Synthetic Aromatic Kerosene Property Prediction Improvements With Isomer Specific Characterization via GCxGC and Vacuum Ultraviolet Spectroscopy

Feldhausen, John; Bell, David C; Yang, Zhibin; Faulhaber, Conor; United States. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment; University of Dayton

doi:10.1016/j.fuel.2022.125002

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Synthetic Aromatic Kerosene Property Prediction Improvements With Isomer Specific Characterization via GCxGC and Vacuum Ultraviolet Spectroscopy

2022-07-01
By Feldhausen, John ; Bell, David C ; Yang, Zhibin ; ...

[PDF-2.82 MB]

English

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Creators:

Feldhausen, John ; Bell, David C ; Yang, Zhibin ; Faulhaber, Conor

Feldhausen, John ; Bell, David C ; Yang, Zhibin ; Faulhaber, Conor Less -
Corporate Creators:

United States. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment ; University of Dayton

United States. Federal Aviation Administration. Center of Excellence for Alternative Jet Fuels and Environment ; University of Dayton Less -
Corporate Contributors:

United States. Department of Transportation. Federal Aviation Administration. Office of Environment and Energy
Subject/TRT Terms:

[+]

ASCENT Deconvolution Elastomers Isomer Identification Jet Engine Fuels Kerosene Property Predictions Synthetic Aromatic Kerosene (SAK) Ultraviolet Spectroscopy Vacuum Ultraviolet Spectroscopy (VUV)
Publication/ Report Number:

j.fuel.2022.125002
DOI:

https://doi.org/10.1016/j.fuel.2022.125002
Resource Type:

Journal Article
Right Statement:

Open Access; https://creativecommons.org/licenses/by/4.0/
Geographical Coverage:

United States
Corporate Publisher:

Elsevier
Abstract:

This research explores an advanced method of fuel composition determination and builds upon typical hydrocarbon group type analyses performed with two-dimensional gas chromatography (GCxGC). In this study, structural information of individual species within Virent’s Synthetic Aromatic Kerosene (SAK) is identified by vacuum ultraviolet (VUV) spectroscopy. By mass, 71.3% of the components elute within six peaks of the chromatogram, from which 12 unique species are identified through a novel deconvolution method. Overall, the identification of 93.6%m across 26 structural isomers is made by the methods described in this work. With 93.6%m ascribed to specific isomers, the precision of fuel property predictions improves dramatically. For example, the absolute error of the viscosity prediction is reduced by 90% because of this advancement in diagnostic capability, and its 95-percentile confidence interval (precision only) is reduced by 93%. Additionally, the properties of SAK, blended with hydro processed esters fatty acids (HEFA), are demonstrated to have blended properties consistent with conventional jet fuel.
Content Notes:

This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: John Feldhausen, David C. Bell, Zhibin Yang, Conor Faulhaber, Randall Boehm, Joshua Heyne, Synthetic aromatic kerosene property prediction improvements with isomer specific characterization via GCxGC and vacuum ultraviolet spectroscopy, Fuel, Volume 326, 2022, 125002, ISSN 0016-2361, https://doi.org/10.1016/j.fuel.2022.125002.
Format:

PDF
Funding:

13-C-AJFF-UD-026
Collection(s):

Federal Aviation Administration
Main Document Checksum:

[+]

urn:sha256:e7cbd8ea03991add808ad09e3a3117b41c5adb2e614f0e19596faad378daf04c
Download URL:

https://rosap.ntl.bts.gov/view/dot/64804/dot_64804_DS1.pdf
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Synthetic Aromatic Kerosene Property Prediction Improvements With Isomer Specific Characterization via GCxGC and Vacuum Ultraviolet Spectroscopy

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