A Computational Assessment of Combustion Submodels for Predictive Simulations of Pre-Chamber Combustion Engines

Silva, Mickael; Liu, Xinlei; Hlaing, Ponnya; Cenker, Emre; Turner, J. W. G.; Im, Hong G.

doi:10.1115/icef2022-90917

Cited by 8 publications

(3 citation statements)

References 37 publications

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“…Further details on computational setup can be found in other works. 52 The model was initialized quiescently at the exhaust valve opening (EVO); a full-cycle simulation was performed aiming to minimize any error influence in the pressure, velocity, and composition field initialization. The intake inflow boundary was considered homogeneous with the air−fuel ratio (λ) shown in Table 4.…”

Section: Model Assessment Using Cfdmentioning

confidence: 99%

Skeletal CH₃OH/NO_x Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

Tang,

Silva,

Hakimov

et al. 2024

ACS Omega

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Methanol is a promising renewable fuel for achieving a better engine combustion efficiency and lower exhaust emissions. Under exhaust gas recirculation conditions, trace amounts of nitrogen oxides have been shown to participate in fuel oxidation and impact the ignition characteristics significantly. Despite numerous studies that analyzed the methanol/NO x interaction, no reliable skeletal kinetic mechanism is available for computational fluid dynamics (CFD) modeling. This work focuses on developing a skeletal CH 3 OH/NO x kinetic model consisting of 25 species and 55 irreversible and 27 reversible reactions, used for full-cycle engine combustion simulations. New experiments of methanol with the presence of 200 ppmv NO/NO 2 were conducted in a rapid compression machine (RCM) at engine-relevant conditions (20−30 bar, 850−950 K). Experimental results indicate notable enhancement effects of the presence of NO/NO 2 on methanol ignition under the conditions tested, which highlights the importance of including the CH 3 OH/NO x interactions in predicting combustion performance. The proposed skeletal mechanism was validated against the literature and new methanol and methanol/NO x experiments over a wide range of operating conditions. Furthermore, the skeletal mechanism was applied in three-dimensional (3D) CFD full-cycle simulations of spark-ignition (SI) and turbulent jet ignition (TJI) engine combustion using methanol. Simulation results demonstrate good agreement with experimental measurements of pressure traces and engine metrics, proving that the proposed skeletal mechanism is suitable and sufficient for CFD simulations.

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Section: Model Assessment Using Cfdmentioning

confidence: 99%

Skeletal CH₃OH/NO_x Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

Tang,

Silva,

Hakimov

et al. 2024

ACS Omega

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“…Under those conditions, Gu¨lder's correlation was compared to the 1D flame speed solutions obtained from the skeletal GRI-Mech 3.0 by Lu and Law. 35 Previous CFD works [5][6][7][8]12,36,37 utilized this chemical mechanism and obtained satisfactory prediction of ultra-learn pre-chamber experimental engine data with affordable computational time. Therefore, it was selected as a reference.…”

Section: -D Laminar Flame Speed Assessmentmentioning

confidence: 99%

A computational assessment of flame speed correlation in an ultra-lean pre-chamber engine

Alkhamis

Silva

Cenker

et al. 2022

International Journal of Engine Research

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Predictive modeling of pre-chamber combustion engines relies primarily on the correct description of laminar and turbulent flame speeds. For engineering applications, the correlations of the flame speeds with physical variables involve empirical constants that are valid for a limited range of operating conditions. The current work aims at assessing the significance of laminar flame speed prediction in the simulation of ultra-lean pre-chamber engine combustion operated with methane. Gülder’s empirical correlation for laminar flame speed was chosen as a reference and was further modified for equivalence ratio, pressure and temperature ranges beyond what it was originally derived for, in order to confirm the original hypothesis; the pressure and temperature dependence were adopted as a power-law correlation. Based on the computational results using the skeletal reaction mechanism, the correlation was modified better represent the flame speeds at ultra-lean engine conditions, using GRI 3.0 as a reference. The modified correlation for methane was implemented in CONVERGE, a three-dimensional computational fluid dynamics (CFD) solver, and the results were validated against the experimental data. In all cases, the original formulation of Peters’s turbulent flame speed correlation was used and was found to have insignificant effect on the conditions under study, confirming the importance of the accurate determination of the laminar flame speed that dominates over any turbulence corrections for high Karlovitz number effects. The flame topology was also investigated to provide insights into the observed pressure behavior among the tested cases. Finally, the relevant turbulent combustion regimes encountered in the pre-chamber combustion engine conditions were examined in the Borghi-Peters diagram, further confirming the findings of the study.

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“…Broad literature reports attempts to understand and optimize the pre-chamber operating conditions, 10,18,19 fuels, 20 geometrical aspects, 9,21,22 and driving cycle. 23 Despite that, the understanding of pre-chamber combustion and the role of the jet (thermal, chemical, and turbulence generation) remains incomplete.…”

Section: Introductionmentioning

confidence: 99%

DoE-ML guided optimization of an active pre-chamber geometry using CFD

Silva

Mohan

Badra

et al. 2022

International Journal of Engine Research

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An optimized active pre-chamber geometry was obtained by combining computational fluid dynamics (CFD) and machine learning (ML). A heavy-duty engine operating with methane under lean conditions was considered. The combustion process was modeled with a multi-zone well-stirred reactor (MZ-WSR) with a skeletal methane oxidation mechanism. The simulations were run for a complete cycle. For the optimization study, the pre-chamber was parametrized; six independent and three dependent variables were considered, while the volume was kept constant. Three hundred pre-chamber designs were generated, and a one-shot design of experiments (DoE) optimization was first considered. A merit function was adopted to rank the designs, and an optimum design was found from the DoE results, which yielded considerable improvements in merit ranking, considering fuel consumption, engine-out emissions, noise, and safety; secondly, machine learning algorithms were trained by utilizing the DoE results aiming at finding a globally optimum geometry for the considered operating condition. Five sequential iterations were performed, and the ML algorithms were capable of proposing a new design with superior performance compared to the best DoE.

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A Computational Assessment of Combustion Submodels for Predictive Simulations of Pre-Chamber Combustion Engines

Cited by 8 publications

References 37 publications

Skeletal CH₃OH/NO_x Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

Skeletal CH₃OH/NO_x Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

A computational assessment of flame speed correlation in an ultra-lean pre-chamber engine

DoE-ML guided optimization of an active pre-chamber geometry using CFD

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A Computational Assessment of Combustion Submodels for Predictive Simulations of Pre-Chamber Combustion Engines

Cited by 8 publications

References 37 publications

Skeletal CH3OH/NOx Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

Skeletal CH3OH/NOx Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

A computational assessment of flame speed correlation in an ultra-lean pre-chamber engine

DoE-ML guided optimization of an active pre-chamber geometry using CFD

Contact Info

Product

Resources

About

Skeletal CH₃OH/NO_x Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines

Skeletal CH₃OH/NO_x Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines