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Numerical Investigation of Fuel Effects on Soot Emissions at Heavy-Duty Diesel Engine Conditions

[+] Author Affiliations
Meng Tang, Jeffrey Naber, Seong-Young Lee

Michigan Technological University, Houghton, MI

Yuanjiang Pei, Yu Zhang, Michael Traver, David Cleary

Aramco Research Center - Detroit, Novi, MI

Zhaoyu Luo

Convergent Science, Madison, WI

Paper No. ICEF2018-9696, pp. V002T06A019; 16 pages
  • ASME 2018 Internal Combustion Engine Division Fall Technical Conference
  • Volume 2: Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development
  • San Diego, California, USA, November 4–7, 2018
  • Conference Sponsors: Internal Combustion Engine Division
  • ISBN: 978-0-7918-5199-9
  • Copyright © 2018 by ASME


Gasoline compression ignition (GCI) engine technology has shown the potential to achieve high fuel efficiency with low criteria pollutant emissions. In order to guide the design and optimization of GCI combustion, it is essential to develop high-fidelity simulation tools. Building on the previous work in computational fluid dynamic (CFD) simulations of spray combustion, this work focuses on predicting the soot emissions in a constant-volume vessel representative of heavy-duty diesel engine applications for an ultra-low sulfur diesel (ULSD) and a high reactivity (Research Octane Number 60) gasoline, and comparing the soot evolution characteristics of the two fuels. Simulations were conducted using both Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) turbulence models. Extensive model validations were performed against the experimental soot emissions data for both fuels. It was found that the simulation results using the LES turbulence model agreed better with the measured ignition delays and liftoff lengths than the RANS turbulence model. In addition, two soot models were evaluated in the current study, including an empirical two-step soot formation and oxidation model, and a detailed soot model that involves poly-aromatic hydrocarbon (PAH) chemistry. Validations showed that the separation of the flame lift-off location and the soot lift-off location and the relative natural luminosity signals were better predicted by the detailed soot model combined with the LES turbulence model. Qualitative comparisons of simulated local soot concentration distributions against experimental measurements in the literature confirmed the model’s performance. CFD simulations showed that the transition of domination from soot formation to soot oxidation was fuel-dependent, and the two fuels exhibited different temporal and spatial characteristics of soot emissions. CFD simulations also confirmed the lower sooting propensity of gasoline compared to ULSD under all investigated conditions.

Copyright © 2018 by ASME



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