As modern structures require more critical and complex designs, the
need for accurate approaches to assess uncertainties in loads,
geometry, material properties, manufacturing processes and
operational environments has increased significantly. Reliability
assessment techniques help to develop safe designs and identify
where significant contributors of uncertainty occur in structural
systems, or, where further research, testing and quality control
could increase the safety and efficiency of the structure.
Reliability-based Structural Design provides readers with an
understanding of the fundamentals and applications of structural
reliability, stochastic finite element method, reliability analysis
via stochastic expansion, and optimization under uncertainty.
Probability theory, statistic methods, and reliability analysis
methods including Monte Carlo Sampling, Latin hypercube sampling,
first and second-Order reliability methods, stochastic finite
element method, and stochastic optimization are discussed. In
addition, the use of stochastic expansions, including polynomial
chaos expansion and Karhunen-Loeve expansion, for the reliability
analysis of practical engineering problems is also examined.
Detailed examples of practical engineering applications including
an uninhabited joined-wing aircraft and a supercavitating torpedo
are presented to illustrate the effectiveness of these methods.
Reliability-based Structural Design will be a valuable reference
for graduate and post graduate students studying structural
reliability, probabilistic analysis and optimization under
uncertainty; as well as engineers, researchers, and technical
managers who are concerned with theoreticalfundamentals,
computational implementations and applications for probabilistic
analysis and design.
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