This item is printed on demand - Print on Demand Titel. Neuware -This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers.In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.

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T�tulo: Integrated Process Design and Operational Optimization via Multiparametric Programming
Editor: Springer, Springer Sep 2020
Fecha de publicaci�n: 2020
Idioma: Ingl�s
ISBN 10: 3031009614
ISBN 13: 9783031009617
Encuadernaci�n: Taschenbuch
Estado: Neu
Dimensiones: 235�mil�metros de ancho por 191 de alto por 15 de largo
Peso: 492 gramos

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Sinopsis

This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers.

In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.

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Baris Burnak is a Ph.D. candidate in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. He has worked under the supervision of Prof. Pistikopoulos for five years with a focus on developing a theoretical basis to simultaneously address design and operational receding horizon decisions in process systems. He earned his Bachelor’s and M.Sc. degrees from the Department of Chemical Engineering at Bogazici University, Turkey. Here, he started his research career studying the Fischer-Tropsch synthesis with data-driven modeling and optimization techniques. He has co-authored 11 peer reviewed journal articles and 6 conference proceedings.Dr. Nikolaos A. Diangelakis is an Optimization Specialist at Octeract Ltd. in London, UK, a massively parallel global optimization software firm. He was a postdoctoral research associate at Texas A&M University and Texas A&M Energy Institute. He holds a Ph.D. and M.Sc. on Advanced Chemical Engineering from Imperial College London and has been a member of the “Multiparametric Optimization and Control Group” since late 2011. He earned his Bachelor’s degree in 2011 from the National Technical University of Athens (NTUA). His main research interests are on the area of optimal receding horizon strategies for chemical and energy processes while simultaneously optimizing their design. For that purpose, Nikos is investigating novel solution methods for classes of non-linear, robust and multiparametric optimization programming problems. He is the main developer of the PARametric Optimization and Control (PAROC) platform and co-developer of the Parametric OPtimization (POP) toolbox. In 2016, Nikos was chosen as one of five participants in the “Distinguished Junior Re- searcher Seminars” in Northwestern University, organized by Prof. Fengqi You. In 2017, he received third place in EFCE’s “Excellence Award in Recognition of Outstanding Ph.D. Thesis on CAPE.” He is the coauthor of 16 peer reviewed articles, 11conference papers, and 3 book chapters.Professor Efstratios N. Pistikopoulos is the Director of the Texas A&M Energy Institute and a TEES Eminent Professor in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. He was a Professor of Chemical Engineering at Imperial College London, UK (1991–2015) and the Director of its Centre for Process Systems Engineering (2002–2009). He holds a Ph.D. degree from Carnegie Mellon University and he worked with Shell Chemicals in Amsterdam before joining Imperial. He has authored or co-authored over 500 major research publications in the areas of modeling, control and optimization of process, energy and systems engineering applications, 15 books, and 3 patents. He is a co-founder of Process Systems Enterprise (PSE) Ltd, a Fellow of AIChE and IChemE, a past Chair of the Computing and Systems Technology (CAST) Division of AIChE, and the current Editor-in-Chief of Computers & Chemical Engineering. In 2007,Prof. Pistikopoulos was a co-recipient of the prestigious MacRobert Award from the Royal Academy of Engineering; in 2012, the recipient of the Computing in Chemical Engineering Award of CAST/AIChE; in 2020, he was awarded the Sargent Medal from the Institution of Chemical Engineers (IChemE). He received the title of Doctor Honoris Causa from the University Politehnica of Bucharest in 2014, and from the University of Pannonia in 2015. In 2013, he was elected Fellow of the Royal Academy of Engineering in the UK.

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