The Sparse Grids Matlab kit--a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification

C Piazzola, L Tamellini - arXiv preprint arXiv:2203.09314, 2022 - arxiv.org
The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be
used for approximating high-dimensional functions and, in particular, for surrogate-model …

Uncertainty of heterogeneous hydrogeological models in groundwater flow and land subsidence simulations–a case study in Huwei Town, Taiwan

DH Tran, SJ Wang, QC Nguyen - Engineering Geology, 2022 - Elsevier
The distribution of hydrogeological materials in a three-dimensional heterogeneous aquifer
system has a large effect on groundwater flow and land subsidence simulations. The …

Review of design parameters for discontinuous numerical modelling of excavations in the Hawkesbury Sandstone

A Keneti, M Pouragha, BA Sainsbury - Engineering Geology, 2021 - Elsevier
Within a well-established stress environment and with well-established laboratory
properties, Hawkesbury Sandstone in the Sydney region of Australia hosts, and will continue …

Algorithm 1040: The Sparse Grids Matlab Kit-a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification

C Piazzola, L Tamellini - ACM Transactions on Mathematical Software, 2024 - dl.acm.org
The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be
used for approximating high-dimensional functions and, in particular, for surrogate-model …

Nonparametric density estimation and bandwidth selection with B-spline bases: A novel Galerkin method

JL Kirkby, Á Leitao, D Nguyen - Computational Statistics & Data Analysis, 2021 - Elsevier
A general and efficient nonparametric density estimation procedure for local bases,
including B-splines, is proposed, which employs a novel statistical Galerkin method …

[HTML][HTML] Intrusive generalized polynomial chaos with asynchronous time integration for the solution of the unsteady Navier–Stokes equations

P Bonnaire, P Pettersson, CF Silva - Computers & Fluids, 2021 - Elsevier
Generalized polynomial chaos provides a reliable framework for many problems of
uncertainty quantification in computational fluid dynamics. However, it fails for long-time …

Stochastic inverse modeling and parametric uncertainty of sediment deposition processes across geologic time scales

SE Patani, GM Porta, V Caronni, P Ruffo… - Mathematical …, 2021 - Springer
In this work an integrated methodological and operational framework for diagnosis and
calibration of Stratigraphic Forward Models (SFMs) which are typically employed for the …

A generic framework for overpressure generation in sedimentary sequences under thermal perturbations

GD Lu, XG Yang, SC Qi, XL Li, PP Ding… - Computers and …, 2020 - Elsevier
Abnormal pore pressures in excess of the hydrostatic equilibrium are observed in natural
and artificial sediment systems worldwide. Such overpressure exerts a fundamental control …

Deep neural network surrogates for nonsmooth quantities of interest in shape uncertainty quantification

L Scarabosio - SIAM/ASA Journal on Uncertainty Quantification, 2022 - SIAM
We consider the point evaluation of the solution to interface problems with geometric
uncertainties, where the uncertainty in the obstacle is described by a high-dimensional …

CFD Uncertainty Quantification using PCE–HDMR: Exemplary Application to a Buoyancy-Driven Mixing Process

PJ Wenig, S Kelm, M Klein - Flow, Turbulence and Combustion, 2024 - Springer
For the investigation of uncertainties in high dimensional spaces of computationally
expensive engineering applications, reliable Uncertainty Quantification (UQ) methods are …