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Based on the convex force-motion polynomial model for quasi-static sliding, we derive the kinematic contact model to determine the contact modes and instantaneous object motion on a supporting surface given a position controlled…

Robotics · Computer Science 2017-05-31 Jiaji Zhou , J. Andrew Bagnell , Matthew T. Mason

Obtaining general relations between macroscopic properties of random assemblies, such as density, and the microscopic properties of their constituent particles, such as shape, is a foundational challenge in the study of amorphous materials.…

Soft Condensed Matter · Physics 2016-05-05 Yoav Kallus

In this paper we introduce 1-$D$ and 2-$D$ discrete models for the dynamic granular matter formation process in the form of a system of difference equations. This approach allows us to differentiate between the influx of the rolling layer…

Numerical Analysis · Mathematics 2013-12-10 Alexander Khapalov , Sergey Lapin

We present a method for guaranteed collision detection with toleranced motions. The basic idea is to consider the motion as a curve in the 12-dimensional space of affine displacements, endowed with an object-oriented Euclidean metric, and…

Computational Geometry · Computer Science 2018-07-31 Hans-Peter Schröcker , Matthias J. Weber

The random diffusion model is a continuum model for a conserved scalar density field driven by diffusive dynamics where the bare diffusion coefficient is density dependent. We generalize the model from one with a sharp wavenumber cutoff to…

Soft Condensed Matter · Physics 2015-03-13 David D. McCowan , Gene F. Mazenko

We consider two bivariate models with two-way interactions in context of risk and queueing theory. The two entities interact with each other by providing assistance but otherwise evolve independently. We focus on certain random quantities…

Probability · Mathematics 2019-11-19 Jevgenijs Ivanovs

This Letter introduces an approach for precisely designing surface friction properties using a conditional generative machine learning model, specifically a diffusion denoising probabilistic model (DDPM). We created a dataset of synthetic…

Computational Physics · Physics 2024-01-11 Even Marius Nordhagen , Henrik Andersen Sveinsson , Anders Malthe-Sørenssen

Using an adiabatic approximation method, which searches for Tomlinson model-like instabilities for a simple but still realistic model for two crystalline surfaces in the extremely light contact limit, with mobile molecules present at the…

Materials Science · Physics 2009-11-07 C. Daly , J. Zhang , J. B. Sokoloff

Many biological processes are supported by special molecules, called motor proteins or molecular motors, that transport cellular cargoes along linear protein filaments and can reversibly associate to their tracks. Stimulated by these…

Statistical Mechanics · Physics 2021-11-17 Akriti Jindal , Anatoly B. Kolomeisky , Arvind Kumar Gupta

We study the problem of parameter estimation for a univariate discretely observed ergodic diffusion process given as a solution to a stochastic differential equation. The estimation procedure we propose consists of two steps. In the first…

Statistics Theory · Mathematics 2018-04-17 Shota Gugushvili , Peter Spreij

This paper proposes a correlated random coefficient linear panel data model, where regressors can be correlated with time-varying and individual-specific random coefficients through both a fixed effect and a time-varying random shock. I…

Econometrics · Economics 2026-02-24 Ming Li

We propose a novel approach to continuum modelling of dynamics of crystal surfaces. Our model follows the evolution of an ensemble of step configurations, which are consistent with the macroscopic surface profile. Contrary to the usual…

Statistical Mechanics · Physics 2007-05-23 Navot Israeli , Daniel Kandel

Interesting data often concentrate on low dimensional smooth manifolds inside a high dimensional ambient space. Random projections are a simple, powerful tool for dimensionality reduction of such data. Previous works have studied bounds on…

Machine Learning · Statistics 2016-09-13 Subhaneil Lahiri , Peiran Gao , Surya Ganguli

Three models from statistical physics can be analyzed by employing space-time determinantal processes: (1) crystal facets, in particular the statistical properties of the facet edge, and equivalently tilings of the plane, (2)…

Statistical Mechanics · Physics 2009-11-11 Herbert Spohn

We provide a two dimensional deformation model to describe how soft squishy circular particles respond to external forces and collisions. This model involves formulating mathematical equations and algorithms for the shape of a deformed…

Soft Condensed Matter · Physics 2024-08-28 Roshan Maharana

We present a new approach for the mechanically consistent modelling and simulation of fluid-structure interactions with contact. The fundamental idea consists of combining a relaxed contact formulation with the modelling of seepage through…

Numerical Analysis · Mathematics 2022-03-02 Erik Burman , Miguel A. Fernández , Stefan Frei , Fannie M. Gerosa

Traditional laws of friction believe that the friction coefficient of two specific solids takes constant value. However, molecular simulations revealed that the friction coefficient of nanosized asperity depends strongly on contact size and…

Materials Science · Physics 2022-08-01 X. M. Liang , G. F. Wang

We propose in this paper a minimal speed-based pedestrian model for which particle dynamics are intrinsically collision-free. The speed model is an optimal velocity function depending on the agent length (i.e.\ particle diameter), maximum…

Physics and Society · Physics 2015-12-19 Antoine Tordeux , Mohcine Chraibi , Armin Seyfried

A macroscopically nominal flat surface is rough at the nanoscale level and consists of nanoasperities. Therefore, the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity…

Mesoscale and Nanoscale Physics · Physics 2020-11-05 jianqiao Hu , Hengxu Song , Stefan Sandfeld , Xiaoming Liu , Yueguang Wei

Mathematical models of biological populations commonly use discrete structure classes to capture trait variation among individuals (e.g. age, size, phenotype, intracellular state). Upscaling these discrete models into continuum descriptions…

Populations and Evolution · Quantitative Biology 2026-03-18 Eleonora Agostinelli , Keith L. Chambers , Helen M. Byrne , Mohit P. Dalwadi