textabstractA multilevel Monte Carlo (MLMC) method for Uncertainty Quantification (UQ) of advection-dominated contaminant transport in a coupled Darcy–Stokes flow system is described. In particular, we focus on high-dimensional epistemic uncertainty due to an unknown permeability field in the Darcy domain that is modelled as a lognormal random field. This paper explores different numerical strategies for the subproblems and suggests an optimal combination for the MLMC estimator. We propose a specific monolithic multigrid algorithm to efficiently solve the steady-state Darcy–Stokes flow with a highly heterogeneous diffusion coefficient. Furthermore, we describe an Alternating Direction Implicit (ADI) based time-stepping for the flux-limited ...
In this work, we present, analyze, and implement a class of Multi-Level Markov chain Monte Carlo (ML...
When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and c...
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo,...
A multilevel Monte Carlo (MLMC) method for Uncertainty Quantification (UQ) of advection-dominated co...
A multigrid multilevel Monte Carlo (MGMLMC) method is developed for the stochastic Stokes-Darcy inte...
Uncertainty is ubiquitous in many areas of science and engineering. It may result from the inadequac...
We present a multilevel Monte Carlo (MLMC) method for the uncertainty quantification of variably sat...
In this paper we address the problem of the prohibitively large computational cost of ex-isting Mark...
This is the author accepted manuscript. The final version is available from Society for Industrial a...
In this paper we address the problem of the prohibitively large computational cost of existing Marko...
We address two computational challenges for numerical simulations of Darcy flow problems: rough and ...
In many models used in engineering and science, material properties are uncertain or spatially varyi...
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo,...
We extend the Multi-Level Monte Carlo (MLMC) algorithm of [19] in order to quantify uncertainty in t...
We consider two problems encountered in simulation of fluid flow through porous media. In macroscopi...
In this work, we present, analyze, and implement a class of Multi-Level Markov chain Monte Carlo (ML...
When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and c...
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo,...
A multilevel Monte Carlo (MLMC) method for Uncertainty Quantification (UQ) of advection-dominated co...
A multigrid multilevel Monte Carlo (MGMLMC) method is developed for the stochastic Stokes-Darcy inte...
Uncertainty is ubiquitous in many areas of science and engineering. It may result from the inadequac...
We present a multilevel Monte Carlo (MLMC) method for the uncertainty quantification of variably sat...
In this paper we address the problem of the prohibitively large computational cost of ex-isting Mark...
This is the author accepted manuscript. The final version is available from Society for Industrial a...
In this paper we address the problem of the prohibitively large computational cost of existing Marko...
We address two computational challenges for numerical simulations of Darcy flow problems: rough and ...
In many models used in engineering and science, material properties are uncertain or spatially varyi...
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo,...
We extend the Multi-Level Monte Carlo (MLMC) algorithm of [19] in order to quantify uncertainty in t...
We consider two problems encountered in simulation of fluid flow through porous media. In macroscopi...
In this work, we present, analyze, and implement a class of Multi-Level Markov chain Monte Carlo (ML...
When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and c...
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo,...