Results 121 to 130 of about 3,355 (214)

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HemaSphere, Volume 10, Issue S1, June 2026.
wiley   +1 more source

PolyChaos.jl - An open source Julia package for polynomial chaos expansion

, 2019
Polynomial chaos expansion (PCE) is a Hilbert space technique for random variables that alleviates uncertainty propagation. Random variables are expanded in terms of polynomials that are orthogonal relative to a given probability density function.
Mühlpfordt, Tillmann, Hagenmeyer, Veit, Faulwasser, Timm   +2 more
core   +1 more source

Uncertainty Quantification of Linearized Stress in High-Pressure Spherical Air Storage Tanks Based on Non-Intrusive Polynomial Chaos Expansion

Mathematics
The high-pressure spherical gas storage tank in a wind tunnel energy storage and gas supply system is a critical pressure-bearing component of the wind tunnel operation system.
Zehong Wu, Chunhua Liu, Fang Luo, Hongbin Zang, Qin Chen   +4 more
doaj   +1 more source

Novel Method for Error Estimation in Applications of Polynomial Chaos Expansion to Stochastic Modeling of Multi-Resonant Systems

, 2018
A novel technique for the estimation of polynomial chaos expansion (PCE) errors in multi-resonant systems is derived and demonstrated on the example of the non-intrusive PCE application to the contour integral method (CM).A novel technique for the ...
Christian Seifert, Eduard Frick, Dahl, David, Frick, Eduard, Seifert, Christian, Lindner, Marko, Schuster, Christian, David Dahl, Christian Schuster, Marko Lindner   +9 more
core   +1 more source

Using polynomial chaos expansion for wind energy

, 2018
Surrogate models are used to approximate the expensive ‘true’ simulation codes and thus have the potential to speed up the wind farm layout optimisation problem (WFLOP). One technique to make surrogate models is Polynomial Chaos Expansion (PCE).
Bailleul, Wouter, Bailleul, Wouter (author)   +1 more
core  

Reliability polynomial chaos metamodel for the dynamic behaviour of reinforced concrete bridges

Advances in Bridge Engineering
The approximation of complex engineering problems and mathematical regressions serves as the authentic inspiration behind the artificial intelligence metamodeling methods.
Hicham Lamouri, Mouna EL Mkhalet, Nouzha Lamdouar   +2 more
doaj   +1 more source

Efficient Markov Chain Monte Carlo sampling using Polynomial Chaos Expansion

, 2013
Markov Chain Monte Carlo (MCMC) methods are often used to probe the posterior probability distribution in inverse problems. This allows for computation of estimates of uncertain system responses conditioned on given observation data by means of ...
Tchelepi, Hamdi, Bazargan, Hamid, Hamid Bazargan, Mike Christie, Hamdi Tchelepi, Christie, Michael Andrew   +5 more
core   +1 more source

Combining Polynomial Chaos Expansions and Kriging

, 2014
Computer simulation has emerged as a key tool for designing and assessing engineeringsystems in the last two decades. Uncertainty quantification has becomepopular more recently as a way to model all the uncertainties affecting the systemand their impact onto its performance.In this respect meta-models (a.k.a.
Schöbi, R., Kersaudy, P., Sudret, B., Wiart, J.   +3 more
openaire   +1 more source

Gaussian Processes and Polynomial Chaos Expansion for Regression Problem: Linkage via the RKHS and Comparison via the KL Divergence. [PDF]

Entropy (Basel), 2018
Yan L, Duan X, Liu B, Xu J.
europepmc   +1 more source

Polynomial chaos expansion for sensitivity analysis of two types of transmission line models

AIP Advances
This paper presents two sensitivity analyses, one of which is for the time-domain transmission line (TL) model using the latest weight-based algorithm that is a combination of the coherence-optimal sampling (COS) and the l1-minimum problem (l1-M) and the
Weiwei Chen, Ziyang Qi, Yuhang Ji, Liping Yan, Xiang Zhao   +4 more
doaj   +1 more source