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A reduced spectral function approach for the stochastic finite element analysis

Quantification of uncertainty in computational prediction is necessary for decision-making. Conventional approach generally builds a response surface by sampling the parameter-space of a problem. This is purely a numerical approach. Funded by Wolfson Research Merit Award, this wok proposes a physics-based approach where eigenmodes of the stochastic operators are used. A significant reduction in computational effort and increased accuracy is demonstrated in the paper. Since this publication, the idea has been extended to dynamic problems and it forms the basis of funding from Embraer Aircraft Corporation [pedro.cabral@embraer.com.br] where this technique is used for uncertainty quantification of composite wing models.