Computational mechanics with deep learning: an introduction /
Series: Lecture notes on numerical methods in engineering and sciences Published by : Springer, (Cham, Switzerland : ) Physical details: xiv, 402 pages: col. illus. ; 24 cm. ISBN:9783031118463.| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Course reserves |
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ASCOT Library - Zabali Campus Reference | Reference | Ref 620.1 Y10c 2023 C1 04626 (Browse shelf) | Available | Ref6201004626 | ||
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ASCOT Library - Zabali Campus Reference | Reference | Ref 620.1 Y10c 2023 C2 04627 (Browse shelf) | Available | Ref6201004627 |
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| Ref 620.0042 L43a 2022 04592 AutoCAD 2023 instructor: a student guide for in-depth coverage of AutoCAD's commands and features / | Ref 620.0042 Y29i 2022 04594 Introduction to AutoCAD 2023 for civil engineering applications / | Ref 620.04 Sh61p 2022 Principles and practice: an integrated approach to engineering graphics and AutoCAD 2023 / | Ref 620.1 Y10c 2023 C1 04626 Computational mechanics with deep learning: an introduction / | Ref 620.1 Y10c 2023 C2 04627 Computational mechanics with deep learning: an introduction / | Ref 620.106 Ud2f 2023 Fluid mechanics: a problem-solving approach / | Ref 620.1064 M77i 2022 Introduction to fluid dynamics: understanding fundamental physics / |
Includes bibliographical references and index.
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
"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 mechanics and deep learning" -- Back cover
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