass of nitrate, showing increased tractability and lower computer costs. Different approaches for model reduction together with an exhaustive analysis of the extended ASM3 model as well as the process are discussed.

CONCLUSIONS: The resulting model with only five differential equations reduces the calculation time by up to one order of magnitude, while maintaining a high description accuracy, demonstrating the advantages of model reduction.

Werk S, Barz T, Arellano-Garcia H, Wozny G (2012) Performance Analysis of Shooting Algorithms in Chance-Constrained Optimization, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 1512-1516 Elsevier
An important aspect for model-based design and development as well as for process monitoring and control is the consideration of uncertain process parameters. One approach for the explicit consideration of such uncertainties is the formulation of Chance-Constrained optimization problems. Within the last years, several different methods for the efficient solution of these problems have been presented. In this work, chance constraints are evaluated following the idea of the variable mapping approach.

Because the efficiency of the original approach deteriorates with an increasing number of uncertain parameters, the probability integration has been extended recently to the exploitation of sparse grids. In this work, additional techniques for improving the efficiency of the variable mapping approach are presented. Firstly, the solution of a subproblem, the so called shooting task is analyzed in detail and enhanced through an idea called here result recycling. Secondly, possible extensions are presented which make use of second order derivative information. The new methods are verified by application to an industrially validated process model of a vacuum distillation column for the separation of multicomponent fatty acids.

Baran N, Wozny G, Arellano-Garcia H (2012) Model-based design of experiments for model identification using closed-loop set-point response, Computer Aided Chemical Engineering, vol.30 - proceedings of the 22nd European Symposium on Computer Aided Process Engineering (ESCAPE22) 30 pp. 1337-1341 Elsevier
In this work, a new approach to model identification based on model-based experimental design is presented. In the proposed strategy, system identification relies on a closed-loop set-point response. For this purpose, experiments are first exemplarily executed with a P-controller. Therefore, in this specific case only one design variable is considered that is represented by the controller gain. In order to validate our approach and demonstrate the benefits of the proposed strategy different scenarios are simulated.
del Rio-Chanona EA, Dechatiwongse P, Zhang D, Maitland GC, Hellgardt K, Arellano-Garcia H, Vassiliadis VS (2015) Optimal Operation Strategy for Biohydrogen Production, Industrial and Engineering Chemistry Research 54 (24) pp. 6334-6343 American Chemical Society
Hydrogen produced by microalgae is intensively researched as a potential alternative to conventional energy sources. Scaling-up of the process is still an open issue, and to this end, accurate dynamic modeling is very important. A challenge in the development of these highly nonlinear dynamic models is the estimation of the associated kinetic parameters. This work presents the estimation of the parameters of a revised Droop model for biohydrogen production by Cyanothece sp. ATCC 51142 in batch and fed-batch reactors. The latter reactor type results in an optimal control problem in which the influent concentration of nitrate is optimized which has never been considered previously. The kinetic model developed is demonstrated to predict experimental data to a high degree of accuracy. A key contribution of this work is the prediction that hydrogen productivity can achieve 3365 mL/L through an optimally controlled fed-batch process, corresponding to an increase of 116% over other recently published strategies.
Son NX, Arellano-Garcia H, Wozny G, Tran K (2012) Oxidative coupling of methane: a new process concept for the improvement of the downstream processing by using adsorption, Czasopismo Techniczne. Mechanika 109 (1-M) pp. 233-242 Interdisciplinary Centre for Mathematical and Computational Modelling
This paper, inspired by the success of adsorptive air separation in big scale (up to 250 tons/day), looks into the possibility of replacing cryogenic distillation with adsorptive separation, and thus improving the downstream processing of OCM. This results in a new process concept. For this purpose, a plug flow model of fixed-bed adsorber was developed and several separation schemes were investigated via simulation. Among them, the simultaneously separation of ethylene and carbon dioxide using zeolite 4A is found realizable. The results show that by switching from cryogenic distillation to adsorption, separation cost can be significantly reduced.
Günther R, Schöneberger JC, Arellano-Garcia H, Thielert H, Wozny G (2012) Design and modeling of a new periodical-steady state process for the oxidation of sulfur dioxide in the context of an emission free sulfuric acid plant, Computer Aided Chemical Engineering, vol.31 - 11th International Symposium on Process Systems Engineering 31 pp. 1677-1681 Elsevier
The oxidation of sulfur dioxide over vanadium pentoxide catalysts represents a basic step in the sulfuric acid production process. In conventional sulfuric acid plants the SO2 oxidation represents the limiting step with respect to the SO2 emissions. Due to the fact that the SO2 oxidation is an equilibrium reaction, sulfuric acid plants always have SO2 emissions. In this work, a new process concept is presented, which uses the transient behaviour of the reaction in two reactors operating under unsteady conditions (Saturated Metal Phase reactor). Besides several advantages, which can increase the efficiency of the whole sulfuric acid process drastically, the SMP Reactor is a key component for an efficient operation of a sulfuric acid plant which reduces the emissions down to zero while keeping the necessary conditions for the hydrogenation unit installed downstream. For this purpose, a mathematical model is used, which describes the dynamic effects of the SO2 oxidation. The model has been experimentally verified in a Miniplant, which works with commercial catalyst pellets.
Esche E, Arellano-Garcia H, Biegler LT, Wozny G (2012) Two-dimensional modeling of a packed-bed membrane reactor for the oxidative coupling of methane, Chemical Engineering Transactions 29 (August) pp. 1537-1542 The Italian Association of Chemical Engineering
Oxidative coupling of methane (OCM) represents an opportunity for the replacement of crude oil, which still is the main source for longer hydrocarbons and almost all base chemicals, with natural gas, or biogas. OCM turns methane catalytically into mostly ethylene and ethane. Thus, several different reactor types exist, out of which the packed-bed membrane reactor (PBMR) is one of the most promising given its combination of reaction and product separation in one apparatus and also the improved temperature control because of the gradual feeding of oxygen through the membrane.
In previous simulation and optimization studies, one-dimensional models have been used to describe the conventional PBMR. However, due to radial diffusion and thermal conduction those models are not accurate enough. In this work, a two-dimensional model for the CPBMR is presented. Radial diffusion and thermal conduction in the packed-bed as well as in the reactor shell are considered while axial dispersion is neglected. In accordance with experimental studies, Knudsen?s diffusivity theory is applied to describe the flux through the membrane. The model is discretized using a combination of Lagrangian and Hermite collocating polynomials on finite elements. The two-dimensional model contains second order derivatives for the radial coordinate. Hence, continuity of both the collocated variable and the first derivative across all finite elements are required in that direction. In this case, Hermite polynomials are advantageous because they allow for the afore-mentioned continuity while negating the necessity of additional equality constraints.
As an initial configuration, a length of 20 cm is assumed for the CPBMR with two separate heating/cooling segments of each 10 cm. The tube-side and shell-side diameters are set to 7 and 10 mm, respectively. Preliminary studies have shown that five radial and twelve axial finite elements are required to ensure a stable performance of all optimization studies for the given initial configuration. The resulting large-scale NLP contains more than 130,000 variables. Most fluid properties and transport parameters are implemented as functions of local temperatures and concentrations rather than average values. A brief study shows that their joint influence cannot be neglected. Using La2O3/CaO as a catalyst with kinetics provided by Stansch et al. (1997), an overestimation of more than 25 percentage points can be observed in the yield of C2 hydrocarbons in a one
Godini H, Jaso S, Martini W, Stuenkel S, Song S, Arellano-Garcia H, Wozny G (2012) Concurrent reactor engineering, separation enhancement and process intensification; comprehensive UniCat approach forOxidative Coupling of Methane (OCM), Czasopismo Techniczne. Mechanika 109 (1-M) pp. 63-74 Interdisciplinary Centre for Mathematical and Computational Modelling
For more than three decades Oxidative Coupling of Methane (OCM) process has been investigated as an attractive alternative for cracking technologies for ethylene production and exploiting the huge resources of natural gas. Developing a uitable catalyst and analyzing proper reactor feeding policy, reviewing and deploying the efficient methods in separation and purification of the undesired and desired products, possible energy saving and process intensification in each section, each has been the subject of many researches in the past. In this paper, these aspects will be addressed simultaneously in a general overview of the main research activities performed in the chair of process dynamics and operation at Berlin Institute of Technology under the context of Unifying Concepts in Catalysis (UniCat) project. Moreover, a cost estimation of the industrial scale OCM process guiding the analysis method to address the potentials and disadvantageous of each OCM scenario structure, highlighted the possible process intensifications potentials in case of energy and equipment.
Hoang MD, Barz T, Merchan V, Biegler LT, Arellano-Garcia H (2013) Simultaneous solution approach to model-based experimental design, AIChE Journal 59 (11) pp. 4006-4451 American Institute of Chemical Engineers
A model-based experimental design is formulated and solved as a large-scale NLP problem. The key idea of the proposed approach is the extension of model equations with sensitivity equations forming an extended sensitivities-state equation system. The resulting system is then totally discretized and simultaneously solved as constraints of the NLP problem. Thereby, higher derivatives of the parameter sensitivities with respect to the control variables are directly calculated and exact. This is an advantage in comparison with proposed sequential approaches to model-based experimental design so far, where these derivatives have to be additionally integrated throughout the optimization steps. This can end up in a high-computational load especially for systems with many control variables. Furthermore, an advanced sampling strategy is proposed which combines the strength of the optimal sampling design and the variation of the collocation element lengths while fully using the entire optimization space of the simultaneous formulation.
Lopez C. DC, Hoyos LJ, Mahecha CA, Arellano-Garcia H, Wozny G (2013) Optimization Model of Crude Oil Distillation Units for Optimal Crude Oil Blending and Operating Conditions, Industrial and Engineering Chemistry Research 52 (36) pp. 12673-13232 American Chemical Society
This work presents the mathematical formulation of a nonlinear programming (NLP) model which optimizes simultaneously crude oil blending and operating conditions for a system of several crude oil distillation units (CDUs) at a Colombian refinery. The CDU system consists of three industrial units processing a blending of five extra-heavy crude oils and producing two commercial fuels, Jet-1A and Diesel. The NLP model involves typical restrictions (e.g., flow rate according to capacity of pumps, distillation columns, etc.) and the heat integration of streams from atmospheric distillation towers (ADTs) and vacuum distillation towers (VDTs) with the heat exchanger networks for crude oil preheating. A metamodeling approach is used so as to represent the ADTs. Preheating networks are modeled with mass, energy balances, and design equations of each heat exchanger. The NLP model has been implemented in GAMS using CONOPT as solver. Different cases are solved by the NLP model such that the optimal case with less profit increment had an economical benefit of 13% with respect to its case without optimization. In each optimal case the extra-heavy crude oils in the feed blending of each CDU required more severe operating conditions such as higher temperature of the crude oil at the entrance to the towers, greater flow rate of stripping steam at the bottom, and minor pressure of the tower tops.
Pastor-Pérez L, Baibars F, Le Sache E, Arellano-Garcia H, Gu S, Ramirez Reina T (2017) CO2 valorisation via Reverse Water-Gas Shift reaction using advanced Cs doped Fe-Cu/Al2O3 catalysts, Journal of CO2 Utilization 21 pp. 423-428 Elsevier
This paper evidences the viability of chemical recycling of CO2 via reverse water-gas shift reaction using advanced heterogeneous catalysts. In particular, we have developed a multicomponent Fe-Cu-Cs/Al2O3 catalyst able to reach high levels of CO2 conversions and complete selectivity to CO at various reaction conditions (temperature and space velocities). In addition, to the excellent activity, the novel-Cs doped catalyst is fairly stable for continuous operation which suggests its viability for deeper studies in the reverse water-gas shift reaction. The catalytic activity and selectivity of this new material have been carefully compared to that of Fe/Al2O3, Fe-Cu/Al2O3 and Fe-Cs/Al2O3 in order to understand each active component?s contribution to the catalyst?s performance. This comparison provides some clues to explain the superiority of the multicomponent Fe-Cu-Cs/Al2O3 catalyst
Le Saché E, Peng Y, Arellano-Garcia H, Ramirez Reina T (2017) Model-Based Analysis and Integration of Synthetic Methane Production and Methane Oxidative Coupling, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 Elsevier
Ethylene is the world?s largest commodity chemical and a fundamental building block molecule in the chemical industry. Oxidative coupling of methane (OCM) is considered a promising route to obtain ethylene due to the potential of natural gas as a relatively economical feedstock. In a recent work, this route has been integrated by Godini et al (2013) with methane dry reforming (DRM) in a dual membrane reactor, allowing an improved thermal performance.
In this work, we have explored a more ambitious integrated system by coupling the production of methane and carbon dioxide via coal gasification with the DRMOCM unit. Briefly, our process utilises coal to generate value-added methane and ethylene. In addition, CO2 management is achieved through CO2 methanation and dry methane reforming. Potential mass and energy integration between two systems is proposed as well as the optimum conditions for synthetic natural gas production. The upstream gasification process is modelled to determine the influence of temperature, pressure, and feed composition in the methane yield. The results suggest that the key variables are temperature and hydrogen concentration, as both parameters significantly affect the methane and CO2 levels in the linking stream. This study reports for the first time the linking stream between the two systems with a high methane concentration and the appropriate amount of CO2 for downstream processing.
Arellano-Garcia H, Ketabchi E, Ramirez Reina T (2017) Integration of Bio-refinery Concepts in Oil Refineries, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 pp. 829-834 Elsevier
In this work, the systematic integration of bio-refineries within oil refineries is considered. This is particularly relevant due to the lack of adaptation of existing refineries to diminishing oil supply. Moreover, the integration of oil and bio-refineries has a massively positive effect on the reduction of CO2 emissions. For instance, the biodiesel produced in bio-refineries could be integrated with conventional oil refinery processes to produce fuel, thusly reducing the dependence on crude oil. This represents a suitable alternative for increasing profit margins while being increasingly environmentally friendly. The identified possible routes of integration will be discussed in this contribution. For this purpose, the different proposed alternatives and their configurations were simulated and analysed. The developed models simulated key integrations e.g. a gasification unit that is fed from pyrolysis oil, biodiesel, and refinery residue, before being combined into one system involving all three. Varying forms of synthesis for these three feeds were also considered, focusing on novel techniques as well as environmentally friendly options that made use of waste products from other processes. The simulations revealed valuable gas stream rich in H2, with some CO2 and with a slight excess of CO resulting from the gasification unit. Further upgrading of these products was achieved by coupling the gasifier with a water gas shift (WGS) unit. This allowed a fine tune of the H2:CO ratio in the gas stream which can be further processed to obtain liquid hydrocarbons via Fischer-Tropsch (FT) synthesis or alternatively, clean hydrogen for fuel cells applications.
Arellano-Garcia H, Isaule F, Rios Huguet A (2017) Di-nucleon structures in homogeneous nuclear matter based on two- and three-nucleon interactions, EUROPEAN PHYSICAL JOURNAL A 52 (299) SPRINGER
We investigate homogeneous nuclear matter within the Brueckner-Hartree-Fock (BHF) approach in the limits of isospin-symmetric nuclear matter (SNM) as well as pure neutron matter at zero temperature. The study is based on realistic representations of the internucleon interaction as given by Argonne v18, Paris, Nijmegen I and II potentials, in addition to chiral N3LO interactions, including three-nucleon forces up to N2LO. Particular attention is paid to the presence of di-nucleon bound states structures in 1S0 and 3SD1 channels, whose explicit account becomes crucial for the stability of self-consistent solutions at low densities. A characterization of these solutions and associated bound states is discussed. We confirm that coexisting BHF single-particle solutions in SNM, at Fermi momenta in the range 0.13 ? 0.3 fm?1 , is a robust feature under the choice of realistic internucleon potentials.
Bürger P, Flores-Alsina X, Arellano-Garcia H, Gernaey K (2017) Improving the Prediction of Phosphate Dynamics in Biotechnological Processes: A Case Study Based on Antibiotic Production Using Streptomyces coelicolor, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 40C pp. 2869-2874 Elsevier Science Ltd (Hersteller)
The objective of this study is to demonstrate that the accurate mathematical description of phosphate dynamics requires a considerable, but unavoidable, degree of complexity when modelling biotechnological systems. As an example, a model predicting antibiotic production using Streptomyces coelicolor is chosen which had difficulties explaining the phosphate dynamics. The model is enhanced by the implementation of an advanced speciation model and a multiple mineral precipitation framework. Furthermore, a model describing intracellular polyphosphate accumulation and consumption is developed and implemented. Based on the conducted work the improved process model is capable of predicting the phosphate dynamics (RMSEd 52h: -90 %, RADd 52h: -96 %) very accurately in comparison to the original implementation, where biomass growth was the only phosphate sink. The description of most other variables was improved by a knowledge-based re-estimation of selected parameters as well. This work contributes to the existing process knowledge of biotechnological systems in general and especially to the antibiotic production with S. coelicolor, which emphasizes the necessity of combining physico-chemical and biological processes to accurately describe phosphate dynamics.
Arellano-Garcia H, Ife M, Sanduk M (2017) Solar Hydrogen Production via Aqueous Methanol Electrolysis, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 40C pp. 2533-2538 Elsevier Science Ltd (Hersteller)
Despite having very clean combustion properties, the majority of hydrogen produced today still comes from fossil fuels. As such, there is a demand for renewably produced hydrogen, such as solar powered electrolysis, so that the hydrogen produced retains its clean credentials. Unfortunately, this process is plagued by inefficiencies and requires improvement in order to economically compete with fossil fuels. This work investigates solar hydrogen production via aqueous methanol (MeOH) electrolysis in comparison to pure water electrolysis in a directly coupled solar-PEM electrolysis system. Experiments were completed to investigate the impact of changing the MeOH concentration, power supply, and load characteristics on electrolysis and solar-hydrogen efficiencies. Simulation studies were then performed to analyse thoroughly the experimental data so as to gain an understanding of the yields and economics of utility scale solar?hydrogen facilities.
Alkandari M, Mujtaba I, Arellano-Garcia H (2017) Model Based Analysis of a Petroleum Refinery Plant with Hydrotreating as a Pre-treatment Unit, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 40A pp. 835-840 Elsevier
Catalytic hydrotreating is one of the processes used intensively in the modern petroleum refining industry. It is series of reactions considered as a mature process that improves the quality of petroleum products and removes Sulphur and undesired impurities. This study aims to develop and enhance the performance of a whole petroleum refining plant, which follows the concept of crude oil hydrotreating (HDT). The study was carried out using Aspen HYSYS simulator building a model-based analysis for the refinery plant. Two refineries have been simulated separately; one with a crude oil hydrotreating and the other followed the conventional method. The comparison and analysis focused on enhancing the yield of middle distillates while reducing the total energy consumption and overall costs. Hydrodenitrogenation and Hydrodesulfurization were the two reactions that took place in the trickle bed reactor at 400 °C and 10 MPa. The hydrotreated crude oil enters then the atmospheric distillation column, where six main products were distilled (LPG, Light Naphtha, Heavy Naphtha, Kerosene and Residual crude). In the model-based analysis, the crude HDT process configuration was completed first using Kirkuk crude oil, and to confirm the significance of the study, Siberian crude was used as an alternative feedstock. Finally, the results confirmed that the crude oil hydrotreating method can be followed using different types of feedstock around the world.
Anagnostopoulos A, Campbell A, Arellano-Garcia H (2017) Modelling of the Thermal Performance of SGSP using COMSOL Multiphysics, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 40C pp. 2575-2560 Elsevier Science Ltd (Hersteller)
Novel renewable energy sources are necessary to counter the current environmental crisis. The largest source of renewable energy is the sun. One possible application of solar energy is the harvesting and storage of low temperature thermal heat ( The new models were compared with experimental data from two different test sites, concerning mainly the temperature at the lower convective zone (LCZ) and the upper convective zone (UCZ). The 3D model was proven to be the most accurate with the 1D model being the least. Furthermore, the general radiative heat transfer equation, with an isotropic scattering phase function, solved using the discrete ordinates method was proven to give a satisfactory accuracy in terms of radiation in semi-transparent media.
Stroud T, Smith T, Le Saché E, Santos J, Centeno M, Arellano-Garcia H, Odriozola J, Ramirez Reina T (2017) Chemical CO2 recycling via dry and bi reforming of methane using Ni-Sn/Al2O3 and Ni-Sn/CeO2-Al2O3 catalysts, Applied Catalysis B: Environmental 224 pp. 125-135 Elsevier
Carbon formation and sintering remain the main culprits regarding catalyst deactivation in the dry and bi-reforming of methane reactions (DRM and BRM, respectively). Nickel based catalysts (10 wt.%) supported on alumina (Al2O3) have shown no exception in this study, but can be improved by the addition of tin and ceria. The effect of two different Sn loadings on this base have been examined for the DRM reaction over 20 h, before selecting the most appropriate Sn/Ni ratio and promoting the alumina base with 20 wt.% of CeO2. This catalyst then underwent activity measurements over a range of temperatures and space velocities, before undergoing experimentation in BRM. It not only showed good levels of conversions for DRM, but exhibited stable conversions towards BRM, reaching an equilibrium H2/CO product ratio in the process. In fact, this work reveals how multicomponent Ni catalysts can be effectively utilised to produce flexible syngas streams from CO2/CH4 mixtures as an efficient route for CO2 utilisation.
Hoeser S, Arora S, Koitka M, Kleinert T, Kahrs O, Sebastia Saez J, Arellano-Garcia H (2017) Adaptation of control structure design methods to an industrial plant engineering workflow, Industrial & Engineering Chemistry Research 56 (48) pp. 14270-14281 American Chemical Society
Methods of systematic control structure design are adapted to suit industrial workflow of plant design and engineering in the chemical and process industry. The applied methods include a systematic step-wise design methodology and the concept of self-optimizing control. Implementation of these methods is performed in a commercial software framework that consists of Aspen Plus and MatLab. The control structure design methodology of an industrial sequence of heat-integrated distillation columns is presented as a case study.
Pastor Perez L, Le Saché E, Jones C, Gu S, Arellano-Garcia H, Ramirez Reina T (2017) Synthetic natural gas production from CO 2 over Ni-x/CeO 2 -ZrO 2 (x = Fe, Co) catalysts: Influence of promoters and space velocity, Catalysis Today Elsevier
Herein, the production of synthetic natural gas is proposed as an effective route for CO2 conversion. Typical catalysts for this reaction are based on Ni. In this study, we demonstrated that the addition of promoters such as iron and cobalt can greatly benefit the activity of standard Ni methanation catalysts. In particular cobalt seems to be a very efficient promoter. Our Co doped material is an outstanding catalysts for the CO2 methanation leading to high levels of CO2 conversion with selectivities close to 100%. Additionally, this catalyst is able to preserve excellent performance at relatively high space velocity which allows flexibility in the reactor design making easier the development of compact CO2 utilisation units. As an additional advantage, the Co-promoted catalysts is exceptionally stable conserving high levels of CO2 conversion under continuous operations in long terms runs.
Sebastia Saez J, Gu S, Konozsy L, Repke J, Arellano-Garcia H (2017) On the effect of the Froude number on the interface area of gravity-driven liquid rivulets, Chemical Engineering Research and Design 130 pp. 208-218 Elsevier
The morphology of gravity-driven rivulets affects the mass transfer performance
in gas separation processes, hence, the need for an improved knowledge on the
hydrodynamics of this
ow. It is well established that the interface area of
the rivulets is determined by the balance between inertia and surface tension,
i.e. the Weber number, which in light of the results presented here, are not
the only parameters involved, but also the inclination of the plate has an effect
on the balance of forces which determines the amount of gas-liquid interface
area. The analysis of the interface area in rivulet
ow demands, therefore, a
more complete physical explanation for packing design purposes. In this work,
we analyse the combined effect of both the inertia and the inclination of the
plate in the interface area of liquid rivulets using CFD and the Volume-of-Fluid
interface tracking method. As a result, we propose the use of the Froude number
to provide a more complete physical explanation on the interface area formation
of gravity-driven liquid rivulets.
Rahimsalehi A, Avignone-Rossa C, Arellano-Garcia H (2017) Experimental Work Towards the Improvement of a Kinetic Model for Acetone-Butanol-Ethanol Pathway, Proceedings of the 27th European Symposium on Computer Aided Process Engineering ? ESCAPE 27 40C pp. 2875-2880 Elsevier Science Ltd (Hersteller)
In recent years, the production of waste materials because of population growth is increasing. Accordingly, finding new methods to convert such materials into fuel are becoming more popular. The objective of this study is to determine the potential of dried distiller`s grains and soluble (DDGS), a by-product of bioethanol industry, to produce butanol using strains of Clostridium saccharoperbutylacetonicum (C.SCC). In addition, this research is intended to develop the fermentation kinetic by improving the bacterial growth and medium optimisation while enhancing the process parameters based on the experimental data. Therefore, to find the most optimum condition for DDGS as the growth medium, the crucial effect of pH and various DDGS media supplementation were identified. Consequently, after performing several experiments in batch serum bottles without agitation, it had been determined that the best condition for DDGS as the growth medium is supplementing the autoclaved DDGS medium with 10 % (v/v) sucrose solution while pH is adjusted to 6.5. Thus, when the supplemented DDGS medium was inoculated with 10 % (v/v) of Clostridium saccharoperbutylacetonicum, the butanol concentration improved to approximately 7.2 (g/L) while this amount for the non-supplemented DDGS medium was approximately 4.4 (g/L). However, under the same conditions for DDGS as the growth medium, the butanol concentration decrease to 0.22 (g/L) while agitation was involved in the batch bioreactor. Based on the experimental results obtained from various experiments of this research, it is concluded that Clostridium saccharoperbutylacetonicum microorganism can ferment sucrose and other carbon sources available in DDGS such as glucose. Moreover, to improve the butanol concentration using mathematical modeling and computer simulation in ongoing studies, the collected preliminary data of this experimental research could be used in the proposed kinetic model by Shinto et al. (2007).
le Saché E, Santos J, Smith T, Arellano-Garcia H, Odriozola J, Ramirez Reina T (2018) Multicomponent Ni-CeO2 Nanocatalysts for Syngas production from CO2/CH4 mixtures, Journal of CO2 Utilization 25 pp. 68-78 Elsevier
The dry reforming of methane with CO2 is a common route to transform CO2/CH4 mixtures into added value syngas. Ni based catalysts are highly active for this goal but suffer from deactivation, as such promoters need to be introduced to counteract this, and improve performance. In this study, mono- and bi-metallic formulations based on 10 wt.% Ni/CeO2-Al2O3 are explored and compared to a reference 10 wt.% Ni/³-Al2O3. The effect of Sn and Pt as promoters of Ni/CeO2-Al2O3 was also investigated. The formulation promoted with Sn looked especially promising, showing CO2 conversions stabilising at 65% after highs of 95%. Its increased performance is attributed to the additional dispersion Sn promotion causes. Changes in the reaction conditions (space velocity and temperature) cement this idea, with the Ni-Sn/CeAl material performing superiorly to the mono-metallic material, showing less deactivation. However, in the long run it is noted that the mono-metallic Ni/CeAl performs better. As such the application is key when deciding which catalyst to employ in the dry reforming process.
Bürger P, Flores Alsina X, Arellano-Garcia H, Gernaey K (2018) Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor, Industrial & Engineering Chemistry Research American Chemical Society

The multiplicity of physico-chemical and biological processes, where phosphorus is involved, makes their accurate prediction using current mathematical models in biotechnology quite a challenge. In this work, an antibiotic production model of Streptomyces coelicolor is chosen as a representative case study in which major difficulties arise in explaining the measured phosphate dynamics among some minor additional issues. Thus, the utilization of an advanced speciation model and a multiple mineral precipitation framework is proposed to improve phosphorus predictions. Furthermore, a kinetic approach describing intracellular polyphosphate accumulation and consumption has been developed and implemented. A heuristic re-estimation of selected parameters is carried out to improve overall model performance. The improved process model predicts phosphate dynamics (Root Mean Squared Error d52h: -90 %, Relative Average Deviation d52h: -96 %) very accurately in comparison to the original implementation, where biomass growth/decay was the only phosphorus source-sink. In addition, parameter re-estimation achieved an improved description of the available measurements for biomass, total ammonia, dissolved oxygen and actinorhodin concentrations.

This work contributes to the existing process knowledge of biotechnological systems in general and especially to antibiotic production with S. coelicolor, while emphasizing the (unavoidable) need of considering both physico-chemical and biological processes to accurately describe phosphorus dynamics.

Mechleri Evgenia, Arellano-Garcia Harvey (2018) A Mathematical Programming Approach to Optimal Design of Smart Distributed Energy Systems, 44 pp. 2521-2526 Elsevier
The UK is committed to reducing its greenhouse gas emissions by at least 80% by 2050, relative to 1990 levels. For this to happen, we need to transform the UK economy while ensuring secure, low-carbon energy supplies to 2050. The future electricity distribution system, known as smart grid, will integrate advanced digital meters, distribution automation, communication systems and distributed energy resources. There has been a lot of discussion about the importance of the Internet of Things (IoT) in future smart grids and smart cities stating that IoT offers many applications and can be used to integrate efficiency renewable energy sources in the smart grid by making the electricity grid more robust and scalable.
This study will focus on the development of an integrated IoT-Distributed energy systems (DES) model for the efficient energy management of a microgrid under the integration of the intermittent renewable energy resources. In this work, we expand the definition of flexible options to include demand and supply together with design and operation strategies using internet of things (IoT). Our framework brings weather data and sensor information into a virtual energy plant optimisation model that connects supplier and consumer to optimise potential flexibility gaps arising from supply and demand mismatch. The problem is posed as a hybrid mixed-integer linear programming (MILP) optimisation model combining flexibility analysis and optimal synthesis for integrating energy supply and demand, where environmental information is added to each stage. Finally, we combine traditional mathematical programming approaches such as flexibility analysis and optimal network synthesis and within a single optimisation framework combining IoT and urban DES.
Dorneanu Bogdan, Mechleri Evgenia, Arellano-Garcia Harvey (2018) Towards the cooperative-based control of chemical plants, 43 pp. 1087-1092 Elsevier
This contribution presents the proof of concept for a consensus-based approach for the design and assessment of control structures in chemical plants. The applicability of the proposed approach is demonstrated on an existing mini-plant. For this purpose, a reduced dynamic model that considers a simplified structure of the plant, consisting of feed preparation, reaction, and downstream processing, is used to assess the control structure of the mini-plant using the consensus algorithm. The reduced model is used to assess the control structure of the mini-plant reactor, considering the relevant operational and safety variables.
Ketabchi Elham, Mechleri Evgenia, Gu Sai, Arellano-Garcia Harvey (2018) Modelling and Optimisation Approach of an Integrated Oil Refinery and a Petrochemical Plant, 4 pp. 1081-1086 Elsevier
An optimised integration approach connecting a conventional oil refinery with an ethylene production plant is investigated. Using the intermediate materials produced as the connection between the two plants, the use of internally provided feedstocks and blending options removes, at least partially, the reliance on external sourcing. This is also beneficial in terms of increasing profit margins and quality for both production systems. Thus, a mathematical model has been developed and implemented in this work to model the oil refinery and the ethylene production plant while considering their integration as an MINLP problem with the aim of optimising the integrated plants. This work considers the optimisation of each plant individually and later the final integration by modelling the interconnection between the oil refinery and the ethylene production plant. Moreover, a case study using practical data was carried out to verify the feasibility of the integration for an industrial application.
Sebastia-Saez Daniel, Arellano-Garcia Harvey (2018) A model-based approach to design miniaturised structured packings for highly efficient mass transfer in gas/liquid multiphase flows, 43 pp. 821-826 Elsevier
Fractals are the evolutionary answer that Nature has developed to provide highly packed structures for mass and heat transfer. In this work, a computational fluid dynamics model will be presented to gain insight on the multiphase flow characteristics within fractal geometries. A substantial increment of the gas-liquid interface area with the fractal dimension of the particular geometry being tested is expected. This will allow the implementation of more compact designs, i.e. with greater specific area, than the conventional structured packings currently used for gas separation. More compact designs also mean less solvent used for the same gas absorption rate, reducing the heat duty of solvent regeneration. The next steps of this research will include the use of 3D printing techniques to reproduce fractal geometries to be tested in an experimental setup, and the study of the interaction between nature-inspired gas absorbers and the rest of the carbon emitting facility through process simulations.
Hajizeinalibioki Sahar, Sebastia-Saez Daniel, Klymenko Oleksiy, Arellano-Garcia Harvey (2018) Dull or bright you still get electric delight: A new approach to the design of all-weather panels, 43 pp. 211-216 Elsevier
Modern renewable energy sources have a great disadvantage of being intermittent. Harvesting solar energy directly using photovoltaic panels is one of the most promising renewable energy technologies. While this allows electricity generation during daytime when the sky is clear, at night there is no production at all and it is greatly diminished in cloudy or rainy conditions. Recently a concept of all-weather solar cells was proposed by Q. Tang et al. (Angew. Chem. Int. Ed. 55(17) (2016) 5243-5246) in which a solar panel was covered with a layer of graphene. This allows collecting energy from falling raindrops containing dissolved salts through charging and discharging of an electrical double layer at the water-graphene interface, which acts as a pseudocapacitor. Although this setup allows harvesting both direct solar radiation and some of the kinetic energy of falling rain drops, the output is low for realistic salt concentrations while the graphene layer diminishes the solar-to-electric conversion rate.
In this work, we propose a different approach to the same problem. Instead of relying on a sufficient concentration of salts in rain water, we propose to convert the mechanical energy delivered by drop impacts directly into electrical energy by supporting a thin-layer solar panel with an array of piezo crystals. The advantage of this setup is that the solar-to-electric performance of such a panel is not affected by the added piezoelectric support. However, only a fraction of the kinetic energy of the falling rain drops can be converted due to the energy dissipation within the material of the thin-layer panel. We have conducted detailed modelling of kinetic energy harvesting process from the drop impact and spreading to the dissipation of mechanical strain through the panel to the generation of piezoelectric potential. The results illustrate the viability of this concept, but they are still to be confirmed experimentally and require an economic feasibility analysis to be performed.