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Research Papers: Internal Combustion Engines

Steady-State Calibration of a Diesel Engine in Computational Fluid Dynamics Using a Graphical Processing Unit-Based Chemistry Solver

[+] Author and Article Information
Jian Gao

General Motors Research and Development,
800 North Glenwood Ave,
Pontiac, MI 48340
e-mail: jian.2.gao@gm.com

Ronald O. Grover, Jr.

General Motors Research and Development,
800 North Glenwood Ave,
Pontiac, MI 48340
e-mail: ronald.grover@gm.com

Venkatesh Gopalakrishnan

General Motors Research and Development,
800 North Glenwood Ave,
Pontiac, MI 48340
e-mail: venkatesh.gopalakrishnan@gm.com

Ramachandra Diwakar

General Motors Research and Development,
800 North Glenwood Ave,
Pontiac, MI 48340
e-mail: ramachandr.diwakar@gm.com

Wael Elwasif

Oak Ridge National Laboratory,
1 Bethel Valley Road,
Oak Ridge, TN 37831
e-mail: elwasifwr@ornl.gov

K. Dean Edwards

Oak Ridge National Laboratory,
1 Bethel Valley Road,
Oak Ridge, TN 37831
e-mail: edwardskd@ornl.gov

Charles E. A. Finney

Oak Ridge National Laboratory,
1 Bethel Valley Road,
Oak Ridge, TN 37831
e-mail: finneyc@ornl.gov

Russell A. Whitesides

Lawrence Livermore National Laboratory,
7000 East Avenue,
Livermore, CA 94550
e-mail: whitesides1@llnl.gov

1Corresponding author.

Contributed by the IC Engine Division of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received February 20, 2018; final manuscript received February 24, 2018; published online June 19, 2018. Editor: David Wisler.The United States Government retains, and by accepting the article for publication, the publisher acknowledges that the United States Government retains, a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States government purposes.

J. Eng. Gas Turbines Power 140(10), 102802 (Jun 19, 2018) (5 pages) Paper No: GTP-18-1085; doi: 10.1115/1.4039735 History: Received February 20, 2018; Revised February 24, 2018

The prospect of analysis-driven precalibration 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. However, the effectiveness of CFD simulation tools for in-cylinder engine combustion is often compromised by the complexity, accuracy, and computational overhead of detailed chemical kinetics necessary for combustion calculations. 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 precalibration process is presented for a passenger car diesel engine using CFD simulations and a graphical processing unit (GPU)-based chemical kinetics solver (Zero-RK, developed at Lawrence Livermore National Laboratory, Livermore, CA) 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 remains a challenge.

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Figures

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Fig. 1

Analytical engine precalibration using DEPE tool and virtual engine model

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Fig. 2

Engine map for DoE study spanning 600+ in-vehicle operating conditions

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Fig. 3

Scaling study of wall time for transport and chemistry models in constant volume reactor simulation using standard and Zero-RK chemistry solvers

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Fig. 4

Improvement in combustion predictions with enhanced mesh resolution

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Fig. 5

Comparison of emission predictions with two different mesh densities against experimental measurements over 600 operating points: (a) base mesh resolution and (b) refined mesh resolution

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