Editorial pubs.acs.org/IECR
Cite This: Ind. Eng. Chem. Res. 2018, 57, 9737−9739
Preface: European Symposium on Computer-Aided Process Engineering
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structure for renewable-to-chemicals network process synthesis, allowing a fast screening of many alternative configurations; Ibarra-Gonzalez et al.4 perform a systematic comprehensive analysis of biomass thermochemical conversion processes, including mass and energy integration opportunities; Said et al.5 address the chemical influence of heavy metals on thermochemical conversion of biomass; Graciano et al.6 analyze the scenarios where the production of liquid fuels from CO2-rich natural gas may be competitive; and Granjo et al.7 implement a systematic model-building strategy to determine glyceride transesterification kinetics, which is a crucial step in biodiesel production from vegetable oils. Another major set of contributions involve the development of improved models and the application of proper optimization techniques to enhance sustainability in the processes industry. Along this line, the work by Castillo-Landero et al.8 proposes a systematic approach for process intensification (tasks integration into fewer pieces of equipment), considering sustainability metrics. Focusing on specific situations, the work by Aeowjaroenlap et al. 9 addresses the development and implementation of a rigorous model representing the reactions involved in the acetylene hydrogenation, leading to significant improvements in steam cracking economics and process ́ performance; Ledezma-Martinez et al.10 exploit the interactions between separation and heat recovery tasks in crude-oil distillation systems to reduce the requirements of utilities; Bü rger et al.11 develop an improved model to predict phosphorus dynamics in biotechnological systems, accounting for both physicochemical and biological processes; Zhou et al.12 address the waste treatment and recovery in the nylon production processes; and Chen and Jobson13 study the design, operation, and optimization of solvent extraction flowsheets, using ionic liquids for the selective separation of metals from solutions. The specific requirements of the pharmaceuticals sector deserved special attention in the ESCAPE-27 program, as in the works of Montes at al.,14 who analyze ways to improve plant design and operation to reduce the effects of uncertainties and disturbances over the specifications of the active pharmaceutical ingredients; and Sugiyama et al.,15 who refer to the requirements for solid drug manufacturing usually found in the pharmaceuticals sector to propose a decision support method for the choice between batch and continuous technologies. The application of suitable and efficient strategies and procedures for the design and operation of water and energy supply networks is also a major concern for the PSE community: Araya et al.16 develop a mathematical programming approach to address the design of water distribution networks, including desalination plants, considering top-
he European Symposium on Computer-Aided Process Engineering (ESCAPE) was introduced as a regular event in the agenda of the Process Systems Engineering (PSE) community in 1992, when the series started with the aim of consolidating the pioneering conferences that had been promoted by the CAPE Working Party of the European Federation of Chemical Engineering since 1968. Nowadays, ESCAPE is a highly recognized yearly event bringing together scientists, industrial experts, academics, and students, all active in the research, development and application of PSE concepts, methods, and tools. The 27th Edition of ESCAPE, held in Barcelona, Spain, Oct. 1−5, 2017, became an especially relevant platform to disseminate the most recent CAPE/PSE contributions across the Chemical Engineering academic and industrial communities, since it took place within the framework of a large gathering of events, including the 10th World Congress of Chemical Engineering and many other specialized Symposiums and Workshops. These events attracted more than 3300 delegates from all over the world, and more than 650 of them directly attended and contributed to the dedicated ESCAPE-27 sessions. ESCAPE-27 shared with all these events a common motivation: addressing the global sustainability challenges identified by the United Nations and many other institutions. These challenges deal with energy, water, health and wellness, and food and nutrition as key elements requiring engineering solutions to enable sufficient and efficient supply of resources for a growing world population. The commitment of the chemical and biochemical engineering community to address them was ratified in the Declaration of Barcelona,1 which was signed at the end of the conference. Accordingly, ESCAPE-27 included a specific topic on CAPE applications dealing with these challenges; however, many other ESCAPE-27 contributions also show how CAPE/PSE concepts, methods, and tools offer a unique approach to systematically address current concerns on sustainability, energy efficiency, water management, etc. The purpose of this ESCAPE-27 special issue, which Industrial & Engineering Chemistry Research (IECR) of the American Chemical Society kindly agreed to publish, is to reflect this capability, through the compilation of 25 invited full-length contributions in the areas of carbon cycle management, sustainability of chemical processes, design and operation of water and energy supply networks, development of CAPE methods and tools, process monitoring and control, and decision making under conflicting objectives. Along this line, a significant number of contributions to this special issue focus on the management of the carbon cycle and the biomass exploitation through the application of PSE approaches to process modeling, synthesis, design, and operation: Panteli et al.2 show the advantages of applying an integrated approach to the synthesis, design, and planning of biorefining supply chains; Shack et al.3 propose a super© 2018 American Chemical Society
Special Issue: 2017 European Symposium on Computer-Aided Process Engineering Published: August 1, 2018 9737
DOI: 10.1021/acs.iecr.8b03116 Ind. Eng. Chem. Res. 2018, 57, 9737−9739
Industrial & Engineering Chemistry Research
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ography requirements and energy integration opportunities; Koltsaklis and Georgiadis17 address the sustainable design and operation of energy generation and transport systems, also proposing the use of mathematical programming models; and Pavão et al.18 present several optimization models for HEN synthesis under uncertainty, managing financial risk. The development and improvement of methods and tools able to address ever more complex process scenarios is, by definition, an ongoing topic for the CAPE community. The work by Huang et al.19 discusses the problem of model identification under uncertainty that appears when the molecular and/or particle interactions in chemical reaction processes must be described. Two works in this special issue address the management of dynamic systems, including batch and semibatch processes, quite usual in the biopharmaceuticals industry, and propose applicable optimization strategies for them: Aydin et al.20 proposes the combination of the indirect solution scheme with a parsimonious input parametrization, and Kappatou et al.21 report reductions in the computational load through the application of model structure reformulation strategies (function smoothening, model size reduction, and scaling). Petsagkourakis et al.22 also propose the use of model reduction strategies to address the optimization of complex large-scale steady-state systems involving nonlinear inequality constraints. Process monitoring and control to ensure process sustainability, safety, and product quality is also a recurrent concern for process systems engineers: Rato and Reis23 propose a way to improve the soft-sensing effectiveness through the adoption of the best granularity for each predicted variable; Yan and Yao24 present improved methods for fault isolation, facilitating the subsequent root-cause diagnosis. Finally, sustainability studies require the evaluation of a wide range of indicators, which usually will not drive the solutions in the same direction, and this motivates a great deal of research into more comprehensive procedures for decision making under conflicting objectives: Capra et al.25 introduce improvements in the derivative-free multilevel coordinate search procedure, and apply them to an adsorption black-box model; Limleamthong et al.26 propose the improvement of the discrimination capacity of Data Envelopment Analysis methods for final decision-making in multiobjective scenarios through metrics reduction with minimum information loss. These specific contributions and the topics they represent are just a sample of the rich and diverse research and engineering work currently ongoing in the area of CAPE/PSE. These works were invited after being selected by the ESCAPE27 International Scientific Committee from the nearly 500 ESCAPE-27 contributions, covering the full scope of the conference: CAPE concepts, methods and tools; CAPE/PSE education and training; integrated and holistic decision support; modeling and simulation; synthesis and design; planning and scheduling; process monitoring and control; and CAPE applications (with special emphasis on energy systems, carbon mitigation, water management, health care, medicine and pharma systems engineering, urban process and systems, and bioengineering, biomedical and biotechnology applications). All the original contributions to ESCAPE-27 may be found in volume 40 of the Computer-Aided Process Engineering Book Series.27
Editorial
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
Views expressed in this editorial are those of the author and not necessarily the views of the ACS.
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ACKNOWLEDGMENTS This Special Issue would not have been possible without the extraordinary support received from the ESCAPE-27 International Scientific Committee and IECR reviewers.
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REFERENCES
(1) Barcelona Declaration−10th World Congress of Chemical Engineering, 1−5 October 2017. Chem. Eng. Res. Des. 2018, 129, A1− A2. (2) Panteli, A.; Giarola, S.; Shah, N. Supply Chain MILP Model Integrating Biorefining Technology Superstructure. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05228. (3) Schack, D.; Rihko-Struckmann, L.; Sundmacher, K. A linear Programming Approach for Structure Optimization of Renewable-toChemicals (R2Chem) Production Networks. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05305. (4) Ibarra-Gonzalez, P.; Rong, B.-G. Systematic Synthesis and Evaluation of Thermochemical Conversion Processes for Lignocellulosic Biofuels Production: Total Process Evaluation and Integration. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05382. (5) Said, M.; Cassayre, L.; Dirion, J.-L.; Joulia, X.; Nzihou, A. Influence of Nickel on Biomass Pyro-Gasification: Coupled Thermodynamic and Experimental Investigations. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05201. (6) Graciano, J. E. A.; Chachuat, B.; Alves, R. M. B. Conversion of CO2-Rich Natural Gas to Liquid Transportation Fuels via Trireforming and Fischer−Tropsch Synthesis: Model-Based Assessment. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.8b00135. (7) Granjo, J. F. O.; Duarte, B. P. M.; Oliveira, N. M. C. Systematic Development of Kinetic Models for the Glyceride Transesterification Reaction via Alkaline Catalysis. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05328. (8) Castillo-Landero, A.; Jiménez-Gutiérrez, A.; Gani, R. An Intensification Methodology to Minimize the Number of Pieces of Equipment and Its Application to a Process to Produce Dioxolane Products. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05229. (9) Aeowjaroenlap, H.; Chotiwiriyakun, K.; Tiensai, N.; Tanthapanichakoon, W.; Spatenka, S.; Cano, A. Model-Based Optimization of an Acetylene Hydrogenation Reactor To Improve Overall Ethylene Plant Economics. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05234. (10) Ledezma-Martínez, M.; Jobson, M.; Smith, R. SimulationOptimization-Based Design of Crude Oil Distillation Systems with Preflash Units. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/ acs.iecr.7b05252. (11) Bürger, P.; Flores-Alsina, X.; Arellano-Garcia, H.; Gernaey, K. V. Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05249. (12) Zhou, H.; Cai, Y.; You, F. Systems Design, Modeling, and Thermo-Economic Analysis of Azeotropic Distillation Processes for Organic Waste Treatment and Recovery in Nylon Plants. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.8b00275. (13) Chen, H.; Jobson, M.; Masters, A. J.; Gonzalez-Miquel, M.; Halstead, S. Flowsheet Simulation of Cobalt-Nickel Separation by Solvent Extraction with Trihexyl(tetradecyl)phosphonium Chloride. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05254. (14) Montes, F. C. C.; Gernaey, K.; Sin, G. Dynamic Plantwide Modeling, Uncertainty and Sensitivity Analysis of a Pharmaceutical
Antonio Espuñ a*
Universitat Politecnica de Catalunya, Spain 9738
DOI: 10.1021/acs.iecr.8b03116 Ind. Eng. Chem. Res. 2018, 57, 9737−9739
Industrial & Engineering Chemistry Research
Editorial
Upstream Synthesis: Ibuprofen Case Study. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.8b00465. (15) Matsunami, K.; Miyano, T.; Arai, H.; Nakagawa, H.; Hirao, M.; Sugiyama, H. Decision Support Method for the Choice between Batch and Continuous Technologies in Solid Drug Product Manufacturing. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/ acs.iecr.7b05230. (16) Araya, N.; Cisternas, F. A.; Lucay, L. A.; Gálvez, E. D. Design of Desalinated Water Distribution Networks: Complex Topography, Energy Production, And Parallel Pipelines. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05247. (17) Elekidis, A. P.; Koltsaklis, N. E.; Georgiadis, M. C. An Optimization Approach for the Assessment of the Impact of Transmission Capacity on Electricity Trade and Power Systems Planning. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05159. (18) Pavão, L. V.; Pozo, C.; Jiménez, L.; Costa, C. B. B.; Ravagnani, M. A. S. S. Financial Risk Management in Heat Exchanger Networks Considering Multiple Utility Sources with Uncertain Costs. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05251. (19) Huang, C.; Piccione, P. M.; Cattani, F.; Galvanin, F. Travelling Traders’ Exchange Problem: Stochastic Modelling Framework and Two-Layer Model Identification Strategy. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.8b00338. (20) Aydin, E.; Bonvin, D.; Sundmacher, K. Toward Fast Dynamic Optimization: An Indirect Algorithm That Uses Parsimonious Input Parameterization. Ind. Eng. Chem. Res.2018, DOI: 10.1021/acs.iecr.8b02109. (21) Kappatou, C. D.; Mhamdi, A.; Campano, A. Q.; Mantalaris, A.; Mitsos, A. Model-Based Dynamic Optimization of Monoclonal Antibodies Production in Semi-Batch OperationUse of Reformulation Techniques. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/ acs.iecr.7b05357 (22) Petsagkourakis, P.; Bonis, I.; Theodoropoulos, C. Reduced Order Optimization of Large-Scale Nonlinear Systems with Nonlinear Inequality Constraints Using Steady State Simulators. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.8b00033. (23) Rato, T. J.; Reis, M. S. Building Optimal Multiresolution Soft Sensors for Continuous Processes. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b04623. (24) Yan, Z.; Yao, Y.; Huang, T.-B.; Wong, Y.-S. ReconstructionBased Multivariate Process Fault Isolation Using Bayesian Lasso. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05189. (25) Capra, F.; Gazzani, M.; Joss, L.; Mazzotti, M.; Martelli, E. MOMCS, a Derivative-Free Algorithm for the Multiobjective Optimization of Adsorption Processes. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.8b00207. (26) Limleamthong, P.; Guillén-Gosálbez, G. Mixed-Integer Programming Approach for Dimensionality Reduction in Data Envelopment Analysis: Application to the Sustainability Assessment of Technologies and Solvents. Ind. Eng. Chem. Res. 2018, DOI: 10.1021/acs.iecr.7b05284. (27) Espuña, A., Graells, M., Puigjaner, L., Eds. 27th European Symposium on Computer Aided Process Engineering; Computer-Aided Chemical Engineering, Vol. 40; Elsevier: Amsterdam, 2017 (ISBN 978-0-444-63965-3).
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DOI: 10.1021/acs.iecr.8b03116 Ind. Eng. Chem. Res. 2018, 57, 9737−9739
