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Towards the True Hybrid: Physics-Informed Trainable Models for Prognostics and Health Management
Document ID
20220012458
Acquisition Source
Ames Research Center
Document Type
Presentation
Authors
Matteo Corbetta (Wyle (United States) El Segundo, California, United States)
Date Acquired
August 11, 2022
Subject Category
Computer Programming And Software
Engineering (General)
Meeting Information
Meeting: AI for Predictive Maintenance Seminar Series
Location: Virtual
Country: US
Start Date: August 15, 2022
Sponsors: RISE Research Institutes of Sweden
Funding Number(s)
CONTRACT_GRANT: 80ARC020D0010
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Peer Committee
Keywords
physics-informed machine learning
prognostics and health management

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