Stochastic Structural Optimization

<p><em>Stochastic Structural Optimization</em> 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.</p><ul> <p> </p> <li>Connects theory with practice in the robust design optimization of structures</li> <p> </p> <li>Advanced enough to support sound practical designs</li> </ul><p>This book provides comprehensive coverage for engineers and graduate students in civil and mechanical engineering.</p><p><strong>Makoto Yamakawa</strong> 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. </p><p><strong>Makoto Ohsaki</strong> 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.</p>