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We present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain…

Numerical Analysis · Mathematics 2023-10-24 Eric Parish , Payton Lindsay , Timothy Shelton , John Mersch

Direct measurement of vertical and longitudinal sediment fluxes on migrating sandy bedforms are extremely difficult to perform in both the field and laboratory. In this study we use the LES--DEM (large eddy simulation--discrete element…

Geophysics · Physics 2018-03-15 Rui Sun , Heng Xiao , Kyle Strom

In this paper we propose a new method of estimation for discrete choice demand models when individual level data are available. The method employs a two-step procedure. Step 1 predicts the choice probabilities as functions of the observed…

Applications · Statistics 2020-10-19 Nick Doudchenko , Evgeni Drynkin

Even though Deep Reinforcement Learning (DRL) showed outstanding results in the fields of Robotics and Games, it is still challenging to implement it in the optimization of industrial processes like wastewater treatment. One of the…

Deep Learning (DL) has achieved unprecedented success in various application domains. Meanwhile, model pruning has emerged as a viable solution to reduce the footprint of DL models in mobile applications, without compromising their…

Hardware Architecture · Computer Science 2024-01-17 Christodoulos Peltekis , Vasileios Titopoulos , Chrysostomos Nicopoulos , Giorgos Dimitrakopoulos

In various practical situations, we encounter data from stochastic processes which can be efficiently modelled by an appropriate parametric model for subsequent statistical analyses. Unfortunately, the most common estimation and inference…

Methodology · Statistics 2022-04-12 Rohan Hore , Abhik Ghosh

In engineering applications snow often undergoes large and fast deformations. During these deformations the snow transforms from a sintered porous material into a granular material. In order to capture the fundamental mechanical behavior of…

Geophysics · Physics 2020-07-06 Thiemo Theile , Denes Szabo , Carolin Willibald , Martin Schneebeli

We investigate the generalisation performance of Distributed Gradient Descent with Implicit Regularisation and Random Features in the homogenous setting where a network of agents are given data sampled independently from the same unknown…

Machine Learning · Statistics 2020-07-02 Dominic Richards , Patrick Rebeschini , Lorenzo Rosasco

A granular system composed of frictional glass beads is simulated using the Discrete Element Method. The inter-grain forces are based on the Hertz contact law in the normal direction with frictional tangential force. The damping due to…

Geophysics · Physics 2017-12-06 Laure Lemrich , Paul A. Johnson , Robert Guyer , Xiaoping Jia , Jan Carmeliet

Recent advances in causal inference have seen the development of methods which make use of the predictive power of machine learning algorithms. In this paper, we develop novel double machine learning (DML) procedures for panel data in which…

Econometrics · Economics 2025-01-03 Paul S. Clarke , Annalivia Polselli

The numerical treatment of fluid-particle systems is a very challenging problem because of the complex coupling phenomena occurring between the two phases. Although accurate mathematical modelling is available to address this kind of…

Numerical Analysis · Mathematics 2024-03-22 Arash Hajisharifi , Rahul Halder , Michele Girfoglio , Andrea Beccari , Domenico Bonanni , Gianluigi Rozza

We develop a Discrete Element Method (DEM) for elastodynamics using polyhedral elements. We show that for a given choice of forces and torques, we recover the equations of linear elastodynamics in small deformations. Furthermore, the…

Numerical Analysis · Mathematics 2016-12-01 Laurent Monasse , Christian Mariotti

The aim of this paper is to propose a novel methodology to deal with micro-structural boundary conditions for the analysis of granular materials. The response of the granular assembly is modelled through the discrete element method (DEM),…

Soft Condensed Matter · Physics 2017-02-27 J. Liu , E. Bosco , A. S. J. Suiker

The modeling of multi-phase flow is very challenging, given the range of scales as well as the diversity of flow regimes that one encounters in this context. We revisit the discrete equation method (DEM) for two-phase flow in the absence of…

Numerical Analysis · Mathematics 2023-03-01 Marco Petrella , Remi Abgrall , Siddhartha Mishra

The entrainment of underlying erodible material by geophysical flows can significantly boost the flowing mass and increase the final deposition extent. The particle size of both the flowing material and the erodible substrate influence the…

Geophysics · Physics 2021-09-20 Eranga Dulanjalee , François Guillard , James Baker , Benjy Marks

Modeling of a dense spray regime using an Euler-Lagrange approach is challenging because of local high volume loading. A cluster of droplets, that are assumed subgrid, can lead to locally low void fractions for the fluid phase. Under these…

Fluid Dynamics · Physics 2019-10-03 Pedram Pakseresht , Sourabh V. Apte

A discrete-element method (DEM) assembly of virtual particles is calibrated to approximate the behavior of a natural sand in undrained loading. The particles are octahedral, bumpy clusters of spheres that are compacted into assemblies of…

Soft Condensed Matter · Physics 2018-12-27 Matthew R. Kuhn , Hannah E. Renken , Austin D. Mixsell , Steven L. Kramer

In large-eddy simulation (LES) of dense sprays or sprays with pronounced clustering, evaporation rates can be inaccurate when the mesh is too coarse to provide realistic boundary conditions for the widely employed single droplet evaporation…

Fluid Dynamics · Physics 2026-05-20 Ruyue Cheng , Ali Shamooni , Andreas Kronenburg , Jan Wilhelm Gärtner , Thorsten Zirwes

Rotational effects are commonly neglected when considering the dynamics of freely rising or settling isotropic particles. Here, we demonstrate that particle rotations play an important role for rising as well as for settling cylinders in…

We investigate the flow of spherical, bulk granular particles down an inclined plane mixed with small-sized spherical lubricant particles using discrete element method simulations. Predefined cohesive interaction is implemented between…

Soft Condensed Matter · Physics 2026-04-27 Sayali V. Chaudhary , Ashish V. Orpe