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Principal Components Analysis of nonlinear systems is based on the singular value decomposition of a collection of response time-histories. The principal components are analogous to the modal response time-histories of linear structural analysis, except that the singular values are related to energy rather than frequency. This paper presents a theoretical(More)
Abbreviations DTRA Defense Threat Reduction Agency HFPB High fidelity, physics-based PCD Principal components decomposition SVD Singular value decomposition ABSTRACT With increasingly powerful computational resources at our disposal, it is becoming commonplace to use analytical predictions in lieu of experimentation for characterization of physical systems(More)
The paper compares two methods for quantifying and propagating uncertainty at the component level to a higher level of assembly. One method is based on quantifying component uncertainty in terms of model (input) parameters. The other method quantifies component uncertainty in terms of dimensionless response (output) metrics. Both representations of(More)
NASA has been interested in the development of methods for evaluating the predictive accuracy of structural dynamic models. This interest stems from the use of mathematical models in evaluating the structural integrity of all spacecraft prior to flight. Space structures are often too large and too weak to be tested fully assembled in a ground test(More)
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