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Technical Paper

Investigation of Sub-Grid Model Effect on the Accuracy of In-Cylinder LES of the TCC Engine under Motored Conditions

2017-09-04
2017-24-0040
The increasing interest in the application of Large Eddy Simulation (LES) to Internal Combustion Engines (hereafter ICEs) flows is motivated by its capability to capture spatial and temporal evolution of turbulent flow structures. Furthermore, LES is universally recognized as capable of simulating highly unsteady and random phenomena driving cycle-to-cycle variability (CCV) and cycle-resolved events such as knock and misfire. Several quality criteria were proposed in the recent past to estimate LES uncertainty: however, definitive conclusions on LES quality criteria for ICEs are still far to be found. This paper describes the application of LES quality criteria to the TCC-III single-cylinder optical engine from University of Michigan and GM Global R&D; the analyses are carried out under motored condition.
Technical Paper

Impact of Grid Density on the LES Analysis of Flow CCV: Application to the TCC-III Engine under Motored Conditions

2018-04-03
2018-01-0203
Large-eddy simulation (LES) applications for internal combustion engine (ICE) flows are constantly growing due to the increase of computing resources and the availability of suitable CFD codes, methods and practices. The LES superior capability for modeling spatial and temporal evolution of turbulent flow structures with reference to RANS makes it a promising tool for describing, and possibly motivating, ICE cycle-to-cycle variability (CCV) and cycle-resolved events such as knock and misfire. Despite the growing interest towards LES in the academic community, applications to ICE flows are still limited. One of the reasons for such discrepancy is the uncertainty in the estimation of the LES computational cost. This in turn is mainly dependent on grid density, the CFD domain extent, the time step size and the overall number of cycles to be run. Grid density is directly linked to the possibility of reducing modeling assumptions for sub-grid scales.
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