Structural Design Optimization Considering Uncertainties
Structures & Infrastructures Book , Vol. 1, Series, Series Editor: Dan M. Frangopol
Uncertainties play a dominant role in the design and optimization of structures and infrastructures. In optimum design of structural systems due to variations of the material, manufacturing variations, variations of the external loads and modelling uncertainty, the parameters of a structure, a structural system and its environment are not given, fixed coefficients, but random variables with a certain probability distribution. The increasing necessity to solve complex problems in Structural Optimization, Structural Reliability and Probabilistic Mechanics, requires the development of new ideas, innovative methods and numerical tools for providing accurate numerical solutions in affordable computing times.
This book presents the latest findings on structural optimization considering uncertainties. It contains selected contributions dealing with the use of probabilistic methods for the optimal design of different types of structures and various considerations of uncertainties. The first part is focused on reliability-based design optimization and the second part on robust design optimization. Comprising twenty-one, self-contained chapters by prominent authors in the field, it forms a complete collection of state-of-the-art theoretical advances and applications in the fields of structural optimization, structural reliability, and probabilistic computational mechanics. It is recommended to researchers, engineers, and students in civil, mechanical, naval and aerospace engineering and to professionals working on complicated costs-effective design problems.
Table of Contents
Part A. Robust design optimization (RDO)
A1. Basic aspects on RDO
- 1: Evaluation and Maximization of Robustness of Trusses by using Semidefinite Programming
Yoshihiro Kanno and Izuru Takewaki.
- 2: A Taylor expansion approach to the design optimization of structures with randomness
Ioannis Doltsinis, Zhan Kang.
A2. Theoretical advances on RDO
- 3: Cost-Benefit Optimization and Risk Acceptability for Maintained Structures
R. Rackwitz and A. Joanni.
- 4: Efficient robust-design optimization involving dynamic reliability problems Alexandros A. Taflanidis and James L. Beck.
- 5: Robust design optimization using possibility theory
Byeng Dong Youn.
- 6: Bridging the gap between robust and reliability-based design optimization with the saddlepoint expansion
Jorge E. Hurtado.
A3. Application driven chapters on RDO
- 7: Info-gap robust design of passively controlled structures with load and model uncertainties
Izuru Takewaki and Yakov Ben-Haim.
- 8: Efficient computing techniques for structural reliability-based robust design optimization Nikos D. Lagaros, Vaggelis Plevris, and Yiannis Tsompanakis.
Part B. Reliability-based design optimization (RBDO)
B1. Basic aspects on RBDO
- 9: Reliability-based structural optimization
- 10: Efficient approaches for system reliability-based design optimization
Zissimos P. Mourelatos, Jinghong Liang and Efstratios Nikolaidis.
B2. Theoretical advancements and academicapplications of RBDO
- 11: Numerical and semi-numerical methods for reliability-based design optimization
- 12: Non-probabilistic design optimization with insufficient data using possibility and evidence theories
Zissimos P. Mourelatos and Jun Zhou.
- 13: Efficient stochastic methods in RBDO
- 14: Reliability analysis and reliability based design optimization using the moment method
Byung Man Kwak, Sang Hoon Lee and Jae Sung Huh.
- 15: Analytical target cascading in optimal design of decomposed systems under uncertainty
M. Kokkolaras and P.Y. Papalambros.
- 16: Reliability based topology optimization using the hybrid cellular automaton method
Neal M. Patel, John E. Renaud, Harish Agarwal and Andres Tovar.
- 17: Sample average approximations in Reliability-based structural optimization: Theory and applications
J.O. Royset, E. Polak.
B3. Application-driven chapters on RBDO
- 18: Design optimization of stochastic dynamic systems by algebraic reduced order models
G. Weickum, M. Allen, K. Maute and D. Frangopol.
- 19: Reliability-based damage tolerance methodology
20: Overview of reliability analysis and design capabilities in DAKOTA with Application to Shape Optimization of MEMS
- M.S. Eldred, S.A. Mitchell, B. J. Bichon and B. M. Adams.
Yiannis Tsompanakis is an Assistant Professor of structural earthquake engineering. He has many research and practical projects in earthquake engineering and computational mechanics. His main interests include: computational dynamics, structural and geotechnical earthquake engineering, structural optimization, probabilistic mechanics, structural assessment, applications of artificial intelligence methods in engineering.
Nikos D. Lagaros is an Assistant Professor of Civil Engineering. His main research interests include: *nonlinear dynamic analysis of concrete and steel structures under seismic loading, *performance-based earthquake engineering, *structural design optimization of real-world structures, *seismic risk and reliability analysis, * neural network in structural engineering, *fragility evaluation of reinforced concrete and steel structures, *inverse problems in structural dynamics, *parallel and distributed computing/Grid computing technologies, *evolutionary computations and *geotechnical earthquake engineering.
Manolis Papadrakakis is a Professor in Civil Engineering His research activities are focused on the development and the application of the latest computer methods and technology to structural engineering analysis and design. He has written and edited many publications, both in English and in Greek.
"This book is successful in its goal of providing an overview of recent research on structural optimization under uncertainties. The papers present a diverse set of approaches. The reader interested in identifying the state-of-the-art in RBDO and RDO would find this book to be a very useful resource".
Professor Lori Graham-Brady, Department of Civil Engineering, John Hopkins University, Baltimore, Maryland, USA