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Despite advances in manufacturing making metal functionally graded materials (FGMs) more common, numerical methods for predicting fracture in ductile functionally graded materials remain limited. In this work we study the crack propagation…

Materials Science · Physics 2024-12-17 Katherine Piper , Vinamra Agrawal

The free volume comprised between rough surfaces in contact governs the fluid/gas transport properties across networks of cracks and the leakage/percolation phenomena in seals. In this study, a fundamental insight into the evolution of the…

Materials Science · Physics 2016-04-19 M. Paggi , Q. -C. He

Seismic imaging from sparsely acquired data faces challenges such as low image quality, discontinuities, and migration swing artifacts. Existing convolutional neural network (CNN)-based methods struggle with complex feature distributions…

Geophysics · Physics 2024-08-01 Xingchen Shi , Shijun Cheng , Weijian Mao , Wei Ouyang

We provide numerical evidence that electronic pre-turbulent phenomena in graphene could be observed, under current experimental conditions, through detectable current fluctuations, echoing the detachment of vortices past localized…

Mesoscale and Nanoscale Physics · Physics 2012-02-01 M. Mendoza , H. J. Herrmann , S. Succi

The Nested Dirichlet Distribution (NDD) provides a flexible alternative to the Dirichlet distribution for modeling compositional data, relaxing constraints on component variances and correlations through a hierarchical tree structure. While…

Methodology · Statistics 2026-01-16 Jacob A. Turner , Monnie McGee , Bianca A. Luedeker

Many random growth models have the property that the set of discovered sites, scaled properly, converges to some deterministic set as time grows. Such results are known as shape theorems. Typically, not much is known about the shapes. For…

Machine Learning · Statistics 2020-06-26 Sebastian Rosengren

Performing electronic structure calculations for large systems, such as nanoparticles or metal clusters, via orbital based Hartree-Fock or Kohn-Sham theories is computationaly demanding. To study such systems, therefore, we have taken…

Condensed Matter · Physics 2007-05-23 Arup Banerjee , Manoj K. Harbola

We introduce a simple model for the formation of voids. In this model the underdensity of galaxies in voids is the product of two factors. The first arises from a gravitational expansion of the negative density perturbation. The second is…

Astrophysics · Physics 2009-10-31 Yasmin Friedmann , Tsvi Piran

Understanding the internal structure and spatial distribution of cosmic voids is crucial when considering them as probes of cosmology. We present recent advances in modeling void density- and velocity-profiles in real space, as well as void…

Cosmology and Nongalactic Astrophysics · Physics 2014-09-29 Nico Hamaus , P. M. Sutter , Benjamin D. Wandelt

We perform numerical simulations of large scale structure evolution in an inhomogeneous Lemaitre-Tolman-Bondi (LTB) model of the Universe. We follow the gravitational collapse of a large underdense region (a void) in an otherwise flat…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-17 David Alonso , Juan Garcia-Bellido , Troels Haugboelle , Julian Vicente

The sizes and shapes of voids in a galaxy survey depend not only on the physics of structure formation, but also on the sampling density of the survey and on the algorithm used to define voids. Using an N-body simulation with a CDM power…

Astrophysics · Physics 2009-10-31 Jason D. Schmidt , Barbara S. Ryden , Adrian L. Melott

The dynamics of materials failure is one of the most critical phenomena in a range of scientific and engineering fields, from healthcare to structural materials to transportation. In this paper we propose a specially designed deep neural…

Materials Science · Physics 2022-11-17 Yu-Chuan Hsu , Markus J. Buehler

The paper presents the results of a theoretical study of the noise shielding effect of a subsonic turbulent jet located near a rigid screen. The developed theoretical model, based on the methods of the Geometrical Theory of Diffraction…

Fluid Dynamics · Physics 2024-11-18 O. P. Bychkov , S. A. Chernyshev , S. L. Denisov , G. A. Faranosov

In this paper, we derive first-order Euler finite element discretization schemes for a time-dependent natural convection model with variable density (NCVD). The model is governed by the variable density Navier-Stokes equations coupled with…

Numerical Analysis · Mathematics 2025-05-20 Li Hang , Chenyang Li

Variability in multiple independent input parameters makes it difficult to estimate the resultant variability in the system's overall response. The Propagation of Errors and Monte-Carlo techniques are two major methods to predict the…

Other Condensed Matter · Physics 2026-04-28 Seungju Yeoa , Paul Funkenbuscha , Hesam Askari

As a companion work to [1], this Note presents a series of simple formulae and explicit results that illustrate and highlight why classical variational phase-field models cannot possibly predict fracture nucleation in elastic brittle…

Materials Science · Physics 2024-11-22 Farhad Kamarei , John E. Dolbow , Oscar Lopez-Pamies

Modelling the near-wall region of wall-bounded turbulent flows is a widespread practice to reduce the computational cost of large-eddy simulations (LESs) at high Reynolds number. As a first step towards a data-driven wall-model, a…

We investigate how material rigidity acts as a key control parameter for the failure of solids under stress. In both experiments and simulations, we demonstrate that material failure can be continuously tuned by varying the underlying…

The formation and subsequent growth of structural defects in an irradiated material can strongly influence the material's performance in technological and industrial applications. Predicting how the growth of defects affects material…

Non-technical losses (NTL) such as electricity theft cause significant harm to our economies, as in some countries they may range up to 40% of the total electricity distributed. Detecting NTLs requires costly on-site inspections. Accurate…

Machine Learning · Computer Science 2017-07-26 Patrick O. Glauner , Andre Boechat , Lautaro Dolberg , Radu State , Franck Bettinger , Yves Rangoni , Diogo Duarte