Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Daniel Duke Project Name: XRayFuelSpray Division: ES Project title: Fuel Injection and Sprays Studied Using X-Ray Diagnostics Associated funding: DOE-EERE Other Systems: None Science: At the Advanced Photon Source Sector 7-BM at Argonne National Laboratory, we are presently engaged in an ongoing investigation of sprays in high pressure fuel injection systems using X-ray diagnostic techniques. An improved understanding spray formation physics is essential to the development of more efficient engine technology. As a part of this ongoing research, we are investigating the presence of cavitation phenomena in fuel injection systems and how these phenomena impact spray formation. Cavitation is a problem in fuel injection systems which operate under high pressure. At the Advanced Photon Source, we are undertaking a series of experiments to develop a novel methodology for measuring real-time cavitation inside fuel injection systems using advanced X-ray imaging techniques. A model nozzle and fuel injection system have been designed specifically for this purpose. In order to develop these novel experimental techniques, it is necessary to have an accurate and detailed prediction of the cavitation zones inside the model nozzle at precisely defined boundary conditions, so that the measurement may be compared against an accurate baseline. To achieve this, numerical simulations of the fluid flow are necessary. The prediction of cavitation in a turbulent flow at high pressure requires the use of a high-resolution three-dimensional mesh with high levels of local refinement. As such, the computation time for these highly resolved meshes is beyond the reasonable capability of a desktop computer. The Fusion cluster will allow us to make these computations. The availability of accurate and detailed prediction of cavitation zones in a model nozzle will permit the exposition of these new experimental techniques, which will enable the measurement of cavitation zones in fuel injection systems and lead to improved design for purpose to reduce or enhance local cavitation. Project description: A CFD model will be used to predict the cavitation zones in a custom-meshed model of a 0.5mm diameter nozzle. These results will be compared to experiments using X-Ray flat-field imaging and radiographic techniques which are being conducted at Sector 7-BM of the Advanced Photon Source. A number of cavitating and non-cavitating codes will be employed in order to compare the effectiveness of these codes against the experimental data. Calculations will be performed using the OpenFOAM open-source software package. Solutions will be developed for incompressible (PISO), barotropic-compressible and incompressible (HRM) cavitation & flash-boiling codes. Comparison of the solutions for these solvers allows us to observe expected differences in velocity and pressure due to local cavitation effects, and also permits prediction of geometric zones where cavitation may be expected over a range of supply pressures and back pressures. The solution convergence can also be verified via mass flow measurements made during the experimental analysis at the APS. The mesh is developed using open-source hex-meshing tools and has been optimized for parallel computation using scotch decomposition. Multi-step mesh refinement is employed and a Richardson extrapolation is used to determine the rate of convergence of the mean velocity and pressure toward grid-independence. Further adaptive local refinement in the cavitation zones is also undertaken in the multiphase model in order to approach 1% of the extrapolated grid-independent condition. The boundary conditions are supplied via prescribed supply pressure and back pressure. The fluid employed in the study is a gasoline model of four components (decane, octane, heptane and pentane) based on NIST thermodynamic tables. The fluid temperature is maintained around 300K to match the APS measurements. Now that a final mesh has been developed which scales well and shows stability for multiple so lvers, the calculation of publishable solutions can begin. This will necessitate an increase in our allocation. Much of the time in the last quarter has been spent waiting for time in the Fusion queue to access the shared pool. In order to accommodate a large increase in allocation and to reduce queue time we are currently in the process of purchasing 6 12-processor nodes on Fusion for the exclusive use of this project. The previous allocation of 50,000 hours per quarter is to be increased to 175,000 hours per quarter , whereby up to 157,680 hours will come from the nodes which we will purchase directly (72 processors*24 hours*365 days/4 quarters = 157,680) and the remaining 17,320 hours will come from the shared pool when it is available. Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 700000 Q1: 175000 Q2: 175000 Q3: 175000 Q4: 175000 Justification: We intend to purcahse 6 * 12 processor nodes on Fusion to support the requested capacity for the number of core hours required. Thank You, The LCRC Accounts System