Robust Physics‐Informed Neural Network Approach for Estimating Heterogeneous Elastic Properties from Noisy Displacement Data

Abstract Accurately estimating spatially heterogeneous elasticity parameters, particularly Young's modulus and Poisson's ratio, from noisy displacement measurements remains a significant challenge in inverse elasticity problems. Existing inverse estimation techniques are often limited by instability...

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Detalles Bibliográficos

Principais autores:	Tatthapong Srikitrungruang, Sina Aghaee Dabaghan Fard, Matthew Lemon, Jaesung Lee, Yuxiao Zhou
Formato:	Artigo
Idioma:	Inglês
Publicado:	Wiley 2025-12-01
Series:	Advanced Science
Assuntos:	elastography inverse problem mechanical properties estimation noisy measurement data physic‐informed neural network
Acceso en liña:	https://doi.org/10.1002/advs.202508445
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