Sensitivity Statistics of 3D Structures under Parametric Uncertainty
Publication: Journal of Engineering Mechanics
Volume 127, Issue 9
Abstract
Determination of sensitivity gradient is a major prerequisite for structural optimization, reliability assessment, and parameter identification. As the conventional deterministic sensitivity analysis cannot provide complete information, stochastic analysis is needed to tackle the uncertainties in structural parameters. This study focuses on the utility of the stochastic finite-element method for random response sensitivity analysis. The stochastic modeling of a random parameter is based on a commonly used 2D local averaging method generalized for a 3D case. The Choleski decomposition technique is then employed for digital simulation. The Neumann expansion based finite-element simulation method is extended for stochastic sensitivity analysis. This technique leads to a considerable saving of computational time. Example problems are used to compare the accuracy of this method to the direct Monte Carlo simulation and perturbation method in terms of varying stochasticity and efficiency in CPU time.
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Information & Authors
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Published In
Journal of Engineering Mechanics
Volume 127 • Issue 9 • September 2001
Pages: 909 - 914
History
Received: Apr 25, 2000
Published online: Sep 1, 2001
Published in print: Sep 2001
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