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research-article

Steady-state Calibration of a Diesel Engine in CFD using a GPU-based Chemistry Solver

[+] Author and Article Information
Jian Gao

General Motors Research and Development
jian.2.gao@gm.com

Ronald O. Grover

General Motors Research and Development
ronald.grover@gm.com

Venkatesh Gopalakrishnan

General Motors Research and Development
venkatesh.gopalakrishnan@gm.com

Ramachandra Diwakar

General Motors Research and Development
ramachandr.diwakar@gm.com

Wael Elwasif

Oak Ridge National Laboratory
elwasifwr@ornl.gov

K. Dean Edwards

Oak Ridge National Laboratory
edwardskd@ornl.gov

Charles E.A. Finney

Oak Ridge National Laboratory
finneyc@ornl.gov

Russell A. Whitesides

Lawrence Livermore National Laboratory
whitesides1@llnl.gov

1Corresponding author.

ASME doi:10.1115/1.4039735 History: Received February 20, 2018; Revised February 24, 2018

Abstract

The prospect of analysis-driven pre-calibration of a modern diesel engine is extremely valuable in order to significantly reduce hardware investments and accelerate engine designs compliant with stricter fuel economy regulations. Advanced modeling tools, such as CFD, are often used with the goal of streamlining significant portions of the calibration process. The success of the methodology largely relies on the accuracy of analytical predictions, especially engine-out emissions. The standard approach has been to use skeletal kinetic mechanisms (~50 species) which consume acceptable computational time but with degraded accuracy. In this work, a comprehensive demonstration and validation of the analytical pre-calibration process is presented for a passenger car diesel engine using CFD simulations and a GPU-based chemical kinetics solver (Zero-RK, developed at Lawrence Livermore National Laboratory) on high performance computing resources to enable the use of detailed kinetic mechanisms. Diesel engine combustion computations have been conducted over 600 operating points spanning in-vehicle speed-load map, using massively parallel ensemble simulation sets on the Titan supercomputer located at the Oak Ridge Leadership Computing Facility. The results with different mesh resolutions have been analyzed to compare differences in combustion and emissions (NOx, Carbon Monoxide CO, Unburned Hydrocarbons UHC, and Smoke) with actual engine measurements. The results show improved agreement in combustion and NOx predictions with a large n-heptane mechanism consisting of 144 species and 900 reactions with refined mesh resolution; however; agreement in CO, UHC and Smoke remain a challenge.

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