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Monte Carlo Particle. FV Mesh points. Irregularly Portioned Lagrangian Monte-Carlo for Turbulent Reacting Flow Simulations. poster presentation by,. University of Pittsburgh Pittsburgh, PA, USA. National Energy Technology Laboratory Morgantown, WV, USA. Server Levent Y ı lmaz - PowerPoint PPT Presentation
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Irregularly Portioned Lagrangian Monte-Carlo for Turbulent Reacting Flow Simulationsposter presentation by,
Server Levent Yı[email protected] for Simulation and Modeling
Mehdi B. Nik Patrick H. [email protected] [email protected] Engineering and Materials Science
University of PittsburghPittsburgh, PA, USA
National Energy Technology LaboratoryMorgantown, WV, USA
Computational resources by,
AbstractHigh fidelity, feasible simulation methodologies are indispensable to modern gas-turbine design, and here we take on a novel methodology, Filtered Density Function (FDF) for large eddy simulation of turbulent reacting flow. FDF is a robust methodology which can provide very accurate predictions for a wide range flow conditions. However, it involves an expensive particle/mesh algorithm where stiff chemical reaction computations cause quite interesting, problem specific, and in most cases extremely imbalanced (a couple of orders of magnitude) computational load distribution. While FDF is established as an indispensible tool in fundamental combustion research, these computational issues prevent it to get its deserved place at level of the industrial applications. We introduce an advanced implementation which combines robust parallelization libraries, such as Zoltan, and other optimized solvers (ODEPACK), with a flexible parallelization strategy to tackle the load-imbalance barrier. We demonstrate scalability with application to a large scale, high Reynolds number combustor.
The FDF/LES Methodology
The Particle/Mesh Algorithm
The Load Balancing Problem
Irregular Decomposition Strategy & Scalability Analysis
Milestone -1: Implementation and State
Premixed Bunsen Burner
Future Milestones
Compressible Reacting Flow Equations
LES Filtering
UnclosedTerms
Direct Numerical Simulation
(DNS)
Large EddySimulation
(LES)
Reynolds AveragedSimulation
(RAS)
Filtered Density Function (FDF)
Modeling via Stochastic Diffusion Process
The following formal definition, satisfies certain normalization conditions
Marginal FDF for scalars
Scalar FDF Transport Equation
Modeled FDF Equation: Chemistry Terms are exact!
Initialization
SDE Coefficients
Interpolate from FV mesh to particles
Construct Moments on FV mesh points byEnsemble Averaging
Finite Volume Solver
Monte CarloSolver
Solution
FV Mesh points
Monte Carlo Particle
Region of High Activity
Region of Low Activity
Stiff ODE
• Particle solver fully parallel• One process runs FV solver, and only that. Scalability bottleneck!• Manual load redistribution
• Full parallelization of the FV solver (using irregular domain boundaries for structured grid). Removing the obvious scalability bottleneck
• Implement automatic load redistribution with Zoltan • Objective is 10Ks of cores!
Special Thanks!• Peyman Givi, Professor, Mechanical Engineering and
Materials Science ,University of Pittsburgh• Peter A. Strakey, Staff Scientist, National Energy
Technology Laboratory
CH4/Air φ=1Re = 24,000
Predictions
The load imbalance is due mainly to expensive stiff chemistry computations. Indeed, this is common problem with reactive flow simulations, and not specific to LES/FDF.
Data from the simulations verify the imbalance:
Conventional Uniform Decomposition (esp. with structured grid codes)
Irregular Load Balancing Decomposition
… poor load balancing
… perfect load balance at the time of Load redistribution
Good balanceuntil next
redistribution stage
Scalability
Speedup
A representative scalar fieldCPU Time spent at each “cell”