An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li - Physics of Fluids, 2021 - pubs.aip.org
Reynolds-averaged Navier–Stokes simulations represent a cost-effective option for practical
engineering applications, but are facing ever-growing demands for more accurate …
被引用次数：130 相关文章

An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li - Physics of fluids, 2021 - diva-portal.org
Reynolds-averaged Navier-Stokes simulations represent a cost-effective option for practical
engineering applications, but are facing ever-growing demands for more accurate …

An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li - Physics of Fluids, 2021 - pubs.aip.org
ABSTRACT Reynolds-averaged Navier–Stokes simulations represent a cost-effective option
for practical engineering applications, but are facing evergrowing demands for more …

An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li - Physics of Fluids, 2021 - cir.nii.ac.jp
抄録< jats: p> Reynolds-averaged Navier–Stokes simulations represent a cost-effective
option for practical engineering applications, but are facing ever-growing demands for more …
[PDF] researchgate.net

[PDF][PDF] An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li - 2021 - researchgate.net
ABSTRACT Reynolds-averaged Navier–Stokes simulations represent a cost-effective option
for practical engineering applications, but are facing evergrowing demands for more …

An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima… - Physics of …, 2021 - ui.adsabs.harvard.edu
Abstract Reynolds-averaged Navier-Stokes simulations represent a cost-effective option for
practical engineering applications, but are facing ever-growing demands for more accurate …
[PDF] researchgate.net

[PDF][PDF] An interpretable framework of data-driven turbulence modeling using deep neural networks

C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li - researchgate.net
ABSTRACT Reynolds-averaged Navier–Stokes simulations represent a cost-effective option
for practical engineering applications, but are facing ever-growing demands for more …