Uncertainty-aware Validation Benchmarks for Coupling Free Flow and Porous-Medium Flow

by   Farid Mohammadi, et al.

A correct choice of interface conditions and useful model parameters for coupled free-flow and porous-medium systems is vital for physically consistent modeling and accurate numerical simulations of applications. We consider the Stokes–Darcy problem with different models for the porous-medium compartment and corresponding coupling strategies: the standard averaged model based on Darcy's law with classical or generalized interface conditions, as well as the pore-network model. We study the coupled flow problems' behaviors considering a benchmark case where a pore-scale resolved model provides the reference solution and quantify the uncertainties in the models' parameters and the reference data. To achieve this, we apply a statistical framework that incorporates a probabilistic modeling technique using a fully Bayesian approach. A Bayesian perspective on a validation task yields an optimal bias-variance trade-off against the reference data. It provides an integrative metric for model validation that incorporates parameter and conceptual uncertainty. Additionally, a model reduction technique, namely Bayesian Sparse Polynomial Chaos Expansion, is employed to accelerate the calibration and validation processes for computationally demanding Stokes–Darcy models with different coupling strategies. We perform uncertainty-aware validation, demonstrate each model's predictive capabilities, and make a model comparison using a Bayesian validation metric.



There are no comments yet.


page 16


Validation and calibration of coupled porous-medium and free-flow problems using pore-scale resolved models

The correct choice of interface conditions and effective parameters for ...

Development and Realization of Validation Benchmarks

In the field of modeling, the word validation refers to simple compariso...

Effective coupling conditions for arbitrary flows in Stokes-Darcy systems

Boundary conditions at the interface between the free-flow region and th...

Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation

Geochemical processes in subsurface reservoirs affected by microbial act...

Coupling staggered-grid and vertex-centered finite-volume methods for coupled porous-medium free-flow problems

In this work, a new discretization approach for coupled free and porous-...

Model-Based Learning of Turbulent Flows using Mobile Robots

In this paper we consider the problem of model-based learning of turbule...

Partitioned Coupling vs. Monolithic Block-Preconditioning Approaches for Solving Stokes-Darcy Systems

We consider the time-dependent Stokes-Darcy problem as a model case for ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.