Structural Design Optimization Considering Uncertainties

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.

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.

Part A. Robust design optimization (RDO)A1. Basic aspects on RDO

1: Evaluation and Maximization of Robustness of Trusses by using Semidefinite ProgrammingYoshihiro Kanno and Izuru Takewaki.
2: A Taylor expansion approach to the design optimization of structures with randomnessIoannis Doltsinis, Zhan Kang.
A2. Theoretical advances on RDO

3: Cost-Benefit Optimization and Risk Acceptability for Maintained StructuresR. 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 theoryByeng Dong Youn.
6: Bridging the gap between robust and reliability-based design optimization with the saddlepoint expansionJorge E. Hurtado.
A3. Application driven chapters on RDO

7: Info-gap robust design of passively controlled structures with load and model uncertaintiesIzuru 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 optimizationAlaa Chateauneuf.
10: Efficient approaches for system reliability-based design optimizationZissimos P. Mourelatos, Jinghong Liang and Efstratios Nikolaidis.
B2. Theoretical advancements and academicapplications of RBDO

11: Numerical and semi-numerical methods for reliability-based design optimizationG. Kharmanda.
12: Non-probabilistic design optimization with insufficient data using possibility and evidence theoriesZissimos P. Mourelatos and Jun Zhou.
13: Efficient stochastic methods in RBDOAlaa Chateauneuf.
14: Reliability analysis and reliability based design optimization using the moment methodByung Man Kwak, Sang Hoon Lee and Jae Sung Huh.
15: Analytical target cascading in optimal design of decomposed systems under uncertaintyM. Kokkolaras and P.Y. Papalambros.
16: Reliability based topology optimization using the hybrid cellular automaton methodNeal M. Patel, John E. Renaud, Harish Agarwal and Andres Tovar.
17: Sample average approximations in Reliability-based structural optimization: Theory and applicationsJ.O. Royset, E. Polak.
B3. Application-driven chapters on RBDO

18: Design optimization of stochastic dynamic systems by algebraic reduced order modelsG. Weickum, M. Allen, K. Maute and D. Frangopol.
19: Reliability-based damage tolerance methodologyY-T. Wu.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.