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Numerical Assessment of Ozone Addition Potential in Direct Injection Compression Ignition Engines

Abstract : This paper aims at taking into account the chemistry of O3 in a 3D CFD simulation of compression ignition engine with Diesel type combustion for low load operating points. The methodology developed in this work includes 0D homogeneous reactors simulations, 3D RANS simulations and validation regarding experimental results. The 0D simulations were needed to take into account O3 reactions during the compression stroke because of the high reactivity of O3 with NO and dissociation at high temperature. The values found in these simulations were used as an input in the 3D model to match the correct O3 concentration at fuel injection timing. The 3D simulations were performed using CONVERGE TM with a RANS approach. Simulations reproduce the compression/expansion stroke after the intake valve closure to focus on the impact of O3 on the fuel auto ignition. The comparison between numerical and experimental results demonstrates that the proposed methodology is able to capture correctly the impact of O3 addition on ignition delay and on heat release. Moreover, the analysis of the data enables to better understand the fundamental processes driving O3 impact in a CI engine. In particular, using 0D simulations, the plateau effect observed experimentally when increasing O3 concentration is attributed to O3 thermal decomposition and reaction with NO during the compression stroke. Also, 3D CFD results showed that O3 impact is observed mainly during LTHR phase and does not affect the topology and the propagation of the flame inside the combustion chamber.
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https://hal-ifp.archives-ouvertes.fr/hal-03586133
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Submitted on : Wednesday, February 23, 2022 - 3:51:27 PM
Last modification on : Tuesday, March 1, 2022 - 3:26:38 AM

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Vincent Giuffrida, Michele Bardi, Mickael Matrat, Anthony Robert, Guillaume Pilla. Numerical Assessment of Ozone Addition Potential in Direct Injection Compression Ignition Engines. International Journal of Engine Research, SAGE Publications (UK and US), 2022, 23 (1), pp.33-48. ⟨10.1177/1468087420973553⟩. ⟨hal-03586133⟩

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