A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)
AuthorsSkeen, Scott A.
Pickett, Lyle M.
Garcia-Oliver, Jose M
Reitz, Rolf D.
Pandurangi, Sushant S.
Wright, Yuri M.
Chishty, Muhammad Aqib
KAUST DepartmentMechanical Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/617787
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AbstractThe 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.
CitationA Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN) 2016, 9 (2) SAE International Journal of Engines
SponsorsThe following individuals and funding agencies are acknowledged for their support. The authors from DTU acknowledge the Technical University of Denmark, Danish Strategic Research Council, and MAN Diesel & Turbo University of Wisconsin: Financial support provided by the Princeton Combustion Energy Frontier Research Center. ETH Zurich: Financial support from the Swiss Federal Office of Energy (grant no. SI/500818-01) and the Swiss Competence Center for Energy and Mobility (CCEM project “In-cylinder emission reduction”) is gratefully acknowledged. Argonne National Labs: Work was funded by U.S. DOE Office of Vehicle Technologies, Office of Energy Efficiency and Renewable Energy under Contract No. DE-AC02-06CH11357. We also gratefully acknowledge the computing resources provided on Fusion, a computing cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory. Sandia National Labs, Combustion Research Facility: Work was supported by the U.S. Department of Energy, Office of Vehicle Technologies. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract DEAC04-94AL85000. Chris Carlen and Dave Cicone are gratefully acknowledged for technical assistance. The authors from ANL and SNL also wish to thank Gurpreet Singh and Leo Breton, program managers at U.S. DOE, for their support.