Multifidelity importance sampling

B Peherstorfer, T Cui, Y Marzouk, K Willcox - Computer Methods in Applied …, 2016 - Elsevier
Estimating statistics of model outputs with the Monte Carlo method often requires a large
number of model evaluations. This leads to long runtimes if the model is expensive to …

Spectral tensor-train decomposition

D Bigoni, AP Engsig-Karup, YM Marzouk - SIAM Journal on Scientific …, 2016 - SIAM
The accurate approximation of high-dimensional functions is an essential task in uncertainty
quantification and many other fields. We propose a new function approximation scheme …

Sobol tensor trains for global sensitivity analysis

R Ballester-Ripoll, EG Paredes, R Pajarola - Reliability Engineering & …, 2019 - Elsevier
Sobol indices are a widespread quantitative measure for variance-based global sensitivity
analysis, but computing and utilizing them remains challenging for high-dimensional …

Calibration experimental design considering field response and model uncertainty

Z Hu, D Ao, S Mahadevan - Computer Methods in Applied Mechanics and …, 2017 - Elsevier
Calibration experiment design optimization (CEDO) seeks to identify the optimal values of
experimental inputs in order to maximize the obtained information within testing budget …

Quantification of airfoil geometry-induced aerodynamic uncertainties---comparison of approaches

D Liu, A Litvinenko, C Schillings, V Schulz - SIAM/ASA Journal on Uncertainty …, 2017 - SIAM
Uncertainty quantification in aerodynamic simulations calls for efficient numerical methods to
reduce computational cost, especially for uncertainties caused by random geometry …

Efficient Markov Chain Monte Carlo for combined Subset Simulation and nonlinear finite element analysis

DKE Green - Computer methods in applied mechanics and …, 2017 - Elsevier
Typical probabilistic problems in an engineering context include rare event probability
estimation for physical models where spatial autocorrelation of material property parameters …

Entropy-based adaptive design for contour finding and estimating reliability

DA Cole, RB Gramacy, JE Warner… - Journal of Quality …, 2023 - Taylor & Francis
In reliability analysis, methods used to estimate failure probability are often limited by the
costs associated with model evaluations. Many of these methods, such as multifidelity …

A surrogate modeling approach for reliability analysis of a multidisciplinary system with spatio-temporal output

Z Hu, S Mahadevan - Structural and Multidisciplinary Optimization, 2017 - Springer
Reliability analysis of a multidisciplinary system is computationally intensive due to the
involvement of multiple disciplinary models and coupling between the individual models …

Computation of electromagnetic fields scattered from objects with uncertain shapes using multilevel Monte Carlo method

A Litvinenko, AC Yucel, H Bagci… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Computational tools for characterizing electromagnetic scattering from objects with uncertain
shapes are needed in various applications ranging from remote sensing at microwave …

Computation of the response surface in the tensor train data format

S Dolgov, BN Khoromskij, A Litvinenko… - arXiv preprint arXiv …, 2014 - arxiv.org
We apply the Tensor Train (TT) approximation to construct the Polynomial Chaos Expansion
(PCE) of a random field, and solve the stochastic elliptic diffusion PDE with the stochastic …