Nouri Gheimassi, Arash
(2018)
Self-Contained Filtered Density Function.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The filtered density function (FDF) closure is extended to a "self-contained" format to include the subgrid scale (SGS) statistics of all of the hydro-thermo-chemical variables in turbulent flows. These are the thermodynamic pressure, the specific internal energy, the velocity vector, and the composition field. In this format, the model is comprehensive and facilitates large eddy simulation (LES) of flows at both low and high compressibility levels. A transport equation is developed for the joint "pressure-energy-velocity-composition filtered mass density function (PEVC-FMDF)." In this equation, the effect of convection appears in closed form. The coupling of the hydrodynamics and thermochemistry is modeled via a set of stochastic differential equation (SDE) for each of the transport variables. This yields
a self-contained SGS closure. For demonstration, LES is conducted of a turbulent shear flow with transport of a passive scalar. The consistency of the PEVC-FMDF formulation is established, and its overall predictive capability is appraised via comparison with direct
numerical simulation (DNS) data.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
25 January 2018 |
Date Type: |
Publication |
Defense Date: |
27 September 2017 |
Approval Date: |
25 January 2018 |
Submission Date: |
17 October 2017 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
48 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Computational Modeling and Simulation |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
Large eddy simulation; filtered density function; Monte Carlo methods; compressible turbulent flows. |
Date Deposited: |
25 Jan 2018 13:37 |
Last Modified: |
25 Jan 2018 13:37 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/33265 |
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