Results 11 to 20 of about 303 (161)
Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2021 Sparse polynomial chaos expansions (PCE) are a popular surrogate modelling method that takes advantage of the properties of PCE, the sparsity-of-effects principle, and powerful sparse regression solvers to approximate computer models with many input parameters, relying on only few model evaluations.
Nora Lüthen +2 more
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A weighted L1-minimization approach for sparse polynomial chaos expansions [PDF]
J. Comput. Phys., 2013 This work proposes a method for sparse polynomial chaos (PC) approximation of high-dimensional stochastic functions based on non-adapted random sampling. We modify the standard l1 -minimization algorithm, originally proposed in the context of compressive sampling, using a priori information about the decay of the PC coefficients and refer to the ...
Ji Peng, Jerrad Hampton, Alireza Doostan
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Sparse Polynomial Chaos expansions using variational relevance vector machines [PDF]
Journal of Computational Physics, 2020 The challenges for non-intrusive methods for Polynomial Chaos modeling lie in the computational efficiency and accuracy under a limited number of model simulations. These challenges can be addressed by enforcing sparsity in the series representation through retaining only the most important basis terms.
Panagiotis Tsilifis +3 more
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Machines, 2023 This paper presents an efficient method for obtaining the dynamic mesh stiffness and dynamic response of a helical gear pair. Unlike the traditional dynamic model that utilizes a time-dependent sequence, the mesh stiffness using the presented method is ...
Hongxu Tian +3 more
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Algorithms, 2022 In this article, multi-fidelity kriging and sparse polynomial chaos expansion (SPCE) surrogate models are constructed. In addition, a novel combination of the two surrogate approaches into a multi-fidelity SPCE-Kriging model will be presented.
Markus P. Rumpfkeil +2 more
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Journal of Marine Science and Engineering, 2022 The geometrical dimensions and mechanical properties of composite materials exhibit inherent variation and uncertainty in practical engineering. Uncertainties in geometrical dimensions and mechanical properties propagate to the structural performance of ...
Ming Chen +3 more
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IEEE Access, 2019 The problem of characterizing the sensitivity indices of structural performance considering random and interval uncertainty variables simultaneously is analyzed.
Chan Qiu +3 more
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A gradient enhanced ℓ1-minimization for sparse approximation of polynomial chaos expansions [PDF]
Journal of Computational Physics, 2018 We investigate a gradient-enhanced $\ell_1$-minimization for constructing sparse polynomial chaos expansions. In addition to function evaluations, measurements of the function gradient is also included to accelerate the identification of expansion coefficients.
Ling Guo +2 more
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A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions [PDF]
Journal of Computational Physics, 2018 Compressive sampling has become a widely used approach to construct polynomial chaos surrogates when the number of available simulation samples is limited. Originally, these expensive simulation samples would be obtained at random locations in the parameter space.
Negin Alemazkoor, Hadi Meidani
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Geosciences, 2021 A rotation of the anisotropic soil fabric pattern is commonly observed in natural slopes with a tilted stratification. This study investigates the rotated anisotropy effects on slope reliability considering spatially varied soils.
Tingting Zhang +3 more
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