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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.
Technical Paper

A Comparison between Different Moving Grid Techniques for the Analysis of the TCC Engine under Motored Conditions

2019-04-02
2019-01-0218
The accurate representation of Internal Combustion Engine (ICE) flows via CFD is an extremely complex task: it strongly depends on a combination of highly impacting factors, such as grid resolution (both local and global), choice of the turbulence model, numeric schemes and mesh motion technique. A well-founded choice must be made in order to avoid excessive computational cost and numerical difficulties arising from the combination of fine computational grids, high-order numeric schemes and geometrical complexity typical of ICEs. The paper focuses on the comparison between different mesh motion technologies, namely layer addition and removal, morphing/remapping and overset grids. Different grid strategies for a chosen mesh motion technology are also discussed. The performance of each mesh technology and grid strategy is evaluated in terms of accuracy and computational efficiency (stability, scalability, robustness).
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