Hello, A new project on the LCRC cluster has been requested. Please forward the information on to the LCRC Allocation sub-committee. Applicant's name: Riccardo Scarcelli Applicant's institution: ANL Applicant's division: ES Project Name: FOA_dual_fuel Project title: Efficiency-Optimized Dual Fuel Engine with In-Cylinder Gasoline/CNG Blending Associated funding: DOE - Office of Vehicle Technology Other Systems: Science: This project proposal, led by Argonne’s Center for Transportation Research, was submitted in response to the FY 2014 Vehicle Technologies Program Wide Funding Opportunity Announcement DE-FOA-0000991 (0991-1822) and was awarded with a total of $1,000,000 for FY2015, FY2016, and FY2017. Main goal of the project is to demonstrate that the proposed gasoline/CNG blending concept yields improved engine efficiencies over both gasoline and CNG-only operation by tailoring fuel properties based on engine load. 3D-CFD simulation plays a key role in carrying out fundamental analysis of the mixture formation process, with particular regard to the direct injection (DI) of natural gas within the cylinder, and in optimizing the engine operating parameters for a cost-effective engine design. Project description: The CFD activity is a crucial sub-task of this entire project and initially (Q1 and Q2) aims at fully characterizing the gaseous jets from DI gas injectors through comparison of numerical results against x-ray measurements carried out at APS. In the second half of FY2015 (Q3 and Q4), the comprehensive modeling of gaseous jets will be exploited to carry out investigations of the mixture formation process in a single-cylinder research engine when gasoline is introduced using port fuel injection (PFI) and compressed natural gas is directly injected (DI) into the cylinder. Simulations will be performed with the commercial code CONVERGE and computational grids of few million cells will require the use of 32-64 cores depending on mesh resolution (the RANS approach will be initially followed). The project is expected to have two members, with 2 or 3 cases run simultaneously on daily bases. With an average of 32 cores per run and 2 cases run in parallel, the expected amount of core-hrs needed for this project for each quarter is about: 32x24x90x2=138,240. There is not scalability data yet available for this project. However, similar engine simulations showed that with the CONVERGE software and with the expected grid resolution (few million cells) the runs should scale efficiently up to 3 nodes (48 cores). For reference please see the GDI_lean_burn project. Industry partnership: Project URL: Requested allocation: 495000 Q1: 90000 Q2: 135000 Q3: 135000 Q4: 135000 Justification: Storage requirements: The requester has used undetermined amount hours of their initial startup project. In addition to approving an initial amount, please specify a Category and Subcategory for this project. For a list of the current selection of approved categories, please see: https://wiki.lcrc.anl.gov/wiki/Processes/Categories Once the Allocation committee has approved the project, please go to the Project Management page to create it: https://accounts.lcrc.anl.gov/projects.php Thank You, The LCRC Accounts System