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research-article

TURBULENT SPRAY COMBUSTION MODELING USING VARIOUS KINETICS SOLVERS AND TURBULENCE MODELS

[+] Author and Article Information
Joshua A. Piehl

PhD student of Department of Mechanical Engineering, Wayne State University, Detroit, MI, United States
joshua.piehl@wayne.edu

Omid Samimi Abianeh

ASME member, Assistant Professor of Department of Mechanical Engineering, Wayne State University, Detroit, MI, United States
o.samimi@wayne.edu

Ashraya Goyal

MSc student of Department of Mechanical Engineering, Wayne State University, Detroit, MI, United States
ashraya.goyal@wayne.edu

Luis Bravo

Vehicle Technology Directorate, Army Research Laboratory, Maryland, United States
luis.g.bravorobles.civ@mail.mil

1Corresponding author.

ASME doi:10.1115/1.4040659 History: Received October 14, 2017; Revised June 17, 2018

Abstract

Turbulent spray combustion of n-dodecane was modeled at relevant engine conditions using two combustion models (Direct Integration of Chemistry (DIC) and Flamelet Generated Manifolds (FGM)) and multi-fidelity turbulence models (Dynamic Structure Large Eddy Simulation and RNG Reynolds-Averaged Naiver-Stokes). The main objective of this research work is to study the effect of various combustion and turbulence models on spray behavior and quantify these effects. To reach these objectives, a recently developed kinetic mechanism and well established spray models were utilized for the 3-D turbulent spray simulation at various combustion chamber initial gas temperature and pressure conditions. Fine mesh with size of 31 microns was utilized to resolve small eddies in the periphery of the spray. A new methodology for mesh generation was proposed and investigated to simulate the measured injection to injection data fluctuation in CFD domain. The pressure-based ignition delay, flame lift-off length, species concentrations histories, spray and jet penetrations were modeled and compared with measured data. Differences were observed between various combustion and turbulence models in predicting spray characteristics. However, these differences are within the uncertainties, error and variations of measured data.

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