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In probability density function (PDF) methods of turbulent flows, the joint PDF of several flow variables is computed by numerically integrating a system of stochastic differential equations for Lagrangian particles. A mathematically exact…

流体动力学 · 物理学 2010-06-17 J. Bakosi

In probability density function (PDF) methods a transport equation is solved numerically to compute the time and space dependent probability distribution of several flow variables in a turbulent flow. The joint PDF of the velocity…

流体动力学 · 物理学 2010-06-04 J. Bakosi , P. Franzese , Z. Boybeyi

The joint probability density function (PDF) of turbulent velocity and concentration of a passive scalar in an urban street canyon is computed using a newly developed particle-in-cell Monte Carlo method. Compared to moment closures, the PDF…

地球物理 · 物理学 2010-03-25 J. Bakosi , P. Franzese , Z. Boybeyi

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is…

流体动力学 · 物理学 2010-03-24 J. Bakosi , P. Franzese , Z. Boybeyi

In this work, we discuss some points relevant for stochastic modelling of one- and two-phase turbulent flows. In the framework of stochastic modelling, also referred to PDF approach, we propose a new Langevin model including all viscosity…

流体动力学 · 物理学 2010-09-14 Sergio Chibbaro , Jean-Pierre Minier

Eulerian-Lagrangian models of particle-laden (multiphase) flows describe fluid flow and particle dynamics in the Eulerian and Lagrangian frameworks respectively. Regardless of whether the flow is turbulent or laminar, the particle dynamics…

We develop a new computational framework to solve the partial differential equations (PDEs) governing the flow of the joint probability density functions (PDFs) in continuous-time stochastic nonlinear systems. The need for computing the…

最优化与控制 · 数学 2019-08-08 Kenneth F. Caluya , Abhishek Halder

This article presents a rigorous analysis for efficient statistically accurate algorithms for solving the Fokker-Planck equations associated with high-dimensional nonlinear turbulent dynamical systems with conditional Gaussian structures.…

统计理论 · 数学 2017-09-19 Nan Chen , Andrew J. Majda , Xin T. Tong

Mathematical models based on probability density functions (PDF) have been extensively used in hydrology and subsurface flow problems, to describe the uncertainty in porous media properties (e.g., permeability modelled as random field).…

流体动力学 · 物理学 2020-06-01 Matteo Icardi , Marco Dentz

Conditional statistics of homogeneous isotropic turbulent flow is investigated by means of high-Reynolds number direct numerical simulations performed with $2048^3$ collocation points. Eulerian as well as Lagrangian velocity increment…

流体动力学 · 物理学 2015-05-20 Holger Homann , Daniel Schulz , Rainer Grauer

The purpose of the present paper is to derive a partial differential equation (PDE) for the single-time single-point probability density function (PDF) of the velocity field of a turbulent flow. The PDF PDE is a highly non-linear…

数学物理 · 物理学 2021-07-08 Jiawei Li , Zhongmin Qian , Mingrui Zhou

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…

流体动力学 · 物理学 2023-11-28 Abhilash Reddy Malipeddi , C. Alberto Figueroa , Jesse Capecelatro

Solving the Fokker-Planck equation for high-dimensional complex turbulent dynamical systems is an important and practical issue. However, most traditional methods suffer from the curse of dimensionality and have difficulties in capturing…

统计方法学 · 统计学 2017-12-06 Nan Chen , Andrew J. Majda

Small-scale turbulence can be comprehensively described in terms of velocity gradients, which makes them an appealing starting point for low-dimensional modeling. Typical models consist of stochastic equations based on closures for…

流体动力学 · 物理学 2024-03-01 Maurizio Carbone , Vincent J. Peterhans , Alexander S. Ecker , Michael Wilczek

We present a hybrid partitioned deep learning framework for the reduced-order modeling of fluid-structure interaction. Using the discretized Navier-Stokes in the arbitrary Lagrangian-Eulerian reference frame, we generate the full-order flow…

流体动力学 · 物理学 2021-11-02 Rachit Gupta , Rajeev Kumar Jaiman

Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to…

流体动力学 · 物理学 2024-02-07 Guilhem Balvet , Jean-Pierre Minier , Yelva Roustan , Martin Ferrand

Currently, Eulerian flow solvers are very efficient in accurately resolving flow structures near solid boundaries. On the other hand, they tend to be diffusive and to dampen high-intensity vortical structures after a short distance away…

数值分析 · 数学 2015-06-05 Artur Palha , Lento Manickathan , Carlos Simao Ferreira , Gerard van Bussel

The way particles interact with turbulent structures, particularly in regions of high vorticity and strain rate, has been investigated in simulations of homogeneous turbulence and in simple flows which have a periodic or persistent…

流体动力学 · 物理学 2012-05-28 Michael W. Reeks

We propose a novel Particle Flow Map (PFM) method to enable accurate long-range advection for incompressible fluid simulation. The foundation of our method is the observation that a particle trajectory generated in a forward simulation…

图形学 · 计算机科学 2024-05-17 Junwei Zhou , Duowen Chen , Molin Deng , Yitong Deng , Yuchen Sun , Sinan Wang , Shiying Xiong , Bo Zhu

In assumed probability density function (pdf) methods of turbulent combustion, the shape of the scalar pdf is assumed a priori and the pdf is parametrized by its moments for which model equations are solved. In non-premixed flows the beta…

流体动力学 · 物理学 2010-11-05 J. Bakosi , J. R. Ristorcelli
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