Idioma: Inglés
Publicado por World Scientific Publishing Comp, 2012
ISBN 10: 9814271950 ISBN 13: 9789814271950
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Idioma: Inglés
Publicado por John Wiley & Sons Mai 2026, 2026
ISBN 10: 1394205570 ISBN 13: 9781394205578
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Añadir al carritoBuch. Condición: Neu. Neuware - Presents a systematic review of optimizing sustainable process systems through multiscale modeling and uncertainty analysis.
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Idioma: Inglés
Publicado por World Scientific Publishing Company, 2012
ISBN 10: 9814271950 ISBN 13: 9789814271950
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Publicado por LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6209974066 ISBN 13: 9786209974069
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Añadir al carritoTaschenbuch. Condición: Neu. Design and Analysis of a Bio-CNG (Compressed Biogas) Plant | Process Design, Optimization, and Performance Evaluation of Sustainable Bio-CNG Systems | Bishal Dey (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209974069 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por John Wiley & Sons Inc, New York, 2026
ISBN 10: 1394205570 ISBN 13: 9781394205578
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Añadir al carritoHardcover. Condición: new. Hardcover. Presents a systematic review of optimizing sustainable process systems through multiscale modeling and uncertainty analysis The global pursuit of net-zero carbon emissions has created an urgent need for chemical engineers and energy researchers to design systems that are both sustainable and resilient. While renewable energy sources such as solar and wind offer great potential, their variability introduces significant challenges that must be addressed through advanced optimization techniques. Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties connects optimization fundamentals with their applications in sustainable energy systems with a particular emphasis on the challenges posed by uncertainty. Divided into two parts, the book first introduces the core mathematical frameworks and methods needed to model and optimize uncertain systems, including stochastic programming, robust optimization, reinforcement learning, and multiscale algorithms. The authors clearly explain these state-of-the-art tools with attention to both theory and computational practice. The second part shifts to applications, demonstrating how these techniques are applied in real-world contexts such as renewable-based hydrogen, methanol, and ammonia production; carbon capture; shale gas systems; biomass integration; and power system optimization. Throughout the text, the authors emphasize the integration of renewables with chemical industries while highlighting strategies to manage variability, strengthen supply chains, and improve system-wide efficiency. Combining rigorous fundamentals with cutting-edge applications through a tutorial-style approach, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties: Provides the foundation and tools needed to design resilient, optimized, and sustainable energy systems Addresses optimization methods under uncertainty tailored to energy and process systems Presents a unified treatment of stochastic programming, robust optimization, and reinforcement learning techniques Integrates renewable-based systems with chemical industry supply chain design and operation Addresses computational challenges in large-scale optimization of energy systems Both a theoretical resource and a practical guide for applied problem-solving, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties is ideal for graduate-level courses in chemical engineering, process systems engineering, energy systems optimization, and operations research. It is also a valuable reference for industrial researchers, system modelers, and developers working on sustainable process design and energy transition strategies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por John Wiley & Sons Inc, New York, 2026
ISBN 10: 1394205570 ISBN 13: 9781394205578
Librería: CitiRetail, Stevenage, Reino Unido
EUR 158,71
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Añadir al carritoHardcover. Condición: new. Hardcover. Presents a systematic review of optimizing sustainable process systems through multiscale modeling and uncertainty analysis The global pursuit of net-zero carbon emissions has created an urgent need for chemical engineers and energy researchers to design systems that are both sustainable and resilient. While renewable energy sources such as solar and wind offer great potential, their variability introduces significant challenges that must be addressed through advanced optimization techniques. Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties connects optimization fundamentals with their applications in sustainable energy systems with a particular emphasis on the challenges posed by uncertainty. Divided into two parts, the book first introduces the core mathematical frameworks and methods needed to model and optimize uncertain systems, including stochastic programming, robust optimization, reinforcement learning, and multiscale algorithms. The authors clearly explain these state-of-the-art tools with attention to both theory and computational practice. The second part shifts to applications, demonstrating how these techniques are applied in real-world contexts such as renewable-based hydrogen, methanol, and ammonia production; carbon capture; shale gas systems; biomass integration; and power system optimization. Throughout the text, the authors emphasize the integration of renewables with chemical industries while highlighting strategies to manage variability, strengthen supply chains, and improve system-wide efficiency. Combining rigorous fundamentals with cutting-edge applications through a tutorial-style approach, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties: Provides the foundation and tools needed to design resilient, optimized, and sustainable energy systems.Addresses optimization methods under uncertainty tailored to energy and process systemsPresents a unified treatment of stochastic programming, robust optimization, and reinforcement learning techniquesIntegrates renewable-based systems with chemical industry supply chain design and operationAddresses computational challenges in large-scale optimization of energy systems Both a theoretical resource and a practical guide for applied problem-solving, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties is ideal for graduate-level courses in chemical engineering, process systems engineering, energy systems optimization, and operations research. It is also a valuable reference for industrial researchers, system modelers, and developers working on sustainable process design and energy transition strategies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 400 pages. 6.00x0.88x9.00 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por John Wiley & Sons Inc, New York, 2026
ISBN 10: 1394205570 ISBN 13: 9781394205578
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 256,25
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Añadir al carritoHardcover. Condición: new. Hardcover. Presents a systematic review of optimizing sustainable process systems through multiscale modeling and uncertainty analysis The global pursuit of net-zero carbon emissions has created an urgent need for chemical engineers and energy researchers to design systems that are both sustainable and resilient. While renewable energy sources such as solar and wind offer great potential, their variability introduces significant challenges that must be addressed through advanced optimization techniques. Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties connects optimization fundamentals with their applications in sustainable energy systems with a particular emphasis on the challenges posed by uncertainty. Divided into two parts, the book first introduces the core mathematical frameworks and methods needed to model and optimize uncertain systems, including stochastic programming, robust optimization, reinforcement learning, and multiscale algorithms. The authors clearly explain these state-of-the-art tools with attention to both theory and computational practice. The second part shifts to applications, demonstrating how these techniques are applied in real-world contexts such as renewable-based hydrogen, methanol, and ammonia production; carbon capture; shale gas systems; biomass integration; and power system optimization. Throughout the text, the authors emphasize the integration of renewables with chemical industries while highlighting strategies to manage variability, strengthen supply chains, and improve system-wide efficiency. Combining rigorous fundamentals with cutting-edge applications through a tutorial-style approach, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties: Provides the foundation and tools needed to design resilient, optimized, and sustainable energy systems Addresses optimization methods under uncertainty tailored to energy and process systems Presents a unified treatment of stochastic programming, robust optimization, and reinforcement learning techniques Integrates renewable-based systems with chemical industry supply chain design and operation Addresses computational challenges in large-scale optimization of energy systems Both a theoretical resource and a practical guide for applied problem-solving, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties is ideal for graduate-level courses in chemical engineering, process systems engineering, energy systems optimization, and operations research. It is also a valuable reference for industrial researchers, system modelers, and developers working on sustainable process design and energy transition strategies. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.