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020 _a9783031020896
_9978-3-031-02089-6
024 7 _a10.1007/978-3-031-02089-6
_2doi
050 4 _aTA174
072 7 _aTBD
_2bicssc
072 7 _aTEC016000
_2bisacsh
072 7 _aTBD
_2thema
082 0 4 _a620.0042
_223
100 1 _aBurnak, Baris.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987767
245 1 0 _aIntegrated Process Design and Operational Optimization via Multiparametric Programming
_h[electronic resource] /
_cby Baris Burnak, Nikolaos A. Diangelakis, Efstratios N. Pistikopoulos.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXV, 242 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Engineering, Science, and Technology,
_x2690-0327
505 0 _aAcknowledgments -- An Introduction to the Grand Unification of Process Design and Operational Optimization -- Mixed-Integer Dynamic Optimization for Simultaneous Process Design and Control -- PAROC: PARametric Optimization and Control Framework -- Integrating Process Design Optimization and Advanced Model-Based Control Strategies -- Process Scheduling and Control via Multiparametric Programming -- Simultaneous Process Design, Scheduling, and Advanced Model-Based Control -- Bibliography -- Authors' Biographies.
520 _aThis 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.
650 0 _aEngineering design.
_93802
650 0 _aMaterials.
_97549
650 0 _aProfessional education.
_941513
650 0 _aVocational education.
_941514
650 1 4 _aEngineering Design.
_93802
650 2 4 _aMaterials Engineering.
_932311
650 2 4 _aProfessional and Vocational Education.
_941516
700 1 _aDiangelakis, Nikolaos A.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987772
700 1 _aPistikopoulos, Efstratios N.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_94257
710 2 _aSpringerLink (Online service)
_987774
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031001611
776 0 8 _iPrinted edition:
_z9783031009617
776 0 8 _iPrinted edition:
_z9783031032172
830 0 _aSynthesis Lectures on Engineering, Science, and Technology,
_x2690-0327
_987776
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02089-6
912 _aZDB-2-SXSC
942 _cEBK
999 _c86147
_d86147