contributor author | Hamilton, Len | |
contributor author | Luning Prak, Dianne | |
contributor author | Cowart, Jim | |
date accessioned | 2017-05-09T01:07:44Z | |
date available | 2017-05-09T01:07:44Z | |
date issued | 2014 | |
identifier issn | 1528-8919 | |
identifier other | gtp_136_07_071505.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/154743 | |
description abstract | There are currently numerous efforts to create renewable fuels that have similar properties to conventional diesel fuels. One major future challenge is evaluating how these new fuels will function in older legacy diesel engines. It is desired to have physically based modeling tools that will predict new fuel performance without extensive full scale engine testing. This study evaluates two modeling tools that are used together to predict ignition delay in a military diesel engine running nhexadecane as a fuel across the engine's speedload range. AVLFIREآ® is used to predict the physical delay of the fuel from the start of injection until the formation of a combustible mixture. Then a detailed Lawrence Livermore National Laboratory (LLNL) chemical kinetic mechanism is used to predict the chemical ignition delay. This total model predicted ignition delay is then compared to the experimental engine data. The combined model predicted results show good agreement to that of the experimental data across the engine operating range with the chemical delay being a larger fraction of the total ignition delay. This study shows that predictive tools have the potential to evaluate new fuel combustion performance. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Predicting the Physical and Chemical Ignition Delays in a Military Diesel Engine Running n Hexadecane Fuel | |
type | Journal Paper | |
journal volume | 136 | |
journal issue | 7 | |
journal title | Journal of Engineering for Gas Turbines and Power | |
identifier doi | 10.1115/1.4026657 | |
journal fristpage | 71505 | |
journal lastpage | 71505 | |
identifier eissn | 0742-4795 | |
tree | Journal of Engineering for Gas Turbines and Power:;2014:;volume( 136 ):;issue: 007 | |
contenttype | Fulltext | |