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: Yuanjiang Pei Applicant's institution: ANL Applicant's division: ES Project Name: SprayFlame-LES Project title: Development of sub-grid turbulent combustion models for LES under engine conditions Associated funding: Strategic Initiative LDRD project, NSF-DOE project Other Systems: Science: Vehicles powered by internal combustion engines (ICEs), operating on a variety of conventional and alternate fuels, are expected to remain as the primary mode of transportation in the foreseeable future worldwide. To assist the design of new combustion regimes, to reduce emission and improve efficiency, it is readily recognized that high-fidelity simulations coupled with advanced combustion models that consider turbulent-chemistry-interaction (TCI), together with detailed chemistry, are necessary for improved accuracy of predictions. However, the importance of the role of TCI has not been systematically explored, especially in the context of high-fidelity large eddy simulation (LES) under engine conditions. The primary objective of the proposed research is to examine the role of TCI when coupled with LES under engine conditions and to develop turbulent combustion models which are universally applicable to mixed regimes of combustion, including premix ed and non-premixed flames with local ignition and extinction. This objective will be achieved through a collaborative effort by combining computational flame diagnostics, turbulence modeling, direct numerical simulation (DNS), LES and Reynolds-averaged Navier-Stokes (RANS). The model development will be primarily based on chemical explosive mode analysis that can rigorously detect limit flame phenomena and elementary flamelets. Project description: With the advent of parallelization techniques and highly-scalable CFD solvers, LES is becoming an increasingly practical technique for modeling turbulent flames in internal combustion engines. Recently it has been shown by Argonne that LES can provide good qualitative and quantitative comparisons to instantaneous engine spray measurements since it directly resolves the large scales in the flow field. However, the systematic study of different combustion models and the role of TCI when coupled with LES at reactive engine conditions has not been explored. LES with different levels of advanced combustion models will be validated against DNS and experimental data in this computational study. High-fidelity detailed combustion model based LES methodology has not yet been applied to simulations under diesel engine conditions. Demonstration of the role of advanced combustion models under real engine simulation is challenging due the need to resolve finer flow structures (to eliminate or minimize the artificial TCI effect due to coarse mesh resolution) across larger volumes which may result in high computational costs. This project will address these challenges by using advanced load-balancing algorithms (such as METIS), reduced chemical kinetic models for combustion (ensuring that the fidelity of the model is very high under the operating conditions), multi-zone combustion model, HPC resources to ensure lower wall-clock times, adaptive mesh resolution technique to add cells in desired locations of high temperature, species, and velocity gradients. The key will be to address the role of TCI under engine conditions and develop a universal combustion model for mixed-mod e combustion. The collaboration between Argonne, University of Connecticut (UCONN) and Sandia National Laboratory (Sandia) will bridge the fundamental research with the industrial needs: 1. LES turbulence model coupled with a delta-function combustion model will be further examined with a 54 species skeletal mechanism. The mesh resolution is expected to be lower than 30 microns, which will be the first-ever diesel spray flame simulations with such high spatial resolution. 2. LES turbulence model coupled with a flamelet generated manifold (FGM) combustion model will be explored and compared to the delta-function combustion model. 3. Finally, a universal combustion model that considers TCI and is applicable to both premixed and non-premixed modes will be examined in the context of both RANS and LES contexts. 4. LES calculations will also be performed to provide boundary conditions for DNS calculations to be done at Sandia and UCONN collaborators. These simulations will help us develop “best practices” for computations of interest to the industry as well since the universal combustion model will be applicable for both RANS and LES applications. Industry partnership: The project is between Argonne, UCONN and Sandia. It is expected that the results of the project will not only advance the state-of-the-art in LES combustion calculations but also significantly benefit industry research. Argonne will be performing the algorithm development, simulations, post-processing results, and writing technical reports. Sandia and UCONN will perform DNS study with simplified geometry and boundary conditions from Argonne’s work and provide feedback to Argonne. The models will be implemented in CONVERGE code owned by the software vendor CSI. Project URL: http://www.transportation.anl.gov/engines/multi_dim_model_home.html Requested allocation: 3000000 Q1: 0 Q2: 150000 Q3: 1350000 Q4: 1500000 Justification: The CONVERGE code has been extensively used on Fusion and Blues clusters and now it can be scaled up to 5000 cores on Mira and is in the progress towards scaling to a rack of Mira. 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