Print Email Facebook Twitter Generating nested quadrature rules with positive weights based on arbitrary sample sets Title Generating nested quadrature rules with positive weights based on arbitrary sample sets Author van den Bos, L.M.M. (TU Delft Wind Energy; Centrum Wiskunde & Informatica (CWI)) Sanderse, Benjamin (Centrum Wiskunde & Informatica (CWI)) Bierbooms, W.A.A.M. (TU Delft Wind Energy) van Bussel, G.J.W. (TU Delft Wind Energy) Date 2020 Abstract For the purpose of uncertainty propagation a new quadrature rule technique is proposed that has positive weights, has high degree, and is constructed using only samples that describe the probability distribution of the uncertain parameters. Moreover, nodes can be added to the quadrature rule, resulting in a sequence of nested rules. The rule is constructed by iterating over the samples of the distribution and exploiting the null space of the Vandermonde system that describes the nodes and weights, in order to select which samples will be used as nodes in the quadrature rule. The main novelty of the quadrature rule is that it can be constructed using any number of dimensions, using any basis, in any space, and using any distribution. It is demonstrated both theoretically and numerically that the rule always has positive weights and therefore has high convergence rates for sufficiently smooth functions. The convergence properties are demonstrated by approximating the integral of the Genz test functions. The applicability of the quadrature rule to complex uncertainty propagation cases is demonstrated by determining the statistics of the flow over an airfoil governed by the Euler equations, including the case of dependent uncertain input parameters. The new quadrature rule significantly outperforms classical sparse grid methods. Subject Numerical integrationQuadrature formulasUncertainty propagation To reference this document use: http://resolver.tudelft.nl/uuid:39e01955-8bec-429e-9c4a-d717a113e773 DOI https://doi.org/10.1137/18M1213373 ISSN 2166-2525 Source SIAM-ASA Journal on Uncertainty Quantification, 8 (1), 139-169 Part of collection Institutional Repository Document type journal article Rights © 2020 L.M.M. van den Bos, Benjamin Sanderse, W.A.A.M. Bierbooms, G.J.W. van Bussel Files PDF 18m1213373.pdf 13.36 MB Close viewer /islandora/object/uuid:39e01955-8bec-429e-9c4a-d717a113e773/datastream/OBJ/view