Dissertation/Thesis Abstract

A computational and experimental study on combustion processes in natural gas/diesel dual fuel engines
by Hockett, Andrew, Ph.D., Colorado State University, 2015, 249; 3746141
Abstract (Summary)

Natural gas/diesel dual fuel engines offer a path towards meeting current and future emissions standards with lower fuel cost. However, numerous technical challenges remain that require a greater understanding of the in-cylinder combustion physics. For example, due to the high compression ratio of diesel engines, substitution of natural gas for diesel fuel at high load is often limited by engine knock and pre-ignition. Additionally, increasing the natural gas percentage in a dual fuel engine often results in decreasing maximum load. These problems limit the substitution percentage of natural gas in high compression ratio diesel engines and therefore reduce the fuel cost savings. Furthermore, when operating at part load dual fuel engines can suffer from excessive emissions of unburned natural gas. Computational fluid dynamics (CFD) is a multi-dimensional modeling tool that can provide new information about the in-cylinder combustion processes causing these issues.

In this work a multi-dimensional CFD model has been developed for dual fuel natural gas/diesel combustion and validated across a wide range of engine loads, natural gas substitution percentages, and natural gas compositions. The model utilizes reduced chemical kinetics and a RANS based turbulence model. A new reduced chemical kinetic mechanism consisting of 141 species and 709 reactions was generated from multiple detailed mechanisms, and has been validated against ignition delay, laminar flame speed, diesel spray experiments, and dual fuel engine experiments using two different natural gas compositions. Engine experiments were conducted using a GM 1.9 liter turbocharged 4-cylinder common rail diesel engine, which was modified to accommodate port injection of natural gas and propane. A combination of experiments and simulations were used to explore the performance limitations of the light duty dual fuel engine including natural gas substitution percentage limits due to fast combustion or engine knock, pre-ignition, emissions, and maximum load. In particular, comparisons between detailed computations and experimental engine data resulted in an explanation of combustion phenomena leading to engine knock in dual fuel engines.

In addition to conventional dual fuel operation, a low temperature combustion strategy known as reactivity controlled compression ignition (RCCI) was explored using experiments and computations. RCCI uses early diesel injection to create a reactivity gradient leading to staged auto-ignition from the highest reactivity region to the lowest. Natural gas/diesel RCCI has proven to yield high efficiency and low emissions at moderate load, but has not been realized at the high loads possible in conventional diesel engines. Previous attempts to model natural gas/diesel RCCI using a RANS based turbulence model and a single component diesel fuel surrogate have shown much larger combustion rates than seen in experimental heat release rate profiles, because the reactivity gradient of real diesel fuel is not well captured. To obtain better agreement with experiments, a reduced dual fuel mechanism was constructed using a two component diesel surrogate. A sensitivity study was then performed on various model parameters resulting in improved agreement with experimental pressure and heat release rate.

Indexing (document details)
Advisor: Marchese, Anthony J.
Commitee: Gao, Xinfeng, Hampson, Greg, Olsen, Daniel B., Young, Peter
School: Colorado State University
Department: Mechanical Engineering
School Location: United States -- Colorado
Source: DAI-B 77/05(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Automotive engineering, Mechanical engineering
Keywords: Chemical kinetic mechanism, Computational fluid dynamics, Diesel engine, Dual fuel, Natural gas, Reactivity controlled compression ign
Publication Number: 3746141
ISBN: 9781339393506
Copyright © 2019 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy
ProQuest