Overview
High-performance computing (HPC) and artificial intelligence (AI) in process engineering involve complex system modelling, data analysis, optimization design, and real-time monitoring. Key methods include data integration, model construction, optimization algorithms, machine learning, deep learning, parallel computing, and real-time analytics. These techniques significantly enhance production efficiency, reduce costs, and improve system stability. They also promote industrial intelligence, creating new opportunities and challenges in process engineering. This integration supports the advancement of Industry 4.0 and smart manufacturing. Key Features: Provides a systematic review of state-of-the-art artificial intelligence technologies and high-performance computing, and their applications in process engineering Introduces the development of traditional process simulators in process engineering and new numerical solvers based on data-driven and physics-informed neural networks approaches Provides perspectives of high-performance computing and artificial intelligence from industrial leaders in software and hardware Aimed at researchers and industrial practitioners in process engineering, manufacturing, data science, artificial intelligence and high-performance computing
Full Product Details
Author: Mingheng Li (California State Polytechnic University (United States)) ,
Yi Heng (Sun Yat-sen University (China))
Publisher: Institute of Physics Publishing
Imprint: Institute of Physics Publishing
Dimensions:
Width: 17.80cm
, Height: 1.90cm
, Length: 25.40cm
Weight: 0.753kg
ISBN: 9780750361729
ISBN 10: 0750361727
Publication Date: 04 April 2025
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Hardback
Publisher's Status: Active
Availability: In Print
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Author Information
Mingheng Li is a professor of chemical engineering specializing in process systems engineering, with a focus on materials, energy, and environmental applications. He has pioneered innovations in the processing of low-emissivity and self-cleaning coatings and advanced non-conventional dynamic and cyclic reverse osmosis techniques. He has served as an editor for the American Institute of Physics Publishing. Yi Heng obtained his Ph.D. degree from RWTH Aachen University, Germany. He is a professor of applied mathematics. His work focuses on inverse problems, high performance computing, artificial intelligence, and their applications to various areas of science and engineering. He has served as an executive member of the editorial board for Science Bulletin.
