The Experts below are selected from a list of 596661 Experts worldwide ranked by ideXlab platform
S B Pope - One of the best experts on this subject based on the ideXlab platform.
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simulation of sandia flame d using velocity scalar filtered Density Function
AIAA Journal, 2010Co-Authors: S L Yilmaz, Peyman Givi, M R Sheikhi, S B PopeAbstract:The joint velocity―scalar filtered mass Density Function methodology is employed for large eddy simulation of Sandia National Laboratories' flame D. This is a turbulent piloted nonpremixed methane jet flame. In velocity―scalar filtered mass Density Function, the effects of the subgrid-scale chemical reaction and convection appear in closed forms. The modeled transport equation for the velocity―scalar filtered mass Density Function is solved by a hybrid finite difference/Monte Carlo scheme. For this flame, which exhibits little local extinction, a flamelet model is employed to relate the instantaneous composition to mixture fraction. The simulated results are assessed via comparison with laboratory data and show favorable agreements.
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filtered Density Function for large eddy simulation of turbulent reacting flows
Physics of Fluids, 1998Co-Authors: P J Colucci, Peyman Givi, Farhad Jaberi, S B PopeAbstract:A methodology termed the “filtered Density Function” (FDF) is developed and implemented for large eddy simulation (LES) of chemically reacting turbulent flows. In this methodology, the effects of the unresolved scalar fluctuations are taken into account by considering the probability Density Function (PDF) of subgrid scale (SGS) scalar quantities. A transport equation is derived for the FDF in which the effect of chemical reactions appears in a closed form. The influences of scalar mixing and convection within the subgrid are modeled. The FDF transport equation is solved numerically via a Lagrangian Monte Carlo scheme in which the solutions of the equivalent stochastic differential equations (SDEs) are obtained. These solutions preserve the Ito-Gikhman nature of the SDEs. The consistency of the FDF approach, the convergence of its Monte Carlo solution and the performance of the closures employed in the FDF transport equation are assessed by comparisons with results obtained by direct numerical simulation ...
Peyman Givi - One of the best experts on this subject based on the ideXlab platform.
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simulation of sandia flame d using velocity scalar filtered Density Function
AIAA Journal, 2010Co-Authors: S L Yilmaz, Peyman Givi, M R Sheikhi, S B PopeAbstract:The joint velocity―scalar filtered mass Density Function methodology is employed for large eddy simulation of Sandia National Laboratories' flame D. This is a turbulent piloted nonpremixed methane jet flame. In velocity―scalar filtered mass Density Function, the effects of the subgrid-scale chemical reaction and convection appear in closed forms. The modeled transport equation for the velocity―scalar filtered mass Density Function is solved by a hybrid finite difference/Monte Carlo scheme. For this flame, which exhibits little local extinction, a flamelet model is employed to relate the instantaneous composition to mixture fraction. The simulated results are assessed via comparison with laboratory data and show favorable agreements.
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Developments in Formulation and Application of the Filtered Density Function
Flow Turbulence and Combustion, 2006Co-Authors: T. G. Drozda, M R H Sheikhi, C. K. Madnia, Peyman GiviAbstract:An overview is presented of the state of progress in large eddy simulation of turbulent combustion via the filtered Density Function (FDF). This includes the formulations based on both the joint velocity-scalar FDF, and the marginal scalar FDF. In the former, the most up-to-date and comprehensive form of the model is presented along with its applications for LES of some relatively simple flows. In the latter, results are presented of the most recent LES of a complex turbulent flame. Both of the models are described in the context of a variable Density flow via consideration of the filtered mass Density Function (FMDF).
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filtered Density Function for subgrid scale modeling of turbulent combustion
AIAA Journal, 2006Co-Authors: Peyman Givi, M R H SheikhiAbstract:Abstract : This research was concentrated primarily on developments and applications of the filtered Density Function (FDF) for subgrid scale (SGS) modeling of turbulent reacting flows. During the past three years, this work addressed: (1) development of the joint velocity-scalar filtered mass Density Function (VSFMDF), (2) development of the joint frequency-velocity-scalar filtered mass Density Function (FVS-FMDF), and (3) implementation of the scalar filtered mass Density Function (SFMDF) and VSFMDF for large eddy simulation of complex turbulent flames. This is a final report of our activities sponsored by AFOSR under Grant FA9550-06-1-0015.
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filtered Density Function for large eddy simulation of turbulent reacting flows
Physics of Fluids, 1998Co-Authors: P J Colucci, Peyman Givi, Farhad Jaberi, S B PopeAbstract:A methodology termed the “filtered Density Function” (FDF) is developed and implemented for large eddy simulation (LES) of chemically reacting turbulent flows. In this methodology, the effects of the unresolved scalar fluctuations are taken into account by considering the probability Density Function (PDF) of subgrid scale (SGS) scalar quantities. A transport equation is derived for the FDF in which the effect of chemical reactions appears in a closed form. The influences of scalar mixing and convection within the subgrid are modeled. The FDF transport equation is solved numerically via a Lagrangian Monte Carlo scheme in which the solutions of the equivalent stochastic differential equations (SDEs) are obtained. These solutions preserve the Ito-Gikhman nature of the SDEs. The consistency of the FDF approach, the convergence of its Monte Carlo solution and the performance of the closures employed in the FDF transport equation are assessed by comparisons with results obtained by direct numerical simulation ...
Mariesa L Crow - One of the best experts on this subject based on the ideXlab platform.
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the fokker planck equation for power system stability probability Density Function evolution
IEEE Transactions on Power Systems, 2013Co-Authors: Keyou Wang, Mariesa L CrowAbstract:This paper presents an analysis of the evolution of the probability Density Function of the dynamic trajectories of a single machine infinite bus power system. The probability Density Function can be used to determine the impact of random (stochastic) load perturbations on system stability. The evolution of the state probability Density Function over time leads to several interesting observations regarding stability regions as a Function of damping parameter. The Fokker-Planck equation (FPE) is used to describe the evolution of the probability Density of the states. The FPE is solved numerically using PDE solvers (such as finite difference method). Based on the results, the qualitative changes of the stationary Density produce peak-like, ridge-like and other complicated shapes. Lastly, the numerical FPE solution combined with SMIB equivalent techniques lay the framework extended to the multimachine system.
Mustafa Mutlu - One of the best experts on this subject based on the ideXlab platform.
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application of rayleigh probability Density Function in electromagnetic wave propagation
Journal of Electrical and Electronic Engineering, 2014Co-Authors: Mustafa MutluAbstract:In this study, signal voltage obtained at the receiver is investigated by taking the Rayleigh Probability Density Function into account. Probability of received signal and occurrence of incoming signal between two levels are also studied. Success percentage, requirement of how much the receiver is to be modified and variation of voltage or power at the output with respect to time are simulated in MATLAB for various physical environments.
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minimization of the difference between the theoretical mean of the rayleigh probability Density Function and the mean obtained from its plot
Universal Journal of Electrical and Electronic Engineering, 2014Co-Authors: Mustafa MutluAbstract:In this study, the difference between the mean of the Rayleigh Probability Density Function and the mean obtained from the graph of Rayleigh Probability Density Function is minimized by changing the coefficient in the equation yielding the mean. By using various numbers of data and K values, Rayleigh Probability Density Function is plotted with the means mentioned above.
P J Colucci - One of the best experts on this subject based on the ideXlab platform.
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filtered Density Function for large eddy simulation of turbulent reacting flows
Physics of Fluids, 1998Co-Authors: P J Colucci, Peyman Givi, Farhad Jaberi, S B PopeAbstract:A methodology termed the “filtered Density Function” (FDF) is developed and implemented for large eddy simulation (LES) of chemically reacting turbulent flows. In this methodology, the effects of the unresolved scalar fluctuations are taken into account by considering the probability Density Function (PDF) of subgrid scale (SGS) scalar quantities. A transport equation is derived for the FDF in which the effect of chemical reactions appears in a closed form. The influences of scalar mixing and convection within the subgrid are modeled. The FDF transport equation is solved numerically via a Lagrangian Monte Carlo scheme in which the solutions of the equivalent stochastic differential equations (SDEs) are obtained. These solutions preserve the Ito-Gikhman nature of the SDEs. The consistency of the FDF approach, the convergence of its Monte Carlo solution and the performance of the closures employed in the FDF transport equation are assessed by comparisons with results obtained by direct numerical simulation ...
