
Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Hwang, Joonsik
Committee Member
Bhushan, Shanti
Committee Member
Mun, Sungkwang
Date of Degree
8-7-2025
Original embargo terms
Visible MSU Only 1 year
Document Type
Graduate Thesis - Campus Access Only
Major
Mechanical engineering
Degree Name
Master of Science (M.S.)
College
James Worth Bagley College of Engineering
Department
Michael W. Hall School of Mechanical Engineering
Abstract
This study investigates the spray behavior of Tier 3 gasoline in gasoline direct injection engines using experimental methods. Tier 3 gasoline, formulated with lower sulfur content, enhances aftertreatment system efficiency and supports cleaner combustion. A comparative fuel property analysis between Tier 3 gasoline and PACE-20, surrogate fuel, was conducted to understand compositional effects on spray. A constant volume spray chamber and optical diagnostics, including diffuse back-illumination extinction, Schlieren, microscopic, and 3D CT reconstruction imaging, were used to examine spray morphology under varying injection conditions. Key spray parameters such as liquid volume fraction, projected liquid volume, droplet size, and cone angle were evaluated. Machine learning models were developed to predict fuel mass, optical rate of injection, and injection current profiles. The results provide insight into optimizing fuel injection strategies by integrating experimental diagnostics and predictive modeling, contributing to cleaner combustion and serving as a valuable dataset for CFD validation.
Sponsorship (Optional)
Aramco America
Recommended Citation
Lee, KyungWon, "Spray characterization and fuel property analysis of Tier 3 gasoline in a GDI system using machine learning" (2025). Theses and Dissertations. 6658.
https://scholarsjunction.msstate.edu/td/6658