Accession Number : ADA601123


Title :   Correlation of RP-1 Fuel Properties with Chemical Composition using Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometry followed by Partial Least Squares Regression Analysis


Descriptive Note : Journal article


Corporate Author : AIR FORCE RESEARCH LAB EDWARDS AFB CA ROCKET PROPULSION DIV


Personal Author(s) : Kehimkar, Benjamin ; Hoggard, Jamin C ; Marney, Luke C ; Billingsley, Matthew C ; Fraga, Carlos G ; Bruno, Thomas J ; Synovec, Robert E


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a601123.pdf


Report Date : Sep 2013


Pagination or Media Count : 72


Abstract : There is an increased need to more fully assess and control the composition of kerosene-based rocket propulsion fuels such as RP-1. In particular, it is critical to make better quantitative connections among the following three attributes: fuel performance (thermal stability, sooting propensity, engine specific impulse, etc.), fuel properties (such as flash point, density, kinematic viscosity, net heat of combustion, hydrogen content, etc.), and the chemical composition of a given fuel, i.e., amounts of specific chemical compounds and chemical groups present in a fuel as a result of feedstock blending and/or processing. Recent efforts in predicting fuel chemical and physical behavior through modeling put greater emphasis on attaining detailed and accurate fuel properties and fuel composition information. Often, one-dimensional gas chromatography (GC) combined with mass spectrometry (MS) is employed to provide chemical composition information. Building on approaches that make use of GCMS, but to glean substantially more chemical composition information from these complex fuels, we have recently studied the use of comprehensive two dimensional (2D) gas chromatography combined with time-of-flight mass spectrometry (GC x GC - TOFMS) using a reversed column format: RTX-wax column for the first dimension, and a RTX-1 column for the second dimension. In this report, by applying chemometric data analysis, specifically partial least-squares (PLS) regression analysis, we are able to readily model (and correlate) the chemical compositional information provided by use of GC x GC - TOFMS to RP-1 fuel property information such as density, kinematic viscosity, net heat of combustion, hydrogen content, and so on. Furthermore, we readily identified compounds that contribute significantly to measured differences in fuel properties based on results from the PLS models.


Descriptors :   *ROCKET FUELS , CHEMICAL COMPOSITION , GAS CHROMATOGRAPHY , KEROSENE , MASS SPECTROMETRY


Subject Categories : Liquid Rocket Propellants


Distribution Statement : APPROVED FOR PUBLIC RELEASE