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E-raamat: Stochastic Structural Optimization [Taylor & Francis e-raamat]

(Kyoto University, Japan), (Tokyo University of Science)
  • Formaat: 254 pages, 48 Tables, black and white; 20 Line drawings, color; 61 Line drawings, black and white; 20 Illustrations, color; 61 Illustrations, black and white
  • Ilmumisaeg: 08-Aug-2023
  • Kirjastus: CRC Press
  • ISBN-13: 9781003153160
Teised raamatud teemal:
  • Taylor & Francis e-raamat
  • Hind: 138,48 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 197,84 €
  • Säästad 30%
  • Formaat: 254 pages, 48 Tables, black and white; 20 Line drawings, color; 61 Line drawings, black and white; 20 Illustrations, color; 61 Illustrations, black and white
  • Ilmumisaeg: 08-Aug-2023
  • Kirjastus: CRC Press
  • ISBN-13: 9781003153160
Teised raamatud teemal:
"This presents a comprehensive picture of robust design optimization of structures, focused on nonparametric stochastic-based methodologies. Linking structural optimization with both reliability-based design (which usually incorporates assumptions on probability functions which are often unknown), and with robust design (offering simplicity and a lower level of sensitivity) through a unified framework of non-parametric stochastic methodologies provides a rigorous theoretical background and high level of practicality. This text shows how to use this theoretical framework in civil and mechanical engineering practice to design a safe structure which takes account of uncertainty"--

Stochastic Structural Optimization presents a comprehensive picture of robust design optimization of structures, focused on nonparametric stochastic-based methodologies. Good practical structural design accounts for uncertainty, for which reliability-based design offers a standard approach, usually incorporating assumptions on probability functions which are often unknown. By comparison, a worst-case approach with bounded support used as a robust design offers simplicity and a lower level of sensitivity. Linking structural optimization with these two approaches by a unified framework of non-parametric stochastic methodologies provides a rigorous theoretical background and high level of practicality. This text shows how to use this theoretical framework in civil and mechanical engineering practice to design a safe structure which accounts for uncertainty.

  • Connects theory with practice in the robust design optimization of structures
  • Advanced enough to support sound practical designs

This book provides comprehensive coverage for engineers and graduate students in civil and mechanical engineering.

Makoto Yamakawa is a Professor at Tokyo University of Science, and a member of the Advisory Board of the 2020 Asian Congress of Structural and Multidisciplinary Optimization.

Makoto Ohsaki is a Professor at Kyoto University, Japan, treasurer of the International Association for Shell & Spatial Structures and former President of the Asian Society for Structural and Multidisciplinary Optimization.



This comprehensive presentation of robust design optimization of structures combines structural optimization with reliability-based design and robust design through a unified framework of non-parametric stochastic methodologies, to design safe civil or mechanical structures which take account of uncertainty.

1. Basic concepts and examples. 
2. Stochastic optimization. 
3. Random
search-based optimization. 
4. Order statistics-based robust design
optimization. 
5. Robust geometry and topology optimization. 
6.
Multi-objective robust optimization approach. 
7. Surrogate-assisted and
reliability-based optimization.  Appendix.
Makoto Yamakawa is a Professor at Tokyo University of Science, and a member of the Advisory Board of the 2020 Asian Congress of Structural and Multidisciplinary Optimization.

Makoto Ohsaki is a Professor at Kyoto University, Japan, treasurer of the International Association for Shell & Spatial Structures and former President of the Asian Society for Structural and Multidisciplinary Optimization.