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Title: Steady-State Calibration of a Diesel Engine in CFD Using a GPU-Based Chemistry Solver

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 EPA 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 pre-calibration process is presented for a passenger car diesel engine using CFD simulations with CONVERGE™ 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 Computingmore » Facility. The results with different mesh resolutions have been analyzed to compare differences in combustion and emissions (NO x, Carbon Monoxide CO, Unburned Hydrocarbons UHC, and Smoke) with actual engine measurements. The results show improved agreement in combustion and NO x 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.« less

Authors:
 [1];  [2];  [1];  [1]; ORCiD logo [3]; ORCiD logo [3]; ORCiD logo [3];  [4]
  1. General Motors (GM), Research and Development Center
  2. General Motors (GM) Corporation
  3. ORNL
  4. Lawrence Livermore National Laboratory (LLNL)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1468279
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: ASME 2017 Internal Combustion Engine Division Fall Technical Conference , Seattle, WA, USA, October 15-18, 2017
Country of Publication:
United States
Language:
English

Citation Formats

Gao, Jian, Grover, Ronald O., Gopalakrishnan, Venkatesh, Diwakar, Ramachandra, Elwasif, Wael R., Edwards, K Dean, FINNEY, Charles E A, and Whitesides, Russel. Steady-State Calibration of a Diesel Engine in CFD Using a GPU-Based Chemistry Solver. United States: N. p., 2017. Web. doi:10.1115/ICEF2017-3631.
Gao, Jian, Grover, Ronald O., Gopalakrishnan, Venkatesh, Diwakar, Ramachandra, Elwasif, Wael R., Edwards, K Dean, FINNEY, Charles E A, & Whitesides, Russel. Steady-State Calibration of a Diesel Engine in CFD Using a GPU-Based Chemistry Solver. United States. doi:10.1115/ICEF2017-3631.
Gao, Jian, Grover, Ronald O., Gopalakrishnan, Venkatesh, Diwakar, Ramachandra, Elwasif, Wael R., Edwards, K Dean, FINNEY, Charles E A, and Whitesides, Russel. Wed . "Steady-State Calibration of a Diesel Engine in CFD Using a GPU-Based Chemistry Solver". United States. doi:10.1115/ICEF2017-3631. https://www.osti.gov/servlets/purl/1468279.
@article{osti_1468279,
title = {Steady-State Calibration of a Diesel Engine in CFD Using a GPU-Based Chemistry Solver},
author = {Gao, Jian and Grover, Ronald O. and Gopalakrishnan, Venkatesh and Diwakar, Ramachandra and Elwasif, Wael R. and Edwards, K Dean and FINNEY, Charles E A and Whitesides, Russel},
abstractNote = {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 EPA 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 pre-calibration process is presented for a passenger car diesel engine using CFD simulations with CONVERGE™ 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.},
doi = {10.1115/ICEF2017-3631},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {11}
}

Conference:
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