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Related papers: Reduced order models for Lagrangian hydrodynamics

200 papers

Lagrangian turbulence lies at the core of numerous applied and fundamental problems related to the physics of dispersion and mixing in engineering, bio-fluids, atmosphere, oceans, and astrophysics. Despite exceptional theoretical,…

Building efficient, accurate and generalizable reduced order models of developed turbulence remains a major challenge. This manuscript approaches this problem by developing a hierarchy of parameterized reduced Lagrangian models for…

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly non-trivial statistical behavior, motivating the development of surrogate models…

We propose a new Nitsche-type approach for weak enforcement of normal velocity boundary conditions for a Lagrangian discretization of the compressible shock-hydrodynamics equations using high-order finite elements on curved boundaries.…

Numerical Analysis · Mathematics 2023-09-06 Nabil M. Atallah , Vladimir Z. Tomov , Guglielmo Scovazzi

This paper is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints. Specifically, we study situations where parts of the constraints…

Optimization and Control · Mathematics 2022-04-20 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz , Gerd Wachsmuth

Adjoint-based shape optimization most often relies on Eulerian flow field formulations. However, since Lagrangian particle methods are the natural choice for solving sedimentation problems in oceanography, extensions to the Lagrangian…

Fluid Dynamics · Physics 2022-09-07 Luka Schlegel , Volker Schulz

We propose a model order reduction approach to speed up the computation of seismograms, i.e. the solution of the seismic wave equation evaluated at a receiver location, for different model parameters. Our approach achieves a reduction of…

Numerical Analysis · Mathematics 2024-06-12 Rhys Hawkins , Muhammad Hamza Khalid , Matthias Schlottbom , Kathrin Smetana

Modeling Lagrangian turbulence remains a fundamental challenge due to its multiscale, intermittent, and non-Gaussian nature. Recent advances in data-driven diffusion models have enabled the generation of realistic Lagrangian velocity…

Fluid Dynamics · Physics 2025-07-28 Tianyi Li , Flavio Tuteri , Michele Buzzicotti , Fabio Bonaccorso , Luca Biferale

We focus on the numerical modelling of water waves by means of depth averaged models. We consider in particular PDE systems which consist in a nonlinear hyperbolic model plus a linear dispersive perturbation involving an elliptic operator.…

Numerical Analysis · Mathematics 2022-11-24 Davide Torlo , Mario Ricchiuto

We present an innovative numerical discretization of the equations of inviscid potential flow for the simulation of three dimensional unsteady and nonlinear water waves generated by a ship hull advancing in water. The equations of motion…

Numerical Analysis · Mathematics 2013-02-06 Andrea Mola , Luca Heltai , Antonio DeSimone

Complex network approaches have been successfully applied for studying transport processes in complex systems ranging from road, railway or airline infrastructure over industrial manufacturing to fluid dynamics. Here, we utilize a generic…

Fluid Dynamics · Physics 2017-04-05 Naoya Fujiwara , Kathrin Kirchen , Jonathan F. Donges , Reik V. Donner

Models with dominant advection always posed a difficult challenge for projection-based reduced order modelling. Many methodologies that have recently been proposed are based on the pre-processing of the full-order solutions to accelerate…

Numerical Analysis · Mathematics 2022-03-02 Davide Papapicco , Nicola Demo , Michele Girfoglio , Giovanni Stabile , Gianluigi Rozza

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

The purpose of this paper is to examine the Lagrangian stochastic modeling of the fluid velocity seen by inertial particles in a nonhomogeneous turbulent flow. A new Langevin-type model, compatible with the transport equation of the drift…

Fluid Dynamics · Physics 2009-07-01 Boris Arcen , Anne Tanière

Turbulent compressible flows are traditionally simulated using explicit time integrators applied to discretized versions of the Navier-Stokes equations. However, the associated Courant-Friedrichs-Lewy condition severely restricts the…

Computational Physics · Physics 2021-08-11 Dominik Wilde , Andreas Krämer , Dirk Reith , Holger Foysi

In this paper, we propose a mass conservative semi-Lagrangian finite difference scheme for multi-dimensional problems without dimensional splitting. The semi-Lagrangian scheme, based on tracing characteristics backward in time from grid…

Numerical Analysis · Mathematics 2016-07-26 Tao Xiong , Giovanni Russo , Jing-Mei Qiu

The present work investigates the evolution of linear perturbations of time-dependent ideal fluid flows with advected quantities, expressed in terms of the second order variations of the action corresponding to a Lagrangian defined on a…

Fluid Dynamics · Physics 2024-04-02 Darryl D. Holm , Ruiao Hu , Oliver D. Street

We introduce optimization-based full-order and reduced-order formulations of fluid structure interaction problems. We study the flow of an incompressible Newtonian fluid which interacts with an elastic body: we consider an arbitrary…

Numerical Analysis · Mathematics 2024-12-30 Tommaso Taddei , Xuejun Xu , Lei Zhang

We consider the assimilation of Lagrangian data into a primitive equations circulation model of the ocean at basin scale. The Lagrangian data are positions of floats drifting at fixed depth. We aim at reconstructing the four-dimensional…

Optimization and Control · Mathematics 2009-11-13 Maëlle Nodet

Machine learning has been successfully applied to grid-based PDE modeling in various scientific applications. However, learned PDE solvers based on Lagrangian particle discretizations, which are the preferred approach to problems with free…

Machine Learning · Computer Science 2023-10-31 Artur P. Toshev , Gianluca Galletti , Fabian Fritz , Stefan Adami , Nikolaus A. Adams