English
Related papers

Related papers: General Lattice Model of Gradient Elasticity

200 papers

The three-dimensional elastic-plastic deformation is considered. The catastrophe theory underlies the construction of this process model. It was shown that the variety of stable states consists on elastic states and can be depicted as a…

Materials Science · Physics 2007-05-23 L. N. Maurin , I. S. Tikhomirova

In this article we propose a discrete lattice model to simulate the elastic, plastic and failure behaviour of isotropic materials. Focus is given on the mathematical derivation of the lattice elements, nodes and edges, in the presence of…

Optimization and Control · Mathematics 2015-05-12 Ioannis Dassios , Andrey Jivkov , Andrew Abu-Muharib , Peter James

Finite fields form an important chapter in abstract algebra, and mathematics in general. We aim to provide a geometric and intuitive model for finite fields, involving algebraic numbers, in order to make them accessible and interesting to a…

History and Overview · Mathematics 2017-08-31 Lucian M. Ionescu , Mina M. Zarrin

Budiansky's nonlinear shell theory is particularized to a 2D setting, and thereupon generalized to a fully nonlinear, statically and kinematically exact, theory of strain-gradient elasticity of beams. The governing equations are displayed…

Classical Physics · Physics 2022-09-27 Marcelo Epstein , Mohammadjavad Javad

We analyze nonlinearly preconditioned gradient methods for solving smooth minimization problems. We introduce a generalized smoothness property, based on the notion of abstract convexity, that is broader than Lipschitz smoothness and…

Optimization and Control · Mathematics 2025-06-18 Konstantinos Oikonomidis , Jan Quan , Emanuel Laude , Panagiotis Patrinos

We present the analytic solution of the Mode III steady-state crack in a square lattice with piecewise linear springs and Kelvin viscosity. We show how the results simplify in the limit of large width. We relate our results to a model where…

Materials Science · Physics 2009-10-31 David A. Kessler

We introduce a generalization of conventional lattice gauge theory to describe fracton topological phases, which are characterized by immobile, point-like topological excitations, and sub-extensive topological degeneracy. We demonstrate a…

Strongly Correlated Electrons · Physics 2017-01-04 Sagar Vijay , Jeongwan Haah , Liang Fu

A lattice of elastic Rayleigh rods organized in a parallelepiped geometry can be axially loaded up to an arbitrary amount without distortion and then be subject to incremental time-harmonic dynamic motion. At certain threshold levels of…

Classical Physics · Physics 2021-03-04 Giovanni Bordiga , Luigi Cabras , Andrea Piccolroaz , Davide Bigoni

In this paper, we consider linear elliptic systems from composite materials where the coefficients depend on the shape and might have the discontinuity between the subregions. We derive a function which is related to the gradient of the…

Analysis of PDEs · Mathematics 2022-06-17 Youchan Kim , Pilsoo Shin

We describe a 3D percolation-type approach to modeling of the processes of aging and certain other properties of tissues analyzed as systems consisting of interacting cells. Lattice sites are designated as regular (healthy) cells, senescent…

Statistical Mechanics · Physics 2016-07-12 Vyacheslav Gorshkov , Vladimir Privman , Sergiy Libert

Recent studies show that transformer-based architectures emulate gradient descent during a forward pass, contributing to in-context learning capabilities - an ability where the model adapts to new tasks based on a sequence of prompt…

Statistics Theory · Mathematics 2024-05-13 Karthik Duraisamy

The Galois lattice is a graphic method of representing knowledge structures. The first basic purpose in this paper is to introduce a new class of Galois lattices, called graded Galois lattices. As a direct result, one can obtain the notion…

Logic · Mathematics 2021-09-14 Reza Sotoudeh , Hamidreza Goudarzi , Ali Akbar Nikoukar

An open question in the Deep Learning community is why neural networks trained with Gradient Descent generalize well on real datasets even though they are capable of fitting random data. We propose an approach to answering this question…

Machine Learning · Computer Science 2020-02-26 Satrajit Chatterjee

This paper presents a non-linear stability analysis for dc-microgrids in both, interconnected mode and island operation with primary control. The proposed analysis is based on the fact that the dynamical model of the grid is a gradient…

Optimization and Control · Mathematics 2019-01-07 Alejandro Garces

A formal derivation of linear hydrodynamics for a granular fluid is given. The linear response to small spatial perturbations of the homogeneous reference state is studied in detail using methods of non-equilibrium statistical mechanics. A…

Statistical Mechanics · Physics 2007-05-23 James W. Dufty , Aparna Baskaran , J. Javier Brey

The majority of machine learning algorithms assumes that objects are represented as vectors. But often the objects we want to learn on are more naturally represented by other data structures such as sequences and time series. For these…

Machine Learning · Computer Science 2015-06-10 Brijnesh Jain

The Generalized Elastic Model is a linear stochastic model which accounts for the behaviour of many physical systems in nature, ranging from polymeric chains to single-file systems. If an external perturbation is exerted \emph{only} on a…

Statistical Mechanics · Physics 2013-05-14 Alessandro Taloni , Aleksei Chechkin , Joseph Klafter

The bi-continuum model composed of two interpenetrating and dynamically coupled material continua is analysed as a simplified but relatively accurate way to describe some physical phenomena in crystalline solids. The essential novelty of…

Materials Science · Physics 2007-05-23 M. Sztyren

We introduce models for viscoelastic materials, both solids and fluids, based on logarithmic stresses to capture the elastic contribution to the material response. The matrix logarithm allows to link the measures of strain, that naturally…

Analysis of PDEs · Mathematics 2024-10-10 Gennaro Ciampa , Giulio G. Giusteri , Alessio G. Soggiu

This paper shows that a wide class of effective learning rules -- those that improve a scalar performance measure over a given time window -- can be rewritten as natural gradient descent with respect to a suitably defined loss function and…

Machine Learning · Computer Science 2024-09-26 Lucas Shoji , Kenta Suzuki , Leo Kozachkov
‹ Prev 1 8 9 10 Next ›