Sources of Bias in Particle-Mesh Methods for PDF Models for Turbulent Flows

Abstract

Numerical errors in particular bias in PDF-based particle mesh methods for turbulence modeling have been explored It is shown that bias decreases linearly with the increase of the number of particles but increases with grid refinement The fluctuations in mean fields which are fed back into the coefficients of stochastic differential equations are attributed to be the sources of bias. The Frozen Coefficient approach has been proposed and adopted to pinpoint the sources of bias in detail. These results provide guidelines for improving the numerical accuracy of PDF models for turbulent flows.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
AD1005707

Entities

People

  • Jun Xu
  • Stephen B. Pope
  • Stephen Pope

Organizations

  • Cornell University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Boundaries
  • Convergence
  • Couette Flow
  • Differential Equations
  • Diffusion
  • Equations
  • Errors
  • Flow
  • Frequency
  • Mechanical Engineering
  • Particles
  • Pressure Gradients
  • Probability Density Functions
  • Random Variables
  • Stochastic Processes
  • Turbulent Flow

Fields of Study

  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Computational Modeling and Simulation
  • Mathematics or Statistics