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A high-fidelity neural network-based force field, NN-F$^{3}$, is developed to cover the strain states up to material failure and the non-equilibrium, intermediate nature of fracture. Simulations of fracture in 2D crystals using NN-F$^{3}$…

Materials Science · Physics 2024-07-23 Pengjie Shi , Shizhe Feng , Zhiping Xu

This work proposes a novel theoretical framework of robust limit analysis i.e. the computation of limit loads of structures in presence of uncertainties using limit analysis and robust optimization theories. We first derive generic robust…

Optimization and Control · Mathematics 2022-03-23 Jeremy Bleyer , Vincent Leclère

This paper studies and critically discusses the construction of nonparametric confidence regions for density level sets. Methodologies based on both vertical variation and horizontal variation are considered. The investigations provide…

Statistics Theory · Mathematics 2019-03-05 Wanli Qiao , Wolfgang Polonik

Lifeline infrastructure systems such as a power transmission network in coastal regions are vulnerable to strong winds generated during tropical cyclones. Understanding the fragility of individual towers is helpful in improving the…

Systems and Control · Electrical Eng. & Systems 2021-07-14 Surender V Raj , Manish Kumar , Udit Bhatia

Iterative geostatistical seismic inversion integrates seismic and well data to infer the spatial distribution of subsurface elastic properties. These methods provide limited assessment to the spatial uncertainty of the inverted elastic…

This work introduces two Monte Carlo (MC)-based sampling methods, known as line sampling and subset simulation, to improve the performance of standard MC analyses in the context of asteroid impact risk assessment. Both techniques sample the…

Earth and Planetary Astrophysics · Physics 2020-09-28 Matteo Romano , Matteo Losacco , Camilla Colombo , Pierluigi Di Lizia

Nearly all aspects of earthquake rupture are controlled by the friction along the fault that progressively increases with tectonic forcing, but in general cannot be directly measured. We show that fault friction can be determined at any…

We propose a new adequacy test and a graphical evaluation tool for nonlinear dynamic models. The proposed techniques can be applied in any setup where parametric conditional distribution of the data is specified, in particular to models…

Statistics Theory · Mathematics 2017-06-02 Igor L. Kheifets

Notched components are commonly used in engineering structures, where stress concentration may easily lead to crack initiation and development. The main goal of this work is to develop a simple numerical method to predict the structural…

Numerical Analysis · Mathematics 2021-12-14 Kailei Wang , Baoying Shen , Mingjing Li , Leiting Dong , Satya N. Atluri

Crush curves are of fundamental importance to numerical modeling of small and porous astrophysical bodies. The empirical literature often measures them for silica grains, and different studies have used various methods, sizes, textures, and…

Fractured metal fragments with rough and irregular surfaces are often found at crime scenes. Current forensic practice visually inspects the complex jagged trajectory of fractured surfaces to recognize a ``match'' using comparative…

In this paper, we consider the problem of estimating the covariance kernel and its eigenvalues and eigenfunctions from sparse, irregularly observed, noise corrupted and (possibly) correlated functional data. We present a method based on…

Methodology · Statistics 2008-07-09 Debashis Paul , Jie Peng

Deep neural networks offer numerous potential applications across geoscience, for example, one could argue that they are the state-of-the-art method for predicting faults in seismic datasets. In quantitative reservoir characterization…

Machine Learning · Computer Science 2021-05-26 Lukas Mosser , Ehsan Zabihi Naeini

The analysis of continuously spatially varying processes usually considers two sources of variation, namely, the large-scale variation collected by the trend of the process, and the small-scale variation. Parametric trend models on latitude…

Uncertainty quantification provides quantitative measures on the reliability of candidate solutions of ill-posed inverse problems. Due to their sequential nature, Monte Carlo sampling methods require large numbers of sampling steps for…

Geophysics · Physics 2021-04-14 Ali Siahkoohi , Felix J. Herrmann

In nonparametric regression analysis, errors are possibly correlated in practice, and neglecting error correlation can undermine most bandwidth selection methods. When no prior knowledge or parametric form of the correlation structure is…

Methodology · Statistics 2025-04-29 Sisheng Liu , Xiaoli Kong

Frailty models are often the model of choice for heterogeneous survival data. A frailty model contains both random effects and fixed effects, with the random effects accommodating for the correlation in the data. Different estimation…

Methodology · Statistics 2019-09-17 Oodally Ajmal , Luc Duchateau , Estelle Kuhn

The nonlinear mechanical responses of rocks and soils to seismic waves play an important role in earthquake physics, influencing ground motion from source to site. Continuous geophysical monitoring, such as ambient noise interferometry, has…

Earthquake-induced secondary ground failure hazards, such as liquefaction and landslides, result in catastrophic building and infrastructure damage as well as human fatalities. To facilitate emergency responses and mitigate losses, the U.S.…

Computational Engineering, Finance, and Science · Computer Science 2022-04-19 Susu Xu , Joshua Dimasaka , David J. Wald , Hae Young Noh

Estimation of the covariance structure of spatial processes is of fundamental importance in spatial statistics. In the literature, several non-parametric and semi-parametric methods have been developed to estimate the covariance structure…

Methodology · Statistics 2016-11-06 Shu Yang , Zhengyuan Zhu