Irregularly Portioned Lagrangian Monte-Carlo for Turbulent Reacting Flow Simulations

1. 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 Yılmaz slyilmaz@pitt.edu Center for Simulation and Modeling Mehdi B. Nik Patrick H. Pisciuneri smb51@pitt.edu php8@pitt.edu Mechanical Engineering and Materials Science Computationalresources by, Abstract The Particle/Mesh Algorithm Irregular Decomposition Strategy & Scalability Analysis High 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. Conventional Uniform Decomposition (esp. with structured grid codes) Irregular Load Balancing Decomposition … poor load balancing The FDF/LES Methodology Compressible Reacting Flow Equations … perfect load balance at the time of Load redistribution Good balance until next redistribution stage Scalability Initialization SDE Coefficients Interpolate from FV mesh to particles Monte Carlo Solver Construct Moments on FV mesh points by Ensemble Averaging Finite Volume Solver Premixed Bunsen Burner Solution Large Eddy Simulation (LES) Reynolds Averaged Simulation (RAS) Direct Numerical Simulation (DNS) The Load Balancing Problem Speedup 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. LES Filtering CH4/Air φ=1 Re = 24,000 Stiff ODE Predictions Region of Low Activity Region of High Activity Unclosed Terms Filtered Density Function (FDF) The following formal definition, satisfies certain normalization conditions Data from the simulations verify the imbalance: Milestone -1: Implementation and State Future Milestones Marginal FDF for scalars • 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! Scalar FDF Transport Equation Modeling via Stochastic Diffusion Process Special Thanks! • PeymanGivi, Professor, Mechanical Engineering and Materials Science ,University of Pittsburgh • Peter A. Strakey, Staff Scientist, National Energy Technology Laboratory • Particle solver fully parallel • One process runs FV solver, and only that. Scalability bottleneck! • Manual load redistribution Modeled FDF Equation: Chemistry Terms are exact! A representative scalar field CPU Time spent at each “cell”