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The rate of fatigue crack growth in Nickle superalloys is a critical factor of safety in the aerospace industry. A machine learning approach is chosen to predict the fatigue crack growth rate as a function of the material composition,…

Disordered Systems and Neural Networks · Physics 2023-09-26 Raghunandan Pratoori

Network infrastructures are essential for the distribution of resources such as electricity and water. Typical strategies to assess their resilience focus on the impact of a sequence of random or targeted failures of network nodes or links.…

Physics and Society · Physics 2014-11-04 D. V. Stäger , N. A. M. Araújo , H. J. Herrmann

Investigating the main determinants of the mechanical performance of metals is not a simple task. Already known physical inspired qualitative relations between 2D microstructure characteristics and 3D mechanical properties can act as the…

Applications · Statistics 2020-02-05 Martina Vittorietti , Javier Hidalgo , Jilt Sietsma , Wei Li , Geurt Jongbloed

We introduce a model of fracture which includes the out-of-plane degrees of freedom necessary to describe buckling in a thin-sheet material. The model is a regular square lattice of elastic beams, rigidly connected at the nodes so as to…

Soft Condensed Matter · Physics 2007-05-23 Bjorn Skjetne , Torbjorn Helle , Alex Hansen

Predicting potential risks associated with the fatigue of key structural components is crucial in engineering design. However, fatigue often involves entangled complexities of material microstructures and service conditions, making…

Machine Learning · Computer Science 2024-02-13 Yingjie Zhao , Yong Liu , Zhiping Xu

This paper introduces a novel methodology that utilizes latency to unveil time-series dependence patterns. A customized statistical test detects memory dependence in event sequences by analyzing their inter-event time distributions.…

Econometrics · Economics 2023-09-22 Fabio Vanni , David Lambert

Time-series anomaly detection plays a vital role in monitoring complex operation conditions. However, the detection accuracy of existing approaches is heavily influenced by pattern distribution, existence of multiple normal patterns,…

Machine Learning · Computer Science 2022-02-08 Min Hu , Yi Wang , Xiaowei Feng , Shengchen Zhou , Zhaoyu Wu , Yuan Qin

We analyze the statistics of gaps ($\Delta H$) between successive avalanches in one dimensional random field Ising models (RFIMs) in an external field $H$ at zero temperature. In the first part of the paper we study the nearest-neighbour…

Disordered Systems and Neural Networks · Physics 2017-10-16 Jishnu N. Nampoothiri , Kabir Ramola , Sanjib Sabhapandit , Bulbul Chakraborty

Rock discontinuities critically govern the mechanical behavior and stability of rock masses. Their internal distributions remain largely unobservable and are typically inferred from surface-exposed discontinuities using generative…

Machine Learning · Computer Science 2025-12-02 Han Meng , Gang Mei , Hong Tian , Nengxiong Xu , Jianbing Peng

In presence of impurities, ferromagnetic and ferroelectric domain walls slide only above a finite external field. Close to this depinning threshold, they proceed by large and abrupt jumps, called avalanches, while, at much smaller field,…

Disordered Systems and Neural Networks · Physics 2017-04-12 Ezequiel E. Ferrero , Laura Foini , Thierry Giamarchi , Alejandro B. Kolton , Alberto Rosso

Dry-snow slab avalanches are considered to be the most difficult to predict, yet the deadliest avalanche types. The release of snow slab avalanches starts with a initial failure in a weak layer that may propagate across the slope until the…

We study a model of ``organized'' criticality, where a single avalanche propagates through an \textit{a priori} static (i.e., organized) sandpile configuration. The latter is chosen according to an i.i.d. distribution from a Borel…

Probability · Mathematics 2007-05-23 Marek Biskup , Philippe Blanchard , Lincoln Chayes , Daniel Gandolfo , Tyll Krueger

A framework for the generation of bridge-specific fragility utilizing the capabilities of machine learning and stripe-based approach is presented in this paper. The proposed methodology using random forests helps to generate or update…

Computational Engineering, Finance, and Science · Computer Science 2018-07-27 Sujith Mangalathu , Jong-Su Jeon

We present a detailed statistical analysis of acoustic emission time series from laboratory rock fracture obtained from different experiments on different materials including acoustic emission controlled triaxial fracture and punch-through…

Statistical Mechanics · Physics 2015-06-25 Jörn Davidsen , Sergei Stanchits , Georg Dresen

Dam breach models are commonly used to predict outflow hydrographs of potentially failing dams and are key ingredients for evaluating flood risk. In this paper a new dam breach modeling framework is introduced that shall improve the…

Computation · Statistics 2018-06-14 S. J. Peter , A. Siviglia , J. Nagel , S. Marelli , R. M. Boes , D. Vetsch , B. Sudret

Capturing the dynamics of granular flows at intermediate length scales can often be difficult. We propose studying the dynamics of contact networks as a new tool to study fracture at intermediate scales. Using experimental three-dimensional…

Soft Condensed Matter · Physics 2012-08-17 Mark Herrera , Shane McCarthy , Steven Slotterback , Emmanuel Cephas , Wolfgang Losert , Michelle Girvan

Statistical techniques play a large role in the structural health monitoring of instrumented infrastructure, such as a railway bridge constructed with an integrated network of fibre optic sensors. One possible way to reason about the…

Applications · Statistics 2018-03-23 Alastair Gregory , F. Din-Houn Lau , Liam Butler

We have numerically studied a mean-field fiber bundle model of fracture at a non-zero temperature and acted by a constant external tensile stress. The individual fibers fail (local damage) due to creep-like dynamics that lead up to a…

Statistical Mechanics · Physics 2024-02-23 Tarun Ram Kanuri , Subhadeep Roy , Soumyajyoti Biswas

This study examine the difference in the size of avalanches among industries triggered by demand shocks, which can be rephrased by control of the economy or fiscal policy, and by using the production-inventory model and observed data. We…

General Finance · Quantitative Finance 2016-04-05 Hiroyasu Inoue

The pressure strain correlation plays a critical role in the Reynolds stress transport modelling. Accurate modelling of the pressure strain correlation leads to proper prediction of turbulence stresses and subsequently the other terms of…

Fluid Dynamics · Physics 2021-03-02 J P Panda , H V Warrior
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