De Bellis, V., Bozza, F., Fontanesi, S., Severi, E. et al., "Development of a Phenomenological Turbulence Model through a Hierarchical 1D/3D Approach Applied to a VVA Turbocharged Engine," SAE Int. J. Engines 9(1):506-519, 2016, doi:10.4271/2016-01-0545.
It is widely recognized that spatial and temporal evolution of both macro- and micro- turbulent scales inside internal combustion engines affect air-fuel mixing, combustion and pollutants formation. Particularly, in spark ignition engines, tumbling macro-structure induces the generation of a proper turbulence level to sustain the development and propagation of the flame front.As known, 3D-CFD codes are able to describe the evolution of the in-cylinder flow and turbulence fields with good accuracy, although a high computational effort is required. For this reason, only a limited set of operating conditions is usually investigated. On the other hand, thanks to a lower computational burden, 1D codes can be employed to study engine performance in the whole operating domain, despite of a less detailed description of in-cylinder processes. The integration of 1D and 3D approaches appears hence a promising path to combine the advantages of both.In the present paper, a 0D phenomenological mean flow and turbulence model belonging to the K-k model family is presented in detail. The latter is implemented in the GT-Power™ software under the form of “user routine”. The model is tuned against in-cylinder results provided by 3D-CFD analyses carried out by the Star-CD™ code at two engine speeds under motored operation. In particular, a currently produced twin-cylinder turbocharged VVA engine is analyzed. The 0D model is then validated against further 3D results at various engine speeds and intake valve lifts, including early closure strategies, both under motored and fired operation.The proposed 0D mean flow and turbulence model shows the capability to accurately estimate the temporal evolution of the incylinder turbulence for all the considered operating conditions, without requiring any case-dependent tuning, proving its generality and reliability.