A physics-embedded deep-learning framework for efficient multi-fidelity modeling applied to guided wave based structural health monitoring

Health monitoring of structures using ultrasonic guided waves is an evolving technology with potential applications in monitoring pipelines, civil bridges, and aircraft components. However, the sensitivity of guided waves to external parameters affects the reliability of monitoring systems based on...

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Vydáno v:	Ultrasonics Ročník 141; s. 107325
Hlavní autoři:	Nerlikar, Vivek, Miorelli, Roberto, Recoquillay, Arnaud, d’Almeida, Oscar
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.07.2024
Témata:	Deep generative model Deep learning multi-fidelity modeling Digital Twin Physics embedded machine learning Simulation-to-experiment Structural health monitoring Ultrasonic guided waves Physics embedded machine learning Digital Twin Deep learning multi-fidelity modeling Deep generative model Structural health monitoring Ultrasonic guided waves Simulation-to-experiment
ISSN:	0041-624X, 1874-9968, 1874-9968
On-line přístup:	Získat plný text
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