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When a failure occurs in a network, network operators need to recognize service impact, since service impact is essential information for handling failures. In this paper, we propose Deep learning based Service Impact Prediction (DeepSIP),…

Networking and Internet Architecture · Computer Science 2020-03-25 Yoichi Matsuo , Tatsuaki Kimura , Ken Nishimatsu

We study the creep rupture of bundles of viscoelastic fibers occurring under uniaxial constant tensile loading. A novel fiber bundle model is introduced which combines the viscoelastic constitutive behaviour and the strain controlled…

Statistical Mechanics · Physics 2019-05-15 Raul Cruz Hidalgo , Ferenc Kun , Hans. J. Herrmann

We formulate the problem of probabilistic predictions of global failure in the simplest possible model based on site percolation and on one of the simplest model of time-dependent rupture, a hierarchical fiber bundle model. We show that…

Materials Science · Physics 2009-11-11 J. Andersen , D. Sornette

Machine learning algorithms have opened a breach in the fortress of the prediction of high-dimensional chaotic systems. Their ability to find hidden correlations in data can be exploited to perform model-free forecasting of spatiotemporal…

Optics · Physics 2022-06-08 S. Coulibaly , F. Bessin , M. G. Clerc , A. Mussot

We investigate numerically and theoretically the precursory intermittent activity characterizing the preliminary phase of damage accumulation prior to failure of quasi-brittle solids. We use a minimal but thermodynamically consistent model…

Statistical Mechanics · Physics 2022-03-23 Estelle Berthier , Ashwij Mayya , Laurent Ponson

The failure time of samples of heterogeneous materials (wood, fiberglass) is studied as a function of the applied stress. It is shown that in these materials the failure time is predicted with a good accuracy by a model of microcrack…

Condensed Matter · Physics 2009-10-31 A. Guarino , S. Ciliberto , A. Garcimartin

Machine learning models using seismic emissions can predict instantaneous fault characteristics such as displacement in laboratory experiments and slow slip in Earth. Here, we address whether the acoustic emission (AE) from laboratory…

Geophysics · Physics 2022-02-09 Kun Wang , Christopher W. Johnson , Kane C. Bennett , Paul A. Johnson

All solids yield under sufficiently high mechanical loads. Below yield, the mechanical responses of all disordered solids are nearly alike, but above yield every different disordered solid responds in its own way. Brittle systems can…

Machine learning has gained widespread attention as a powerful tool to identify structure in complex, high-dimensional data. However, these techniques are ostensibly inapplicable for experimental systems where data is scarce or expensive to…

The response of amorphous materials to an applied strain can be continuous, or instead display a macroscopic stress drop when a shear band nucleates. Such discontinuous response can be observed if the initial configuration is very stable.…

Soft Condensed Matter · Physics 2018-10-17 Marko Popović , Tom W. J. de Geus , Matthieu Wyart

This study provides an in-depth analysis of time series forecasting methods to predict the time-dependent deformation trend (also known as creep) of salt rock under varying confining pressure conditions. Creep deformation assessment is…

Failed workloads that consumed significant computational resources in time and space affect the efficiency of data centers significantly and thus limit the amount of scientific work that can be achieved. While the computational power has…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-13 Jie Li , Rui Wang , Ghazanfar Ali , Tommy Dang , Alan Sill , Yong Chen

Time-dependent deformation, particularly creep, in high-temperature alloys such as Inconel 625 is a key factor in the long-term reliability of components used in aerospace and energy systems. Although Inconel 625 shows excellent creep…

Machine Learning · Computer Science 2025-12-22 Shubham Das , Kaushal Singhania , Amit Sadhu , Suprabhat Das , Arghya Nandi

Widespread processes in nature and technology are governed by the dynamical transition whereby a material in an initially solid-like state then yields plastically. Major unresolved questions concern whether any material will yield smoothly…

Statistical Mechanics · Physics 2022-11-23 Joseph Pollard , Suzanne M Fielding

Grain-boundary (GB) local stress is central to the initiation and evolution of long-term creep damage in polycrystalline superalloys. Owing to the high-dimensional nonlinear relationships between the GB stress response and multiple…

Materials Science · Physics 2026-05-18 Weichen Kong , Yanwei Dai , Yinglin Zhang , Yinghua Liu

Dynamic random access memory failures are a threat to the reliability of data centres as they lead to data loss and system crashes. Timely predictions of memory failures allow for taking preventive measures such as server migration and…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-21 Jasmin Bogatinovski , Qiao Yu , Jorge Cardoso , Odej Kao

Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time…

Data Analysis, Statistics and Probability · Physics 2015-06-04 Randall D. Peters , Martine Le Berre , Yves Pomeau

We study the non-linear dynamics and failure statistics of a coupled-field fatigue damage evolution model. We develop a methodology to derive averaged damage evolution rate laws from such models. We show that such rate laws reduce…

Applied Physics · Physics 2024-01-01 Arjun Roy , Joseph P. Cusumano

We present an extension of the continuous damage fiber bundle model to describe the gradual degradation of highly heterogeneous materials under an increasing external load. Breaking of a fiber in the model is preceded by a sequence of…

Materials Science · Physics 2009-11-13 F. Raischel , F. Kun , H. J. Herrmann

Accurately predicting machine failures in advance can decrease maintenance cost and help allocate maintenance resources more efficiently. Logistic regression was applied to predict machine state 24 hours in the future given the current…

Applications · Statistics 2018-04-18 Matthew Battifarano , David DeSmet , Achyuth Madabhushi , Parth Nabar