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The immersed boundary method is an approach to fluid-structure interaction that uses a Lagrangian description of the structural deformations, stresses, and forces along with an Eulerian description of the momentum, viscosity, and…

Numerical Analysis · Mathematics 2017-02-27 Boyce E. Griffith , Xiaoyu Luo

We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for…

Soft Condensed Matter · Physics 2023-02-28 Paul J. Atzberger

We solve an inverse problem for fluid particle pair-statistics: we show that a time sequence of probability density functions (PDF's) of separations can be exactly reproduced by solving the diffusion equation with a suitable time-dependent…

Fluid Dynamics · Physics 2015-06-16 Gregory L. Eyink , Damien Benveniste

Fluid deformation and strain history are central to wide range of fluid mechanical phenomena ranging from fluid mixing and particle transport to stress development in complex fluids and the formation of Lagrangian coherent structures…

Fluid Dynamics · Physics 2025-10-03 Daniel R. Lester , Marco Dentz , Tanguy Le Borgne , Felipe P. J. de Barros

The Lagrangian approach is natural to study issues of turbulent dispersion and mixing. We propose in this work a general Lagrangian stochastic model including velocity and acceleration as dynamical variables for inhomogeneous turbulent…

Fluid Dynamics · Physics 2020-05-01 Alessio Innocenti , Nicolas Mordant , Nick Stelzenmuller , Sergio Chibbaro

We consider the statistics for the vorticity field in two-dimensional homogeneous isotropic turbulence (HIT). First, we exploit the invariance properties to derive dimensionally reduced governing equations for the one-point and two-point…

Fluid Dynamics · Physics 2026-04-20 Qian Huang , Simon Görtz , Paul Hollmann , Johannes Conrad , Christian Rohde , Martin Oberlack

A computational method based on the non-linear Gaussian process (GP), known as deep Gaussian processes (deep GPs) for uncertainty quantification & propagation in modelling of flow through heterogeneous porous media is presented. The method…

Machine Learning · Statistics 2020-11-06 A. Daneshkhah , O. Chatrabgoun , M. Esmaeilbeigi , T. Sedighi , S. Abolfathi

Fusing probabilistic information is a fundamental task in signal and data processing with relevance to many fields of technology and science. In this work, we investigate the fusion of multiple probability density functions (pdfs) of a…

Signal Processing · Electrical Eng. & Systems 2023-01-20 Günther Koliander , Yousef El-Laham , Petar M. Djurić , Franz Hlawatsch

A cascade model is described based on multiplier distributions determined from 3D direct numerical simulations (DNS) of turbulent particle laden flows, which include two-way coupling between the phases at global mass loadings equal to…

Astrophysics · Physics 2015-06-30 Robert C. Hogan , Jeffrey N. Cuzzi

Current supercomputers often have a heterogeneous architecture using both CPUs and GPUs. At the same time, numerical simulation tasks frequently involve multiphysics scenarios whose components run on different hardware due to multiple…

Computational Engineering, Finance, and Science · Computer Science 2024-12-10 Samuel Kemmler , Christoph Rettinger , Ulrich Rüde , Pablo Cuéllar , Harald Köstler

The statistical properties of the $E \times B$ flux in different types of plasma turbulence simulations are investigated using probability density distribution functions (PDF). The physics included in the models ranges from two dimensional…

Plasma Physics · Physics 2009-11-10 Volker Naulin , Odd Erik Garcia , Anders Henry Nielsen , Jens Juul Rasmussen

A phase-field method for unstructured grids that is accurate, conservative, and robust is proposed in this work. The proposed method also results in bounded transport of volume fraction, and the interface thickness adapts automatically to…

Fluid Dynamics · Physics 2023-10-18 Hanul Hwang , Suhas S. Jain

We explore the application of the reference map technique, originally developed for the Eulerian simulation of solid mechanics, in Lagrangian kinematics of fluid flows. Unlike traditional methods based on explicit particle tracking, the…

Fluid Dynamics · Physics 2024-12-04 Imran Hayat , Ryan T. Black , George Ilhwan Park

Bayesian estimation strategies represent the most fundamental formulation of the state estimation problem available, and apply readily to nonlinear systems with non-Gaussian uncertainties. The present paper introduces a novel method for…

Optimization and Control · Mathematics 2013-01-22 T R Bewley , A S Sharma

In this paper, we propose an approach for simulating wall-bounded incompressible turbulent flows by integrating the technology of random vortex method with the core principles of large-eddy simulations (LES). In particular, we employ the…

Fluid Dynamics · Physics 2025-11-11 Zihao Guo , Zhongmin Qian

We present a computational framework for modeling large-scale particle-laden flows in complex domains with the goal of enabling simulations in medical-image derived patient specific geometries. The framework is based on a volume-filtered…

Fluid Dynamics · Physics 2023-11-28 Abhilash Reddy Malipeddi , C. Alberto Figueroa , Jesse Capecelatro

In the present article, novel Coarse-Graining (CG) algorithms for the Eulerian-Lagrangian (EL) simulation of particle-laden flows are proposed. These include different variants of Reproducing Kernel Particle Methods (RKPM) and an extended…

Fluid Dynamics · Physics 2025-11-12 H. Eshraghi , E. Amani , M. Saffar-Avval

We study statistical properties of two-dimensional turbulent flows. Three systems are considered: the Navier-Stokes equation, surface quasi-geostrophic flow, and a model equation for thermal convection in the Earth's mantle. Direct…

chao-dyn · Physics 2009-10-31 Norbert Schorghofer

Predicting particle transport in complex flows is traditionally achieved by solving the Navier-Stokes equations. While various numerical and experimental methods exist, they typically require deep physical insights and incur high…

Fluid Dynamics · Physics 2025-11-03 Jingdi Wan , Hongping Wang , Bo Liu , Xiaolei Yang , Xiaodong Hu , Shengze Cai , Guowei He , Yang Liu

In this paper, we present a novel interface-driven adaptive variational procedure using a fully Eulerian description of fluid-structure interaction. The proposed fully-Eulerian procedure involves a fixed background unstructured mesh on…

Computational Physics · Physics 2022-02-08 Biswajeet Rath , Xiaoyu Mao , Rajeev K. Jaiman