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Human mobility, enabled by diverse transportation modes, is fundamental to urban functionality. Studying these movements across scales-from microscopic to macroscopic-yields valuable insights into urban dynamics. Local adaptation and…

Disordered Systems and Neural Networks · Physics 2026-05-21 Babak Benam , Abolfazl Ramezanpour

This paper addresses congested transport, which can be described, at macroscopic scales, by a continuity equation with a pressure variable generated from the hard-congestion constraint (maximum value of the density). The main goal of the…

Analysis of PDEs · Mathematics 2024-05-27 Inwon Kim , Antoine Mellet , Jeremy Sheung-Him Wu

We propose a fully discrete variational scheme for nonlinear evolution equations with gradient flow structure on the space of finite Radon measures on an interval with respect to a generalized version of the Wasserstein distance with…

Numerical Analysis · Mathematics 2016-09-29 Jonathan Zinsl , Daniel Matthes

This paper concerns the so-called diffusion in the curl of the 2d Gaussian free field, and its generalization to higher dimensions $n \geq 2$, building on the scale-by-scale homogenization approach developed recently by Chatzigeorgiou,…

Probability · Mathematics 2025-11-20 Peter S. Morfe , Felix Otto , Christian Wagner

Motivated by pedestrian modelling, we study evolution of measures in the Wasserstein space. In particular, we consider the Cauchy problem for a transport equation, where the velocity field depends on the measure itself. We deal with…

Analysis of PDEs · Mathematics 2012-06-06 Benedetto Piccoli , Francesco Rossi

Foundations of a new projection-based model reduction approach for convection dominated nonlinear fluid flows are summarized. In this method the evolution of the flow is approximated in the Lagrangian frame of reference. Global basis…

Fluid Dynamics · Physics 2021-10-05 Rambod Mojgani , Maciej Balajewicz

Diffeomorphic matching (only one of several names for this technique) is a technique for non-rigid registration of curves and surfaces in which the curve or surface is embedded in the flow of a time-series of vector fields. One seeks the…

Numerical Analysis · Mathematics 2009-11-13 C. J. Cotter

We study the problem of lateral diffusion on a static, quasi-planar surface generated by a stationary, ergodic random field possessing rapid small-scale spatial fluctuations. The aim is to study the effective behaviour of a particle…

Probability · Mathematics 2014-02-03 A. B. Duncan

We study the effect of turbulence on a sedimenting layer of particles by means of direct numerical simulations. A Lagrangian model in which particles are considered as tracers with an additional downward settling velocity is integrated…

Fluid Dynamics · Physics 2020-07-08 Alessandro Sozza , Gabor Drotos , Emilio Hernández-García , Cristóbal López

We introduce a novel spatio-temporal discretization for nonlinear Fokker-Planck equations on the multi-dimensional unit cube. This discretization is based on two structural properties of these equations: the first is the representation as a…

Numerical Analysis · Mathematics 2016-01-11 Oliver Junge , Daniel Matthes , Horst Osberger

We adapt the Gradient Discretisation Method (GDM), originally designed for elliptic and parabolic partial differential equations, to the case of a linear scalar hyperbolic equations. This enables the simultaneous design and convergence…

Numerical Analysis · Mathematics 2019-10-28 Jérôme Droniou , Robert Eymard , T. Gallouët , R. Herbin

We present a perturbation theory by extending a prescription due to Feynman for computing the probability density function for the random flight motion. The method can be applied to a wide variety of otherwise difficult circumstances. The…

Classical Physics · Physics 2007-05-23 S. Tim Hatamian

Particle-based variational inference offers a flexible way of approximating complex posterior distributions with a set of particles. In this paper we introduce a new particle-based variational inference method based on the theory of…

Machine Learning · Statistics 2019-05-16 Luca Ambrogioni , Umut Guclu , Marcel van Gerven

We present a numerical investigation of two-dimensional decaying turbulence in the Lagrangian framework. Focusing on single particle statistics, we investigate Lagrangian trajectories in a freely evolving turbulent velocity field. The…

Fluid Dynamics · Physics 2009-11-13 Michael Wilczek , Oliver Kamps , Rudolf Friedrich

When expressed in Lagrangian variables, the equations of motion for compressible (barotropic) fluids have the structure of a classical Hamiltonian system in which the potential energy is given by the internal energy of the fluid. The…

Analysis of PDEs · Mathematics 2021-12-21 Thomas Gallouët , Quentin Merigot , Andrea Natale

A new Lagrangian particle method for solving Euler equations for compressible inviscid fluid or gas flows is proposed. Similar to smoothed particle hydrodynamics (SPH), the method represents fluid cells with Lagrangian particles and is…

Numerical Analysis · Mathematics 2016-03-21 Hsin-Chiang Chen , Roman Samulyak , Wei Li

This article performs a unified convergence analysis of a variety of numerical methods for a model of the miscible displacement of one incompressible fluid by another through a porous medium. The unified analysis is enabled through the…

Numerical Analysis · Mathematics 2018-03-07 Jérôme Droniou , Robert Eymard , Alain Prignet , Kyle S. Talbot

The Eulerian-Lagrangian approach based on Large-Eddy Simulation (LES) is one of the most promising and viable numerical tools to study turbulent dispersed flows when the computational cost of Direct Numerical Simulation (DNS) becomes too…

Fluid Dynamics · Physics 2017-06-02 Alessio Innocenti , Cristian Marchioli , Sergio Chibbaro

The primary emphasis of this work is the development of a finite element based space-time discretization for solving the stochastic Lagrangian averaged Navier-Stokes (LANS-$\alpha$) equations of incompressible fluid turbulence with…

Numerical Analysis · Mathematics 2021-11-01 Jad Doghman , Ludovic Goudenège

We show how to learn discrete field theories from observational data of fields on a space-time lattice. For this, we train a neural network model of a discrete Lagrangian density such that the discrete Euler--Lagrange equations are…

Numerical Analysis · Mathematics 2024-01-10 Christian Offen , Sina Ober-Blöbaum
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