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Complex problems are difficult to solve by exact methods. Simulation methods are used in such cases. Probabilistic simulation of systems has received much attention particularly in the research as of reliability, and risk analysis, sensitivity analysis, optimization under uncertainty, to mention a few. In the context of uncertainty- based simulation, one of the major problem is computational demand of the numerical (finite element) model that is used to analyze the large scale engineering systems under consideration. However, probabilistic simulation is the only alternative for those cases in reliability analysis for those cases where the limit state function is not available in explicit form. However to address computational issue, efficient simulation techniques or design of experiments (DoE) are carried out i.e. determining the design points (in the input space), where the original (high fidelity) computational model needs to be evaluated. The accuracy level of reliability analysis depends on the region of simulation in the limit state function depends on the DoE over the input design space. This chapter will introduce state-of-the-art probabilistic simulation methods in uncertainty quantification of engineered systems with varying input dimensionality and computational complexity.
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- Probabilistic Simulation Methods
Sanjay K. Gupta
- Chapter 5
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