[LCRC Accounts] Yearly Allocation Request from cfd_enginemodeling
Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Sibendu Som Project Name: cfd_enginemodeling Division: ES Project title: Computation Fluid Dynamics Modeling of Diesel Engine Processes Associated funding: DOE – Office of Vehicle Technologies Other Systems: Science: This project will use an Eulerian-Lagrangian Computation Fluid Dynamics (CFD) software called CONVERGE to model various diesel engine processes like internal nozzle flow, spray behavior, combustion and emission processes. The goal is to develop predictive nozzle flow, spray, combustion, and turbulence models for compression ignition engine fuels. Project description: The project is divided into three major phases: 1) Cavitation modeling: A two-phase cavitation modeling approach using the homogeneous relaxation method has been developed and implemented in CONVERGE. Extensive validation of the new model will be performed against experimental data available in literature and new data from Advanced photon source at Argonne. 2) Spray Modeling: Traditional Eulerian-Lagrangian spray modeling approaches are hampered by the fact that the results are not grid-independent. Grid-convergent spray modeling approaches will be developed and validated against experimental data from the Engine Combustion Network. The simulations will be performed in a constant volume combustion vessel since it is a more effective crucible for model validation 3) Turbulence Modeling: Traditionally engine simulations have been performed using the Reynolds Average Navier Stokes Equations (RANS) approach. RANS employs filtering in time to derive the governing equations for the mean state. Turbulent interactions over the full range of dynamic scales are averaged to make the calculations affordable for engineering analysis. Only the largest energy containing features in a flow are resolved and no information exists to describe broadband small-scale interactions. Thus, computational requirements for RANS are relatively low and the most affordable. However, case-by-case calibration of models is required, and stochastic processes such as cycle-to-cycle variations cannot be captured in RANS. Large Eddy Simulation (LES) directly resolves the large scale unsteady motions that account for the bulk spatial transportation, while smaller scales of the flow are removed through a filtering operation and treated by using subgrid scale (SGS) models f or reduced computational cost. By resolving the large-scale turbulence, LES can significantly improve the accuracy of flow predictions compared to RANS. A dynamic structure based LES model will be developed and the results will be compared against RANS. The CONVERGE software has been observed to scale well up to 256 processors and full-cycle engine simulations. Project URL: http://www.transportation.anl.gov/engines/multi_dim_model_home.html Current FY Hours Used: undetermined amount New FY Requested allocation: 499000 Q1: 125000 Q2: 125000 Q3: 125000 Q4: 124000 Justification: Thank You, The LCRC Accounts System
participants (1)
-
accounts@lcrc.anl.gov