Results 31 to 40 of about 7,268 (236)
Alternative SPICE Implementation of Circuit Uncertainties Based on Orthogonal Polynomials [PDF]
, 2011 The impact on circuit performance of parameters uncertainties due to possible tolerances or partial information on devices can be effectively evaluated by describing the resulting stochastic problem in terms of orthogonal polynomial expansions of ...
Stievano, Igor Simone +5 more
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HIERARCHICAL ADAPTIVE POLYNOMIAL CHAOS EXPANSIONS [PDF]
Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2015), 2015 Polynomial chaos expansions (PCE) are widely used in the framework of uncertainty quantification. However, when dealing with high dimensional complex problems, challenging issues need to be faced. For instance, high-order polynomials may be required, which leads to a large polynomial basis whereas usually only a few of the basis functions are in fact ...
Mai, Chu V., Sudret, Bruno
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A conditional stochastic projection method applied to a parametric vibrations problem
Journal of Civil Engineering and Management, 2014 Parametric vibrations can be observed in cable-stayed bridges due to periodic excitations caused by a deck or a pylon. The vibrations are described by an ordinary differential equation with periodic coefficients.
Wlodzimierz Brzakala, Aneta Herbut
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Projection Pursuit Adaptation on Polynomial Chaos Expansions
Computer Methods in Applied Mechanics and Engineering, 2022 The present work addresses the issue of accurate stochastic approximations in high-dimensional parametric space using tools from uncertainty quantification (UQ). The basis adaptation method and its accelerated algorithm in polynomial chaos expansions (PCE) were recently proposed to construct low-dimensional approximations adapted to specific quantities
Xiaoshu Zeng, Roger Ghanem
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Sparse deterministic approximation of Bayesian inverse problems [PDF]
, 2011 We present a parametric deterministic formulation of Bayesian inverse problems with an input parameter from infinite-dimensional, separable Banach spaces.
A M Stuart +5 more
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Vehicle parameter sensitivity with polynomial chaos
Revista Iberoamericana de Automática e Informática Industrial RIAI, 2015 It is interesting to analyze the parameter sensitivity of mathematical models that describe physical systems, and it deserves particular attention the sensitivity study of models with uncertainty in the parameter values.
Eduardo Haro +2 more
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From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases [PDF]
Wind Energy Science, 2018 We define and demonstrate a procedure for quick assessment of site-specific lifetime fatigue loads using simplified load mapping functions (surrogate models), trained by means of a database with high-fidelity load simulations.
N. Dimitrov +3 more
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Polynomial chaos in evaluating failure probability: A comparative study [PDF]
, 2018 summary:Recent developments in the field of stochastic mechanics and particularly regarding the stochastic finite element method allow to model uncertain behaviours for more complex engineering structures.
Kučerová, Anna +2 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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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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