Abstract: This paper presents a multi-disciplinary design optimization methodology that is based on probabilistic computational methods. The methodology permits consideration of different measures of product performance and reliability in order to determine the optimal product design. The approach developed enables engineers to evaluate the impact of design changes on all relevant measures of performance simultaneously. By incorporating variable uncertainty, the impact of variable variation on product performance can be determined. Reliability methods are available for the computation of component and system-level reliability, and their use in the design of multidisciplinary systems. The method demonstrates the adaptation of probabilistic reliability analysis tools to complex engineering systems that exploit the synergism of mutually interacting disciplines such as structures, propulsion, aerodynamics, and controls. The ability of probabilistic methods to determine the sensitivity of performance to random variable distribution parameters is employed to develop linear programming models that can optimize product design. Reliability-base optimum design typically employs the minimization of weight or cost as the objective function, and component and system-level reliability requirements as constraints. A demonstration problem that illustrates the application of the method is provided.
Publication Year: 1998
Publication Date: 1998-08-22
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 7
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