A transformer-based convolutional method to model inverse cascade in forced two-dimensional turbulence
type: Item
instance of: scholarly article
title: A transformer-based convolutional method to model inverse cascade in forced two-dimensional turbulence
author: Haochen Li
author: Jinhan Xie
author: Chi Zhang
author: Yuchen Zhang
author: Yaomin Zhao
published in: Journal of Computational Physics
publication date: 2024-12-04T00:00:00Z
Mathematics Subject Classification ID: 76Fxx
Mathematics Subject Classification ID: 76Mxx
Mathematics Subject Classification ID: 76-XX
zbMATH DE Number: 7953968
MaRDI profile type: Publication
cites work: A dynamic subgrid-scale model for compressible turbulence and scalar transport
cites work: Q4513938
cites work: Subgrid modelling for two-dimensional turbulence using neural networks
cites work: Stable \textit{a posteriori} LES of 2D turbulence using convolutional neural networks: backscattering analysis and generalization to higher \(Re\) via transfer learning
cites work: A stable and scale-aware dynamic modeling framework for subgrid-scale parameterizations of two-dimensional turbulence
cites work: Turbulent Flows
cites work: Subgrid-scale model for large-eddy simulation of isotropic turbulent flows using an artificial neural network
cites work: Inertial-range transfer in two- and three-dimensional turbulence
cites work: Stochastic and deterministic kinetic energy backscatter parameterizations for simulation of the two-dimensional turbulence
DOI: 10.1016/J.JCP.2024.113475
description: scientific article; zbMATH DE number 7953968