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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 20 July 2026
- ISBN 9781032508870
- Binding Paperback
- No. of pages220 pages
- Size 229x152 mm
- Language English
- Illustrations 86 Illustrations, black & white; 44 Halftones, black & white; 42 Line drawings, black & white; 15 Tables, black & white 700
Categories
Short description:
Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load bearing structures as well as mechanical metamaterials.
MoreLong description:
Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load-bearing structures as well as mechanical metamaterials.
Discussing both machine learning and design analysis in detail, this book enables readers to optimize their designs using a data-driven approach. This book discusses the basics of the materials utilized, for example, shape memory polymers, and the manufacturing approach employed, such as 3D or 4D printing. Additionally, the book discusses the use of forward design and inverse design frameworks to discover novel lattice unit cells and thin-walled cellular unit cells with enhanced mechanical and functional properties such as increased mechanical strength, heightened natural frequency, strengthened impact tolerance, and improved recovery stress. Inverse design methodologies using generative adversarial networks are proposed to further investigate and improve these structures. Detailed discussions on fingerprinting approaches, machine learning models, structure screening techniques, and typical Python codes are provided in the book.
The book provides detailed guidance for both students and industry engineers to optimize their structural designs using machine learning.
MoreTable of Contents:
1. Introduction to Structures with Complex Geometrical Configurations. 2. Structural Optimization. 3. Introduction to Machine Learning-Assisted Structural Optimization. 4. Structural Optimization of Biomimetic Rods Using Machine Learning Regression. 5. Structural Optimization of Lattice Structures. 6. Inverse Machine Learning Using Generative Adversarial Networks. 7. Design and Optimization of Mechanical Metamaterials Using Correlation Analysis. 8. Summary and Future Perspectives.
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