Sediments and Subgrid: A Great Combination

Long term morphodynamic simulations are used for predicting the impact of climate change and human interventions in our estuarine and coastal regions. The accuracy of this type of simulations suffers generally from low resolution grids. Eventhough high resolution bathymetry data is increasingly more available thanks to new measurement techniques...

Large eddy simulation for turbulent non-premixed fuel-rich combustion in a cylindrical combustor

In this work we investigate turbulent non-premixed combustion, including species concentrations and temperature, in a model of 3D cylindrical combustor. Gaseous propane (C3H8) and preheated air with temperature of 773K are injected through the combustor inlet. A Large Eddy Simulation (LES) technique is applied to solve the governing equations of...

Stabilized FEM for incompressible flow: A critical review and new trends

The numerical solution of the nonstationary, incompressible Navier-Stokes model can be split into linearized auxiliary problems of Oseen type. We present in a unique way different stabilization techniques of finite element schemes on isotropic and hybrid meshes. First we describe the state-of-the-art for the classical residual-based SUPG/PSPG...

Numerical Methods for the Optimization of Nonlinear Residual-Based Sungrid-Scale Models Using the Variational Germano Identity

The Variational Germano Identity [1, 2] is used to optimize the coefficients of residual-based subgrid-scale models that arise from the application of a Variational Multiscale Method [3, 4]. It is demonstrated that numerical iterative methods can be used to solve the Germano relations to obtain values for the parameters of subgrid-scale models...

Direct Numerical Simulation and Large-Eddy Simulation of wake vortices: Going from laboratory conditions to flight conditions

This paper aims at presenting DNS and LES as applied to the simulation of vortex wakes: in laboratory conditions (moderate to medium Reynolds numbers) and up to real aircraft conditions (high to very high Reynolds numbers). Only incompressible flows are considered. DNS and LES are able to capture complex 3-D physics provided one uses high...

Accuracy and efficiency in numerical river modelling: Investigating the large effects of seemingly small numerical choices

A river engineer is challenged with the task of setting up an appropriate model for a certain application. The model needs to provide suitable answers to the questions asked (i.e. be effective) and needs to do this within the available time (i.e. be efficient). To set up such a model with sufficient accuracy and certainty, a modeller needs to...

Stochastic convection parameterization with Markov Chains in an intermediate-complexity GCM

Conditional Markov chain (CMC) models have proven to be promising building blocks for stochastic convection parameterizations. In this paper, it is demonstrated how two different CMC models can be used as mass flux closures in convection parameterizations. More specifically, the CMC models provide a stochastic estimate of the convective area...

A finite volume approach for shallow water flow accounting for high-resolution bathymetry and roughness data

This study presents a finite volume hydrodynamic model for shallow water flow that computes on a coarse grid, but accounts for high-resolution bathymetry and roughness variations on a subgrid. The detailed information can be incorporated by using the assumption of a uniform flow direction and a uniform friction slope within a part of a coarse...

Stochastic parameterization of convective area fractions with a multicloud model inferred from observational data

Observational data of rainfall from a rain radar in Darwin, Australia, are combined with data defining the large-scale dynamic and thermodynamic state of the atmosphere around Darwin to develop a multicloud model based on a stochastic method using conditional Markov chains. The authors assign the radar data to clear sky, moderate congestus,...

Advancing Artificial Neural Network Parameterization for Atmospheric Turbulence Using a Variational Multiscale Model

Data-driven parameterizations offer considerable potential for improving the fidelity of General Circulation Models. However, ensuring that these remain consistent with the governing equations while still producing stable simulations remains a challenge. In this paper, we propose a combined Variational-Multiscale (VMS) Artificial Neural...

Boosted robustness of semi-implicit subgrid methods for shallow water flash floods in hills

The widespread availability of high-resolution Digital Elevation Models (DEM), has led to the development of subgrid numerical modeling techniques, based on Shallow Water Equations (SWE). Detailed DEM data is clustered as much as possible within a coarse grid cell that is preferably much larger than a raster pixel. This has considerable...

Efficient non-hydrostatic modelling of 3D wave-induced currents using a subgrid approach

Wave-induced currents are an ubiquitous feature in coastal waters that can spread material over the surf zone and the inner shelf. These currents are typically under resolved in non-hydrostatic wave-flow models due to computational constraints. Specifically, the low vertical resolutions adequate to describe the wave dynamics – and required to...

Intercomparison of Large-Eddy Simulations of the Antarctic Boundary Layer for Very Stable Stratification

In polar regions, where the boundary layer is often stably stratified, atmospheric models produce large biases depending on the boundary-layer parametrizations and the parametrization of the exchange of energy at the surface. This model intercomparison focuses on the very stable stratification encountered over the Antarctic Plateau in 2009. Here...

Addressing the Grid-Size Sensitivity Issue in Large-Eddy Simulations of Stable Boundary Layers

We have identified certain fundamental limitations of a mixing-length parametrization used in a popular turbulent kinetic energy-based subgrid-scale model. Replacing this parametrization with a more physically realistic one significantly improves the overall quality of the large-eddy simulation (LES) of stable boundary layers. For the range...

Addressing the Grid size Sensitivity Issue in Large eddy Simulations of Stable Boundary Layers

In current study, several fundamental and inherent problems in original Deardorff subgrid model are identified under stably stratified condition. It is found that the mixing length parameterization in this subgrid model is at the root of a long trouble problem of grid size sensitivity in large-eddy simulation (LES). A new formulation of mixing...

A Machine Learning Approach to Unresolved-Scale Modeling for Burgers’ Equation

This thesis is part of a greater effort to use machine learning for the development of flexible and universal unresolved-scale models in large eddy simulation (LES). The novelty in the current work is that a neural network learns to predict the integral forms of the unresolved-scale terms directly without a priori assumptions on the underlying...

Explicit Algebraic Subgrid-Scale Stress Model for Homogeneous Turbulence

The whole construct of explicit algebraic Reynolds stress models, as they are known in RANS, is based on the weak equilibrium assumption. By employing this assumption, and in addition, incorporating models for terms in the Reynolds stress transport equations, the system of six partial differential equations can be simplified to an algebraic form...

Tidally- and Wind-Driven Horizontal Flow Patterns on Intertidal Flats in the Wadden Sea: An Assessment using Subgrid Modeling Technique

The Wadden Sea is of great ecological importance. Key elements in the Wadden Sea are the extensive intertidal flats. These contain vast amounts of life, serve as feeding grounds for millions of birds, and provide ecosystem services such as coastal protection. It follows that it is important to be able to understand and predict how these vital...