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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 106
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by:
Paper 128
Uncertainty Analysis of the Dynamic Response of a Randomly Parametrized Corrugated Skin A. Kundu1, F.A. DiazDelaO2, M.I. Friswell1 and S. Adhikari1
1Civil and Computational Engineering Centre, Swansea University, Swansea, United Kingdom
A. Kundu, F.A. DiazDelaO, M.I. Friswell, S. Adhikari, "Uncertainty Analysis of the Dynamic Response of a Randomly Parametrized Corrugated Skin", in , (Editors), "Proceedings of the Twelfth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 128, 2014. doi:10.4203/ccp.106.128
Keywords: stochastic structural dynamics, stochastic sensitivity, sparse-grid collocation, corrugated skin..
Summary
Uncertainty analysis of computational models is essential to obtain a probabilistic
description of the output quantities in the presence of uncertain model parameters or
model inadequacy. Uncertainty quantification of the numerical model inputs, propagation
of uncertainty to the model output and finally the analysis of response statistics,
sensitivity, reliability, are all covered within the topic of uncertainty analysis. This has
important applications in engineering design in terms of optimizing design variables
under parameter fluctuations, obtaining confidence values associated with a novel design
amongst others. However, the stochastic analysis of computational models are
quite expensive. The objective of the work, described in this paper, is to develop a
computational framework for efficient uncertainty analysis of structural dynamic systems.
This has been applied to the design optimization of corrugated compliant skins
in order to study its response sensitivity to its material properties and geometrical parameters.
The sparse grid collocation technique has been utilized here as an efficient
uncertainty propagation method for a multidimensional stochastic input. The sensitivity
of the solution to the various sources of input uncertainty is studied using the
Sobol's indices for sensitivity measure. Important physical insight into the behavior
of the model for various uncertainties in geometrical and parametric properties is
provided by this analysis.
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