UNCERTAINTY EVALUATION METHOD FOR NONLINEAR SYSTEM TEST BASED ON POLYNOMIAL CHAOS EXPANSION
Jixie qiangdu, 2022 The uncertainty analysis of test results of nonlinear system shows the dispersion of test results. In this paper, an evaluation method of test uncertainty of nonlinear system based on polynomial chaos expansion is suggested.
YU HuiJie +5 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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Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification [PDF]
, 2014 Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits.
Daniel, Luca +4 more
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A Flexible Polynomial Expansion Method for Response Analysis with Random Parameters
Complexity, 2018 The generalized Polynomial Chaos Expansion Method (gPCEM), which is a random uncertainty analysis method by employing the orthogonal polynomial bases from the Askey scheme to represent the random space, has been widely used in engineering applications ...
Rugao Gao, Keping Zhou, Yun Lin
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Review of polynomial chaos-based methods for uncertainty quantification in modern integrated circuits [PDF]
, 2018 Advances in manufacturing process technology are key ensembles for the production of integrated circuits in the sub-micrometer region. It is of paramount importance to assess the effects of tolerances in the manufacturing process on the performance of ...
Dhaene, Tom +2 more
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An Efficient Polynomial Chaos Expansion Method for Uncertainty Quantification in Dynamic Systems
Applied Mechanics, 2021 Uncertainty is a common feature in first-principles models that are widely used in various engineering problems. Uncertainty quantification (UQ) has become an essential procedure to improve the accuracy and reliability of model predictions.
Jeongeun Son, Yuncheng Du
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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
openaire +4 more sources
Comparison of Stochastic Methods for the Variability Assessment of Technology Parameters [PDF]
, 2011 This paper provides and compares two alternative solutions for the simulation of cables and interconnects with the inclusion of the effects of parameter uncertainties, namely the Polynomial Chaos (PC) method and the Response Surface Modeling (RSM).
Bellan +21 more
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Identification of ground anchors reliability based on acceptance tests and the polynomial chaos expansion method [PDF]
Archives of Civil EngineeringThe paper presents a reliability analysis of ground anchors based on acceptance tests and the polynomial chaos expansion method. First of all, it was estimated the probability of meeting the requirements of acceptance tests based on anchor tests realised
Marek Wyjadłowski +3 more
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Applied Mechanics, 2021 In order to analyze the dynamics of a structural problem accurately, a precise model of the structure, including an appropriate material description, is required.
Marcel S. Prem +2 more
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