[PDF][PDF] Fast numerical methods for stochastic computations: a review

D **u - Communications in computational physics, 2009‏ - ece.uvic.ca
This paper presents a review of the current state-of-the-art of numerical methods for
stochastic computations. The focus is on efficient high-order methods suitable for practical …

Time capsule for geotechnical risk and reliability

M Chwała, KK Phoon, M Uzielli, J Zhang… - … and management of …, 2023‏ - Taylor & Francis
This paper is motivated by the Time Capsule Project (TCP) of the International Society for
Soil Mechanics and Geotechnical Engineering (ISSMGE). The historical developments of …

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

RK Tripathy, I Bilionis - Journal of computational physics, 2018‏ - Elsevier
State-of-the-art computer codes for simulating real physical systems are often characterized
by vast number of input parameters. Performing uncertainty quantification (UQ) tasks with …

The random feature model for input-output maps between banach spaces

NH Nelsen, AM Stuart - SIAM Journal on Scientific Computing, 2021‏ - SIAM
Well known to the machine learning community, the random feature model is a parametric
approximation to kernel interpolation or regression methods. It is typically used to …

Recent trends in the modeling and quantification of non-probabilistic uncertainty

M Faes, D Moens - Archives of Computational Methods in Engineering, 2020‏ - Springer
This paper gives an overview of recent advances in the field of non-probabilistic uncertainty
quantification. Both techniques for the forward propagation and inverse quantification of …

Inverse problems: a Bayesian perspective

AM Stuart - Acta numerica, 2010‏ - cambridge.org
The subject of inverse problems in differential equations is of enormous practical
importance, and has also generated substantial mathematical and computational …

A GF-discrepancy for point selection in stochastic seismic response analysis of structures with uncertain parameters

J Chen, J Yang, J Li - Structural Safety, 2016‏ - Elsevier
In the stochastic dynamic analysis of nonlinear structures, the strategy of point selection
plays a critical role in achieving the tradeoffs between the accuracy and efficiency. To this …

[کتاب][B] Stochastic dynamics of structures

J Li, J Chen - 2009‏ - books.google.com
In Stochastic Dynamics of Structures, Li and Chen present a unified view of the theory and
techniques for stochastic dynamics analysis, prediction of reliability, and system control of …

Optimal discretization of random fields

CC Li, A Der Kiureghian - Journal of engineering mechanics, 1993‏ - ascelibrary.org
A new method for efficient discretization of random fields (ie, their representation in terms of
random variables) is introduced. The efficiency of the discretization is measured by the …

A univariate dimension-reduction method for multi-dimensional integration in stochastic mechanics

S Rahman, H Xu - Probabilistic Engineering Mechanics, 2004‏ - Elsevier
This paper presents a new, univariate dimension-reduction method for calculating statistical
moments of response of mechanical systems subject to uncertainties in loads, material …