Computational Metal Additive Manufacturing: Advanced Multiphysics and AI-Enhanced Simulation – Hardcover

This book presents a comprehensive and forward-looking approach to computational modeling in metal additive manufacturing (AM), focusing on the integration of advanced multiphysics simulations with artificial intelligence (AI) techniques. It is designed to serve as a foundational and practical reference textbook for students, researchers, and industry professionals engaged in digital manufacturing, process optimization, and predictive modeling within the context of metal additive manufacturing (AM). The book bridges the gap between theoretical computational modeling and real-world manufacturing challenges by providing the reader with a deep understanding of how to simulate, predict, and enhance complex metal AM processes such as Powder Bed Fusion (PBF), Directed Energy Deposition (DED), binder jet, Electrochemical Metal AM (ECAM) and a few non common metal AM methods. It emphasizes modeling the thermomechanical behavior, residual stress evolution, microstructural transformations (grain morphology and phase fraction), melt-pool dynamics, and performance prediction (e.g. fatigue life prediction) of printed metal parts using analytical models, numerical methods (like finite element (FE), finite difference (FD), meshless, and finite volume (FV) methods), mesoscale methods (like phase-field (PF), and stochastic methods), computational thermodynamics, and AI-assisted hybrid models, including Physics-Informed Neural Networks (PINNs) and Convolutional Neural Networks (CNNs).”