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Large eddy simulation using linear eddy sub-grid mixing modeling

Salman Arshad (Institutionen för tillämpad mekanik, Förbränning)
Göteborg : Chalmers University of Technology, 2016. - 55 s.
[Licentiatavhandling]

As emissions regulations are getting stricter and efficiency requirements of engines are increasing, different concepts to improve combustion are being investigated. For example lean stratified premixed combustion, homogeneous charge compression ignition(HCCI), use of more exhaust gas recirculation (EGR) to reduce NOx etc. In all these concepts, combustion happens at lower temperatures, higher pressures, and higher level of air dilution than today's typical spark ignition or diesel engines. Many combustion models in computational fluid dynamics (CFD) today describe either premixed or non-premixed mode of combustion, assuming fast chemistry regimes only. There is a great need of new combustion models that are mode (premixed/non-premixed) and regime (fast/non fast chemistry) independent. The linear eddy model (LEM) of Kerstein [1] used as a sub-grid combustion model for large eddy simulation (LES) is regarded as a truly mode and regime independent combustion model as it models all the physical processes, i.e. large and small scale turbulent advection, molecular diffusion and chemical reactions at their respective time scales. It is also crucial for combustion models to describe turbulent mixing well. The LEM used as a sub-grid mixing model for LES called LES-LEM, has been successfully used to predict turbulent mixing flows too. This thesis presents a new approach for large scale turbulent advection in LES-LEM. The approach links the sub-grid LEM implementation to a concept of control-volume crossing rate. Magnitude and direction of the crossing is implied by LES-prescribed mass fluxes. A high flux implies a high crossing rate, corresponding to a high displacement per time step, and vice versa.

Nyckelord: Large Eddy Simulation, Linear Eddy Model, LES-LEM, Splicing



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Denna post skapades 2016-08-17.
CPL Pubid: 240362