Data-driven uncertainty quantification of structural systems via B-spline expansion

A data-driven uncertainty quantification scheme relying on B-spline functions is investigated in this study. Instead of predefining basis functions according to the statistics of the uncertain input, as in conventional polynomial chaos expansion (PCE)-based implementations, the method introduced her...

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Veröffentlicht in:	Computers & structures 2018-09, Vol.207, p.245-257
Hauptverfasser:	Dertimanis, V.K., Spiridonakos, M.D., Chatzi, E.N.
Format:	Artikel
Sprache:	eng
Schlagworte:	B spline functions B-splines Basis functions Estimating techniques Evolutionary algorithms Hybrid optimization Knots Optimization Parameter estimation Parameterization Polynomial chaos Polynomials Robustness (mathematics) Separable Non-linear Least Squares Uncertainty
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