Parametric Compressible Flow Predictions using Physics-Informed Neural Networks

Wassing, Simon and Bekemeyer, Philipp (2022) Parametric Compressible Flow Predictions using Physics-Informed Neural Networks. 22nd ODAS: ONERA - DLR Aerospace Symposium, 2022-06-01 - 2022-06-03, Hamburg, Deutschland.

PDF - Only accessible within DLR
1MB

Item URL in elib:

https://elib.dlr.de/189704/

Document Type:

Conference or Workshop Item (Speech)

Title:

Parametric Compressible Flow Predictions using Physics-Informed Neural Networks

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Wassing, Simon	UNSPECIFIED	https://orcid.org/0009-0008-4702-1358	UNSPECIFIED
Bekemeyer, Philipp	UNSPECIFIED	https://orcid.org/0009-0001-9888-2499	UNSPECIFIED

Date:

2022

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Page Range:

pp. 1-13

Status:

Published

Keywords:

deep learning, physics-informed, machine learning, partial differential equations

Event Title:

22nd ODAS: ONERA - DLR Aerospace Symposium

Event Location:

Hamburg, Deutschland

Event Type:

international Conference

Event Start Date:

1 June 2022

Event End Date:

3 June 2022

Organizer:

DLR und Onera

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Aeronautics

HGF - Program Themes:

other

DLR - Research area:

Aeronautics

DLR - Program:

L - no assignment

DLR - Research theme (Project):

L - no assignment

Location:

Braunschweig

Institutes and Institutions:

Institute for Aerodynamics and Flow Technology > CASE, BS

Deposited By:

Wassing, Simon

Deposited On:

16 Dec 2022 09:29

Last Modified:

02 Dec 2025 13:23

Repository Staff Only: item control page