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Multidimensional Modeling and Validation of Dual-Fuel Combustion in a Large Bore Medium Speed Diesel Engine

[+] Author Affiliations
Sameera Wijeyakulasuriya, Shawn Givler, Mandhapati Raju

Convergent Science Inc., Madison, WI

Ravichandra S. Jupudi, Ashwin Raman

GE Global Research Center, Bangalore, India

Roy J. Primus, Adam E. Klingbeil

GE Global Research Center, Niskayuna, NY

Paper No. ICEF2015-1077, pp. V001T01A006; 14 pages
doi:10.1115/ICEF2015-1077
From:
  • ASME 2015 Internal Combustion Engine Division Fall Technical Conference
  • Volume 1: Large Bore Engines; Fuels; Advanced Combustion
  • Houston, Texas, USA, November 8–11, 2015
  • Conference Sponsors: Internal Combustion Engine Division
  • ISBN: 978-0-7918-5727-4
  • Copyright © 2015 by ASME

abstract

High fidelity, three-dimensional CFD was used to model the flow, fuel injection, combustion, and emissions in a large bore medium speed diesel engine with different levels of natural gas substitution. Detailed chemical kinetics was used to model the complex combustion behavior of the premixed natural gas, ignited via a diesel spray. The numerical predictions were compared against measured multiple cycle pressure data, to understand the possible factors affecting cyclic variation in experimental data. Under conditions with high natural gas substitution rates, diesel was injected much earlier than firing-TDC. This additional mixing time allowed the active radicals from diesel dissociation to initiate combustion from the cylinder wall and propagate inwards. 0%, 60%, and 93% natural gas substitution rates (by energy) were tested in this study to develop computational capabilities needed to accurately model and understand the underlying physics. Several innovative computational methods such as adaptive mesh refinement (which automatically refines and coarsens the mesh based on the existing solution parameters), and multi-zoning (which groups chemically similar cells together to reduce combustion calculation time) were utilized to obtain accurate predictions at a lower computational cost. Important engine emissions such as NOx, CO, unburnt HC, and soot were predicted numerically and compared against measured engine data.

Copyright © 2015 by ASME

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