4.7 Article

Investigations of data-driven closure for subgrid-scale stress in large-eddy simulation

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Mechanics

Turbulence Modeling in the Age of Data

Karthik Duraisamy et al.

ANNUAL REVIEW OF FLUID MECHANICS, VOL 51 (2019)

Article Physics, Fluids & Plasmas

Searching for turbulence models by artificial neural network

Masataka Gamahara et al.

PHYSICAL REVIEW FLUIDS (2017)

Article Mechanics

A neural network approach for the blind deconvolution of turbulent flows

R. Maulik et al.

JOURNAL OF FLUID MECHANICS (2017)

Article Mechanics

Deep earning in fluid dynamics

J. Nathan Kutz

JOURNAL OF FLUID MECHANICS (2017)

Article Computer Science, Interdisciplinary Applications

Machine learning strategies for systems with invariance properties

Julia Ling et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2016)

Article Multidisciplinary Sciences

Mastering the game of Go with deep neural networks and tree search

David Silver et al.

NATURE (2016)

Article Computer Science, Interdisciplinary Applications

The Johns Hopkins Turbulence Databases: An Open Simulation Laboratory for Turbulence Research

Kalin Kanov et al.

COMPUTING IN SCIENCE & ENGINEERING (2015)

Article Biotechnology & Applied Microbiology

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

Babak Alipanahi et al.

NATURE BIOTECHNOLOGY (2015)

Article Multidisciplinary Sciences

Extreme events in computational turbulence

P. K. Yeung et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2015)

Article Computer Science, Interdisciplinary Applications

High-order compact schemes for incompressible flows: A simple and efficient method with quasi-spectral accuracy

Sylvain Laizet et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2009)

Article Mechanics

Scaling properties of subgrid-scale energy dissipation

Sergei G. Chumakov

PHYSICS OF FLUIDS (2007)

Article Physics, Multidisciplinary

Ten questions concerning the large-eddy simulation of turbulent flows

SB Pope

NEW JOURNAL OF PHYSICS (2004)

Article Computer Science, Interdisciplinary Applications

Neural networks based subgrid scale modeling in large eddy simulations

F Sarghini et al.

COMPUTERS & FLUIDS (2003)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)

Article Engineering, Aerospace

Large-eddy simulations:: Where are we and what call we expect?

J Jiménez et al.

AIAA JOURNAL (2000)