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SUMMARY:Current state of the art of polynomial chaos metamodel constructio
 n - Ko\, J (Uncertainty Quantification specialist\, Areva\, Paris)
DTSTART:20130325T103000Z
DTEND:20130325T110000Z
UID:TALK44112@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Polynomial chaos expansion is being increasingly used in the u
 ncertainty quantification of industrial applications. Proposed by Weiner t
 o represent random solution response with respect to input stochastic proc
 ess with Gaussian random variable using a Hermite polynomial\, polynomial 
 chaos expansion (PCE) metamodel mimics the response of the solution over t
 he random input parameter space and can be used in quantile estimation\, r
 eliability analysis and solution optimization\, in addition to quantifying
  statistical moments. PCE is useful in the industrial context because anal
 ysis on a polynomial metamodel is essentially free in comparison to the ti
 me- and CPU-intensive evaluation of the complete numerical model. One of i
 ts main appeal lies in its non-intrusive approach: the PCE metamodel can b
 e constructed from samples of the complete numerical model:  a black-box. 
 This talk will compare the current state of the art in PCE methodologies\,
  namely the stochastic spectral projection\, algebraic quadrature and leas
 t-squares\, using examples.\n
LOCATION:Seminar Room 1\, Newton Institute
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