Abstract

Producing reliable in-cylinder simulations for quick-turnaround engine development for industrial purposes is a challenging task for modern computational fluid dynamics, mostly because of the tuning effort required for the sub-models used in the various frameworks (the Reynolds-averaged Navier–Stokes and large eddy simulation). Tuning is required because of the need for modern engines to operate under a wider range of conditions and fuels. In this article, we suggest a novel methodology based on automated simulation parameter optimisation that is capable of delivering a priori a coefficient matrix for each operating condition. This approach produces excellent results for multiple comparison metrics like liquid and vapour penetration lengths, radial and axial mass fraction and temperature distributions. In this article, we also show for the first time that input model coefficients can potentially be linked to ambient boundary conditions in a physically consistent manner. Changes in injection pressure, charge pressure and charge density are considered. This paves the way for the tabulation of the constants in order to eliminate lengthy tuning iterations between operating conditions and move towards adaptive simulations as the piston moves changing the in-cylinder conditions. An additional discussion is performed for the validity range of existent models given that in recent years there has been a shift towards more extreme thermodynamic conditions in the injection stage (reaching the limits of transcritical flows). Although in this work the framework was implemented in the Reynolds-averaged Navier–Stokes context because this is the tool of preference of digital engineering currently by automotive industries, the approach can be easily extended in large eddy simulation.

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