Machine Learning in Modeling and Simulation

Chapter 1 Machine Learning in Computer Aided Engineering

Chapter 3 Gaussian Processes

Chapter 4 Machine Learning Methods for Constructing Dynamic Models From Data

Chapter 5 Physics-Informed Neural Networks: Theory and Applications

Chapter 6 Physics-Informed Deep Neural Operator Networks

Chapter 7 Digital Twin for Dynamical Systems

Chapter 8 Reduced Order Modeling

Chapter 9 Regression Models for Machine Learning

Chapter 10 Overview on Machine Learning Assisted Topology Optimization Methodologies

Chapter 11 Mixed-Variable Concurrent Material, Geometry, and Process Design in Integrated Computational Materials Engineering

Chapter 12 Machine Learning Interatomic Potentials: Keys to First-Principles Multiscale Modeling