Sökning: onr:"swepub:oai:DiVA.org:kth-317336" >
Physics-informed ne...
Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations
-
- Eivazi, Hamidreza (författare)
- KTH,Teknisk mekanik,Linné Flow Center, FLOW,Faculty of New Sciences and Technologies, University of Tehran, Tehran, 1439957131, Iran
-
- Tahani, Mojtaba (författare)
- Univ Tehran, Fac New Sci & Technol, Tehran 1439957131, Iran.
-
- Schlatter, Philipp (författare)
- KTH,Strömningsmekanik och Teknisk Akustik,Linné Flow Center, FLOW
-
visa fler...
-
- Vinuesa, Ricardo (författare)
- KTH,Strömningsmekanik och Teknisk Akustik,Linné Flow Center, FLOW
-
visa färre...
-
(creator_code:org_t)
- AIP Publishing, 2022
- 2022
- Engelska.
-
Ingår i: Physics of fluids. - : AIP Publishing. - 1070-6631 .- 1089-7666. ; 34:8
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- Physics-informed neural networks (PINNs) are successful machine-learning methods for the solution and identification of partial differential equations. We employ PINNs for solving the Reynolds-averaged Navier-Stokes equations for incompressible turbulent flows without any specific model or assumption for turbulence and by taking only the data on the domain boundaries. We first show the applicability of PINNs for solving the Navier-Stokes equations for laminar flows by solving the Falkner-Skan boundary layer. We then apply PINNs for the simulation of four turbulent flow cases, i.e., zero-pressure-gradient boundary layer, adverse-pressure-gradient boundary layer, and turbulent flows over a NACA4412 airfoil and the periodic hill. Our results show the excellent applicability of PINNs for laminar flows with strong pressure gradients, where predictions with less than 1% error can be obtained. For turbulent flows, we also obtain very good accuracy on simulation results even for the Reynolds-stress components.
Ämnesord
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Strömningsmekanik och akustik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Fluid Mechanics and Acoustics (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas