1st Edition

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures

By Won‐Kee Hong Copyright 2023
580 Pages 244 Color Illustrations
by CRC Press

580 Pages 244 Color Illustrations
by CRC Press

580 Pages 244 Color Illustrations
by CRC Press

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice. It shows how objective functions including cost, CO2 emissions, and structural weight of concrete structures are optimized either separately or... Read more

1. Introduction to Lagrange optimization for engineering applications

2. AI-based Lagrange optimization adopting universally generalizable functions

3. An optimized design of reinforced concrete columns based on an ANN-based Hong-Lagrange method

4. Optimizing reinforced concrete beam cost using ANN-based Hong-Lagrange method

5. ANN-based structural designs using Lagrange multipliers optimizing multiple objective functions

Appendix A

Appendix B

Appendix C

Appendix D

Biography

Won‐Kee Hong is a professor of architectural engineering at Kyung Hee University, South Korea. He received his master's and PhD degrees from UCLA, and has worked for Englekirk and Hart, Inc. (USA), Nihhon Sekkei (Japan), and the Samsung Engineering and Construction Company (Korea). Dr. Hong has more than 35 years of professional experience in structural and construction engineering. He has been both an inventor and researcher in the field of modularized composite structures and is the author of more than 100 technical papers and over 100 patents in both Korea and The United States.