High-performance computing (HPC) and artificial intelligence (AI) have revolutionized process engineering, enabling complex system modeling, data analysis, optimization design, and real-time monitoring. This book offers a thorough review of state-of-the-art AI technologies, HPC, and their applications in process engineering.

The text delves into the development of traditional process simulators and introduces new numerical solvers based on data-driven and physics-informed neural network approaches. It covers a range of applications in science and engineering, such as multiscale modeling and optimal design in reverse osmosis desalination, model-based experimental analysis to enhance boiling heat transfer, and the inverse identification of high-resolution spatiotemporal contaminant source distributions in atmospheric pollution.

This book is an invaluable resource for researchers, postgraduate students, and industrial practitioners in the fields of process engineering, manufacturing, data science, artificial intelligence, and high-performance computing.