Results 21 to 30 of about 12,137 (169)

Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models [PDF]

, 2021
Global sensitivity analysis aims at quantifying the impact of input variability onto the variation of the response of a computational model. It has been widely applied to deterministic simulators, for which a set of input parameters has a unique ...
Sudret, B., Zhu, X.
core   +1 more source

Small Sample-Based Fatigue Reliability Analysis Using Non-Intrusive Polynomial Chaos

IEEE Access, 2020
Based on small sample of fatigue test data, a new method to obtain p-S-N curve for fatigue reliability analysis using non-intrusive polynomial chaos (NIPC) is proposed to lower test cost.
Xiaoran Liu, Qin Sun
doaj   +1 more source

Bayesian inference of earthquake rupture models using polynomial chaos expansion [PDF]

Geoscientific Model Development, 2018
In this paper, we employed polynomial chaos (PC) expansions to understand earthquake rupture model responses to random fault plane properties. A sensitivity analysis based on our PC surrogate model suggests that the hypocenter location plays a ...
H. Cruz-Jiménez, G. Li, P. M. Mai, I. Hoteit, O. M. Knio, O. M. Knio   +5 more
doaj   +1 more source

Aerodynamic Performance Uncertainty Analysis and Optimization of a Conventional Axisymmetric Vehicle Based on Parallel Polynomial Chaos Expansions

Aerospace, 2022
In this study, the aerodynamic uncertainty analysis and optimization of a conventional axisymmetric vehicle with an aerodynamic configuration were investigated.
Xun Peng, Hao Zhu, Dajun Xu, Mingyang Xiao, Weizong Wang, Guobiao Cai   +5 more
doaj   +1 more source

Application of uncertainty design optimization based on polynomial chaos expansions and maximum entropy method in ship design

Zhongguo Jianchuan Yanjiu, 2023
ObjectivesThe key to uncertainty design optimization (UDO) is uncertainty quantification (UQ), but the traditionally used Monte Carlo (MC) method can be time-consuming and computationally expensive.
Xiao WEI, Heng LI, Chenran HUANG
doaj   +1 more source

Multi-Fidelity Sparse Polynomial Chaos and Kriging Surrogate Models Applied to Analytical Benchmark Problems

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, Dean Bryson, Phil Beran   +2 more
doaj   +1 more source

STOCHASTIC POLYNOMIAL CHAOS EXPANSIONS TO EMULATE STOCHASTIC SIMULATORS

International Journal for Uncertainty Quantification, 2023
In the context of uncertainty quantification, computational models are required to be repeatedly evaluated. This task is intractable for costly numerical models. Such a problem turns out to be even more severe for stochastic simulators, the output of which is a random variable for a given set of input parameters.
Zhu, Xujia, Sudret, Bruno; id_orcid0000-0002-9501-7395   +1 more
openaire   +3 more sources

Combining polynomial chaos expansions and genetic algorithm for the coupling of electrophysiological models [PDF]

, 2019
The number of computational models in cardiac research has grown over the last decades. Every year new models with di erent assumptions appear in the literature dealing with di erences in interspecies cardiac properties.
A Mahajan, AL Hodgkin, BA Lawson, BA Lawson, CM Armstrong, D Xiu, F Bezanilla, GW Beeler, H Li, J Feinberg, JR Terkildsen, K Yanagihara, MA Tatang, Marco Ratto, P Hauseux, S Gattoni, SV Pandit, VG Eck   +17 more
core   +2 more sources

MECHANICAL STRUCTURAL RELIABILITY ANALYSIS BASED ON POLYNOMIAL CHAOS EXPANSIONS

Jixie qiangdu, 2022
Reliability is one of important index in the analysis and evaluation of mechanical structure. Aiming at the problems of various failure modes and low efficiency of reliability evaluation for complex mechanical structures, the reliability analysis method ...
WANG ZhiMing, ZHENG Lei, ZHANG LuXi, YUAN Hao, LIU WeiMin   +4 more
doaj  

Uncertainty quantification in the design of wireless power transfer systems

Open Physics, 2020
The paper addresses the uncertainty quantification of physical and geometrical material parameters in the design of wireless power transfer systems. For 3D complex systems, a standard Monte Carlo cannot be directly used to extract statistical quantities.
Pei Yao, Pichon Lionel, Bensetti Mohamed, Le-Bihan Yann   +3 more
doaj   +1 more source