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Towards a Predictive Simulation of Turbulent Combustion?—An Assessment for Large Internal Combustion Engines

Thomas Lauer and Jens Frühhaber
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Thomas Lauer: Institute of Powertrains and Automotive Technology, TU Wien, 1060 Vienna, Austria
Jens Frühhaber: Institute of Powertrains and Automotive Technology, TU Wien, 1060 Vienna, Austria

Energies, 2020, vol. 14, issue 1, 1-26

Abstract: Frequently the question arises in what sense numerical simulation can be considered predictive if prior model tuning with test results is necessary. In this paper a summary of the present Computational Fluid Dynamics (CFD) simulation methods for in-cylinder modelling is presented with a focus on combustion processes relevant for large engines. The current discussion about the sustainability of internal combustion engines will have a strong impact on applying advanced CFD methods in industrial processes. It is therefore included in the assessment. Simplifications and assumptions of turbulence, spray, and combustion models, as well as uncertainties of model boundary conditions, are discussed and the future potential of an advanced approach like Large Eddy Simulation (LES) is evaluated. It follows that a high amount of expertise and a careful evaluation of the numerical results will remain necessary in the future to apply the best-suited models for a given combustion process. New chemical mechanisms will have to be developed in order to represent prospective fuels like hydrogen or OME. Multi-injection or dual fuel combustion will further pose high requirements to the numerical methods. Therefore, the further development and validation of advanced mixture, combustion and emission models will remain important. Close cooperation between academia, code suppliers and engine manufacturers could promote the necessary progress.

Keywords: internal combustion engines; large engines; turbulence; computational fluid dynamics; LES; combustion; spray; emissions (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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