Physics-Informed Neural Networks for Structural Degradation Modeling

Jilke, Lukas and Raddatz, Florian and Hosters, Norbert and Behr, Marek and Wende, Gerko (2023) Physics-Informed Neural Networks for Structural Degradation Modeling. 10th GACM Colloquium on Computational Mechanics, 10.-13. Sept. 2023, Wien, Österreich.

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Item URL in elib:

https://elib.dlr.de/197331/

Document Type:

Conference or Workshop Item (Poster)

Title:

Physics-Informed Neural Networks for Structural Degradation Modeling

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Jilke, Lukas	UNSPECIFIED	https://orcid.org/0000-0001-6879-3279	UNSPECIFIED
Raddatz, Florian	UNSPECIFIED	https://orcid.org/0000-0002-0660-7650	UNSPECIFIED
Hosters, Norbert	RWTH Aachen University	UNSPECIFIED	UNSPECIFIED
Behr, Marek	RWTH Aachen University	UNSPECIFIED	UNSPECIFIED
Wende, Gerko	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

Date:

September 2023

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

Physics-Informed Neural Networks, PINN, degradation

Event Title:

10th GACM Colloquium on Computational Mechanics

Event Location:

Wien, Österreich

Event Type:

international Conference

Event Dates:

10.-13. Sept. 2023

Organizer:

German Association for Computational Mechanics

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Aeronautics

HGF - Program Themes:

Efficient Vehicle

DLR - Research area:

Aeronautics

DLR - Program:

L EV - Efficient Vehicle

DLR - Research theme (Project):

L - Digital Technologies

Location:

Aachen

Institutes and Institutions:

Institute of Maintenance, Repair and Overhaul > Process Optimisation and Digitalisation

Deposited By:

Jilke, Lukas

Deposited On:

18 Sep 2023 07:00

Last Modified:

18 Sep 2023 07:00

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