Application of a jet fuel database in the development of chemical kinetic models

Growing interest in sustainable aviation fuels (SAFs) has led to widespread efforts to help understand and model the behavior of SAFs in real engine configurations. This study develops a chemical kinetic mechanism for the modeling of an Alcohol-to-Jet (ATJ) aviation turbine fuel in order to validate a methodology for the development of models using data from a publicly available jet fuel test database. Specifically, two-dimensional gas chromatography (GCxGC) data taken from the National Alternative Jet Fuels Test Database (AJFTD) hosted by the University of Illinois at Urbana-Champaign (UIUC) is used to identify an appropriate surrogate to model the ATJ fuel. Through Cantera simulations, the foundation for a chemical mechanism adapted from the HyChem structure is created. A machine learning based approach known as the hybrid response surface technique is used to rapidly generate a set of 1000 models which satisfy ATJ ignition delay curves and to quantify the uncertainties of these models. Models are constrained according to their ability to predict the behavior of the ATJ fuel in various combustion scenarios in order to arrive at a favored model result. This methodology contributes to the prescreening of novel SAFs as it provides a means of quickly developing a chemical kinetic mechanism based on limited experimental testing and fuel volumes. Model predictions aid SAF producers in understanding whether a potential SAF will be viable in real aircraft engines, so producers can make an informed decision whether to scale up production of the SAF. Aspects of this methodology are expected to be incorporated as functionality of the AJFTD in future, allowing researchers and SAF producers alike to more easily understand the behavior of various SAFs.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Aerospace Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Godsell, Audrey

Contributors dc:contributor

• Lee, Tonghun

• Kinetic Modeling
• Sustainable Aviation Fuel
• Response Surface
• Hychem
• Fuel Database

Statement dc:rights

• Copyright 2024 Audrey Godsell

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/127405

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F127405