Application of Stress Inversion Method to Develop Crustal Deformation Monitor of Japanese Islands

Author(s):  
Muneo Hori ◽  
Teruyki Kato ◽  
Kenji Oguni ◽  
Takeshi Iinuma
2011 ◽  
Vol 90-93 ◽  
pp. 337-341
Author(s):  
Ran Gang Yu ◽  
Yong Tian

This paper propose genetic algorithm combined with neural networks, greatly improving the convergence rate of neural network aim at the disadvantage of the traditional BP neural network inversion method is easy to fall into local minimum and slow convergence.Finally, verified the feasibility and superiority of the above methods through the successful initial ground stress inversion of actual project.


2013 ◽  
Vol 29 (1_suppl) ◽  
pp. 81-98 ◽  
Author(s):  
Manabu Hashimoto

The 2011 Tohoku-oki earthquake generated large displacements in and around the Japanese islands that were detected by the nationwide GPS network, sea-floor geodetic surveys, and space-borne radars. The east-west extension exerted on the Japanese islands by this event induced inland events of Mw6 or larger earthquakes. Coseismic subsidence of up to 1 m was observed along the coast where subsidence was found during the interseismic period. This observation contradicts expectations based on the concept of the recurrence of inter-plate earthquakes. Therefore, postseismic motions or other large events are expected to resolve this paradox.


2001 ◽  
Vol 106 (B2) ◽  
pp. 2281-2289 ◽  
Author(s):  
Richard Lisle ◽  
Tobore Orife ◽  
Luis Arlegui

2008 ◽  
Vol 336 (1-2) ◽  
pp. 132-148
Author(s):  
Muneo Hori ◽  
Takeshi Iinuma ◽  
Teruyuki Kato

2020 ◽  
Vol 87 (11) ◽  
Author(s):  
Mark J. Chen ◽  
Wilkins Aquino ◽  
Timothy F. Walsh ◽  
Phillip L. Reu ◽  
Kyle L. Johnson ◽  
...  

Abstract We develop a generalized stress inversion technique (or the generalized inversion method) capable of recovering stresses in linear elastic bodies subjected to arbitrary cuts. Specifically, given a set of displacement measurements found experimentally from digital image correlation (DIC), we formulate a stress estimation inverse problem as a partial differential equation-constrained optimization problem. We use gradient-based optimization methods, and we accordingly derive the necessary gradient and Hessian information in a matrix-free form to allow for parallel, large-scale operations. By using a combination of finite elements, DIC, and a matrix-free optimization framework, the generalized inversion method can be used on any arbitrary geometry, provided that the DIC camera can view a sufficient part of the surface. We present numerical simulations and experiments, and we demonstrate that the generalized inversion method can be applied to estimate residual stress.


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