Computational Mechanics with Deep Learning

1. Overview.- 2. Mathematical Background for Deep Learning.- 3. Computational Mechanics with Deep Learning.- 4. Numerical Quadrature with Deep Learning.- 5. Improvement of Finite Element Solutions with Deep Learning.- 6. Contact Mechanics with Deep Learning.- 7. Flow Simulation with Deep Learning.- 8. Further Applications with Deep Learning.- 9. Bases for Computer Programming.- 10. Computer Programming for a Representative Problem.

Genki Yagawa received his Ph.D. from University of Tokyo in 1970. He became Professor at University of Tokyo in 1984 and Director and Professor at Center for Computational Mechanics Research of Toyo University in 2004. Currently, he is an Emeritus Professor at University of Tokyo and Toyo University, Chairman of Nuclear Safety Research Association, and Member of Science Council of Japan. His awards and honors include the Order of the Sacred Treasure, Gold Rays with Neck Ribbon endowed from His Majesty the Japanese Emperor, Japan Academy Prize, International Association for Computational Mechanics Award, Asia Pacific Association Computational Mechanics Zienkiewicz Medal, Prime Minister Award, Minister of Science and Technology Award, Toray Science and Technology Medal, Honorary Doctor Endowed from Iasi Technical University, and Fellow of International Association for Computational Mechanics, Japan Society for Industrial and Applied Mathematics, Japan Society for Simulation Technology and Atomic Energy Society of Japan.



Atsuya Oishi received his Ph.D. from University of Tokyo in 1996. He became Lecturer at University of Tokushima in 1997 and has been an Associate Professor at University of Tokushima since 2006. His awards include the outstanding paper award from Japan Society for Computational Engineering and Science and JACM fellow award from Japan Association for Computational Mechanics.