Toward neural-network-based large eddy simulation: Application to turbulent channel flow
A fully connected neural network (NN) is used to develop a subgrid-scale (SGS) model
mapping the relation between the SGS stresses and filtered flow variables in a turbulent …
mapping the relation between the SGS stresses and filtered flow variables in a turbulent …
Heterogeneous CPU+ GPU parallelization for high-accuracy scale-resolving simulations of compressible turbulent flows on hybrid supercomputers
A Gorobets, P Bakhvalov - Computer Physics Communications, 2022 - Elsevier
A heterogeneous parallel algorithm for simulation of compressible turbulent flows and its
portable software implementation are presented. The underlying numerical method is based …
portable software implementation are presented. The underlying numerical method is based …
A new hybrid recursive regularised Bhatnagar–Gross–Krook collision model for lattice Boltzmann method-based large eddy simulation
ABSTRACT A new Lattice Boltzmann collision model for large eddy simulation (LES) of
weakly compressible flows is proposed. This model, referred to as the Hybrid Recursive …
weakly compressible flows is proposed. This model, referred to as the Hybrid Recursive …
[HTML][HTML] Invariance embedded physics-infused deep neural network-based sub-grid scale models for turbulent flows
R Bose, AM Roy - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
In this paper, we present two novel physics-infused neural network (NN) architectures that
satisfy various invariance conditions for constructing efficient and robust Deep Learning (DL) …
satisfy various invariance conditions for constructing efficient and robust Deep Learning (DL) …
On the feasibility of affordable high-fidelity CFD simulations for indoor environment design and control
N Morozova, FX Trias, R Capdevila… - Building and …, 2020 - Elsevier
Computational fluid dynamics (CFD) is a reliable tool for indoor environmental applications.
However, accurate CFD simulations require large computational resources, whereas …
However, accurate CFD simulations require large computational resources, whereas …
Mathematical methodology and metallurgical application of turbulence modelling: A review
This paper focusses on three main numerical methods, ie, the Reynolds-Averaged Navier-
Stokes (RANS), Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS) …
Stokes (RANS), Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS) …
Accurate deep learning sub-grid scale models for large eddy simulations
R Bose, AM Roy - arXiv preprint arXiv:2307.10060, 2023 - arxiv.org
We present two families of sub-grid scale (SGS) turbulence models developed for large-
eddy simulation (LES) purposes. Their development required the formulation of physics …
eddy simulation (LES) purposes. Their development required the formulation of physics …
Physical consistency of subgrid-scale models for large-eddy simulation of incompressible turbulent flows
We study the construction of subgrid-scale models for large-eddy simulation of
incompressible turbulent flows. In particular, we aim to consolidate a systematic approach of …
incompressible turbulent flows. In particular, we aim to consolidate a systematic approach of …
Parallel algorithm of the NOISEtte code for CFD and CAA simulations
A Gorobets - Lobachevskii Journal of Mathematics, 2018 - Springer
This paper describes the parallel algorithm of the NOISEtte code for computational fluid
dynamics and aeroacoustics simulations. It is based on a family of higher-accuracy …
dynamics and aeroacoustics simulations. It is based on a family of higher-accuracy …
Large eddy simulation of flow over a circular cylinder with a neural-network-based subgrid-scale model
A neural-network-based large eddy simulation is performed for flow over a circular cylinder.
To predict the subgrid-scale (SGS) stresses, we train two fully connected neural network …
To predict the subgrid-scale (SGS) stresses, we train two fully connected neural network …