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 …
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
The distribution of hydrogeological materials in a three-dimensional heterogeneous aquifer
system has a large effect on groundwater flow and land subsidence simulations. The …
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 …
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 …
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
A general and efficient nonparametric density estimation procedure for local bases,
including B-splines, is proposed, which employs a novel statistical Galerkin method …
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 …
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 …
calibration of Stratigraphic Forward Models (SFMs) which are typically employed for the …
A generic framework for overpressure generation in sedimentary sequences under thermal perturbations
Abnormal pore pressures in excess of the hydrostatic equilibrium are observed in natural
and artificial sediment systems worldwide. Such overpressure exerts a fundamental control …
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 …
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 …
expensive engineering applications, reliable Uncertainty Quantification (UQ) methods are …