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Improved Near Wall Treatment for CI Engine CFD Simulations. Mika Nuutinen Helsinki University of Technology, Internal Combustion Engine Technology. Conjugate Heat Transfer in CFD. Continuous heat flux across surface
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Improved Near Wall Treatment for CI Engine CFD Simulations Mika Nuutinen Helsinki University of Technology, Internal Combustion Engine Technology
Conjugate Heat Transfer in CFD • Continuous heat flux across surface • Simultaneous determination of heat flow and temperature within a fluid and its adjacent solid e.g. • Cylinder charge and piston • Engine block and coolant
Why conjugate heat transfer? • Primarily: Designer needs accurate temperature data in/on solid part • Maximum temperature (melting) • Temperature distribution (thermal loads) • Secondarily: Produces transient, more accurate boundary condition for temperature • More accurate heat loss prediction • More accurate overall temperature/pressure fields
CFD problems in heat transfer • Inaccuracy of RANS turbulence models (k-ε, k-ω) • Extreme field gradients near walls • Standard wall treatment (wall functions) omits the effects of temperature induced density variations near walls
New wall function formalism • Derived similarly to standard wall functions, but with smooth turbulent viscosity transition (Mellor) and variable near wall turbulent Pr (Kays) • Sensitive to temperature induced density variation near the walls unlike standard wall functions + Improves heat transfer and temperature predictions + Easy to include other temperature variable effects to e.g. heat capacity, μ, k… - No analytical solution -> computational burden
Wall function comparison, typical CI engine simulation case • Simulations were made with 4 combinations of turbulence models and near wall treatments: • 1) High Reynolds number k-e model with standard wall functions. • 2) High Reynolds number k-e model with the new variable density wall functions • 3) High Reynolds number RNG k-e model with standard wall functions. • 4) Low Reynolds number k-e model with hybrid wall treatment.
Spray and Combustion modeling • Lagrangian particle tracking • Transfer of mass, momentum and heat modeled • Droplet break up models: Reitz-Diwakar etc. • Turbulent dispersion, collisions, coalescence • EBU LaTCT (laminar and turbulent characteristic time) combustion model
Concluding remarks • The new wall function formalism works well in practical simulations • Enhances the predicted wall heat transfer in CI engine simulations when the gas is hot (and vice versa) • Further improvements easy to implement • Computational burden can be minimized by selecting a smaller boundary where the heat transfer is critical