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Related papers: Machine Learning Approach to Earthquake Rupture Dy…

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Seismogenic plate boundaries are presumed to behave in a similar manner to a densely packed granular medium, where fault and blocks systems rapidly rearrange the distribution of forces within themselves, as particles do in slowly sheared…

Reliable earthquake forecasting methods have long been sought after, and so the rise of modern data science techniques raises a new question: does deep learning have the potential to learn this pattern? In this study, we leverage the large…

Geophysics · Physics 2023-07-06 Jonas Koehler , Wei Li , Johannes Faber , Georg Ruempker , Nishtha Srivastava

We show that the mesoscopic and transport characteristics of networks follow the same trends for the same type of the shear ruptures in terms of rupture speed while also comparing the results of three different friction experiments.The…

Geophysics · Physics 2014-01-03 H. O. Ghaffari , R. P. Young

Pulse-like ruptures arise spontaneously in many elastodynamic rupture simulations and seem to be the dominant rupture mode along crustal faults. Pulse-like ruptures propagating under steady-state conditions can be efficiently analysed…

Geophysics · Physics 2019-08-07 Nicolas Brantut , Dmitry I. Garagash , Hiroyuki Noda

Fault diagnosis of rotating machinery plays a important role for the safety and stability of modern industrial systems. However, there is a distribution discrepancy between training data and data of real-world operation scenarios, which…

Sound · Computer Science 2023-10-24 Zhongliang Chen , Zhuofei Huang , Wenxiong Kang

We report some new applications of functional complex networks on acoustic emission waveforms from frictional interfaces. Our results show that laboratory faults undergo a sequence of generic phases as well as strengthening, weakening or…

Geophysics · Physics 2014-07-29 H. O. Ghaffari , B. D. Thompson , R. P. Young

We present an adjoint-based optimization method to invert for stress and frictional parameters used in earthquake modeling. The forward problem is linear elastodynamics with nonlinear rate-and-state frictional faults. The misfit functional…

Numerical Analysis · Mathematics 2024-09-10 Vidar Stiernström , Martin Almquist , Eric M. Dunham

Faults are complex systems embedded in an evolving medium fractured by seismic ruptures. This off-fault damage zone is shown to be thermo-hydro-mechano-chemically coupled to the main fault plane by a growing number of studies. Yet,…

Geophysics · Physics 2024-10-22 Roxane Ferry , Marion Y. Thomas , Harsha S. Bhat , Pierpaolo Dubernet

Real-time simulation of elastic structures is essential in many applications, from computer-guided surgical interventions to interactive design in mechanical engineering. The Finite Element Method is often used as the numerical method of…

Machine Learning · Computer Science 2021-09-21 Alban Odot , Ryadh Haferssas , Stéphane Cotin

Post-disaster crew dispatch is a critical but computationally intensive task. Traditional mixed-integer linear programming methods often require minutes to several hours to compute solutions, leading to delays that hinder timely…

Systems and Control · Electrical Eng. & Systems 2025-09-05 Farshad Amani , Faezeh Ardali , Amin Kargarian

Computational simulations of wildfire spread typically employ empirical rate-of-spread calculations under various conditions (such as terrain, fuel type, weather). Small perturbations in conditions can often lead to significant changes in…

Machine Learning · Computer Science 2025-01-14 Andrew Bolt , Carolyn Huston , Petra Kuhnert , Joel Janek Dabrowski , James Hilton , Conrad Sanderson

Context: Financial system stability is determined by the condition of the banking system. A bank failure can destroy the stability of the financial system, as banks are subject to systemic risk, affecting not only individual banks but also…

Machine Learning · Computer Science 2025-10-09 Zuherman Rustam , Sri Hartini , Sardar M. N. Islam , Fevi Novkaniza , Fiftitah R. Aszhari , Muhammad Rifqi

We propose a theoretical model for branching instabilities in 2-dimensional fracture, offering predictions for when crack branching occurs, how multiple cracks develop, and what is the geometry of multiple branches. The model is based on…

Materials Science · Physics 2009-11-10 Eran Bouchbinder , Joachim Mathiesen , Itamar Procaccia

Disorder and long-range interactions are two of the key components that make material failure an interesting playfield for the application of statistical mechanics. The cornerstone in this respect has been lattice models of the fracture in…

Statistical Mechanics · Physics 2009-11-11 Mikko J. Alava , Phani K. V. V. Nukala , Stefano Zapperi

Metal rolling is a widespread and well-studied process, and many finite-element (FE) rolling simulations can be found in the scientific literature. However, these FE simulations are typically limited in their resolution of through-thickness…

Context: Across different domains, Artificial Neural Networks (ANNs) are used more and more in safety-critical applications in which erroneous outputs of such ANN can have catastrophic consequences. However, the development of such neural…

This study tries to develop new attenuation relationships of peak ground velocity using machine learning methods; random forest and neural network. In order to compare with the predictors obtained by machine learning, we have also…

Geophysics · Physics 2021-11-02 Junjie Wu , Yoshihisa Maruyama , Wen Liu

Friction plays a fundamental role in many natural processes, including earthquakes, landslides, and volcanic eruptions. Earthquakes occur when highly compressed fault surfaces accumulate large enough shear stresses, causing the faults to…

Materials Science · Physics 2026-02-16 Mary Agajanian , Nadia Lapusta , Anna Pandolfi , Michael Ortiz

This article surveys the growing interest in utilizing Deep Learning (DL) as a powerful tool to address challenging problems in earthquake engineering. Despite decades of advancement in domain knowledge, issues such as uncertainty in…

Machine Learning · Computer Science 2024-05-16 Yazhou Xie

In this work, a combined modelling approach for crack propagation in defective graphene is presented. Molecular dynamics (MD) simulations are used to obtain material parameters (Young's modulus and Poisson ratio) and to determine the energy…