This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems of computational mechanics. The final chapter gives perspectives to the applications of the deep learning to computational mechanics.

This book is intended for students, engineers, and researchers interested in both computational mechanics and deep learning. It presents the mathematical and computational foundations of Deep Learning with detailed mathematical formulas in an easy-to-understand manner. It also discusses various applications of Deep Learning in Computational Mechanics, with detailed explanations of the Computational Mechanics fundamentals selected there. Sample programs are included for the reader to try out in practice. This book is therefore useful for a wide range of readers interested in computational...

This book focuses on wave propagation phenomena in elastic solids modelled by the use of the finite element method. Although the latter is a well-established and popular numerical tool used by engineers and researchers all around the word the process of modelling of wave propagation can still be a challenge. The book introduces a reader to the problem by presenting a historical background and offering a broad perspective on the development of modern science and numerical methods. The principles of wave phenomena are clearly presented to the reader as well as the necessary background for...