349172 Visualization of Composition-Property Relationships of Synthetic Jet Fuel with Aromatic Additives

Monday, November 4, 2013
Grand Ballroom B (Hilton)
Moiz Bohra, Elfatih Elmalik, Rehan Hussain, Haider Ramadhan, Ibrahim Al Nuaimi, Samah Warrag and Nimir Elbashir, Chemical Engineering, Texas A&M University at Qatar, Doha, Qatar

In the current economic climate, the search for economically viable alternative aviation fuels continues, specifically for fuels that meet  new stringent environmental regulations.  Synthetic jet fuels derived from natural gas using Gas-to-Liquid (GTL) technology are certified by the ASTM for use in commercial aviation when blended up to fifty percent with conventional oil-derived jet fuel (ASTM D-7566). From an environmental standpoint, GTL synthetic fuels have virtually no sulfur and lack aromatics, thus positively limiting gaseous and particulate emissions. Despite the benefits of the paraffinic-based hydrocarbon composition of GTL synthetic jet fuels, they fail to meet several required properties for jet fuels when used at a percentage higher than fifty. The naturally-occurring aromatics in conventional jet fuels swell the elastomeric O-rings within the fuel system, thus ensuring a tight seal. They also increase the density of the fuel, thus reducing the required volume of the fuel tank. Synthetic fuels on the other hand do not naturally contain aromatics, and their use could thus cause the O-rings to shrink and fail. Synthetic fuels also have different physical properties compared to regular jet fuel, which can influence their storage, flow and combustion behavior.

The aim of this research project is to study the effect of aromatic additives on synthetic jet fuel. Previous studies by our group have resulted in a visualization model that predicts the composition-property relationships for various ‘surrogate’ blends made from compounds representing the hydrocarbon building blocks of synthetic jet fuel (normal, iso and cyclo paraffins). In the current study an aromatic compound, toluene, was added, and the density, viscosity and freezing point - properties crucial for gauging a fuel’s performance – were measured experimentally. The results were analyzed using MATLAB’s neural network toolbox to generate composition-property relationships that can be visualized in three dimensions using a quaternary plot. Ongoing work on the effect of the fuels’ carbon number on the physical properties will further augment our model. Thus, by enabling prediction of the physical properties of a synthetic fuel blend given its chemical composition, the most suitable fuels for a specified composition can be identified. This poster reports the experimental activities and the summary of the results generated by a group of undergraduate student researchers who participated in the three phases of this project: experimental, statistical analysis, and visualization model development campaigns.

The authors would like to acknowledge the financial support of this project by Qatar National Research Fund (QNRF) under the grant UREP 14-051-2-014.


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