This reference text will provide a systematic review of state-of-the-art AI technologies, high-performance computing and their applications in process engineering. It will introduce the development of traditional process simulators in the field of process engineering and new numerical solvers based on data-driven and physics-informed neural networks approaches.
It will also cover applications in science and engineering, including but not limited to multiscale modelling and optimal design problem in reverse osmosis desalination, model-based experimental analysis in enhancement of boiling heat transfer, and inverse identification of high-resolution spatiotemporal contaminant source distributions in atmospheric pollution.
