A GC × GC Tier α combustor operability prescreening method for sustainable aviation fuel candidates. (15th May 2021)

• Record Type: Journal Article
• Authors: Yang, Zhibin; Kosir, Shane; Stachler, Robert; Shafer, Linda; Anderson, Carlie; Heyne, Joshua S.
• Is Part Of: Fuel. Volume 292(2021)
• Publication Date: 2021-05-15
• Subjects: Sustainable aviation fuel -- Combustor operability -- Property predictions -- Two-dimensional gas chromatography (GC × GC) -- Monte Carlo sampling; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2021.120345
• Languages: English
• ISSNs: 0016-2361

Abstract

Highlights: A Tier α (<1 mL) Sustainable Aviation Fuel prescreening process is reported. Eight critical properties are predicted with uncertainty quantification. Predictions leverage GC × GC data and a 1226 hydrocarbon database of compounds. Predictions are evaluated against experimental measurements of 20 SAFs. Uncertainty quantification approximates the variance from novel molecules. Abstract: Fuels derived from sustainable feedstocks have significant potential to reduce greenhouse gas emissions associated with aviation. These alternative aviation fuels need to meet comprehensive safety and compatibility requirements established by an ASTM committee to achieve approval. To date, only seven annexes that define the property and compositional requirements for alternative fuels have been approved due, in part, to the significant cost and time required for evaluation and approval. Here, a Tier α sustainable aviation prescreening tool has been developed to predict the acceptability of novel SAF candidates, with the minimal volume required. Two-dimensional gas chromatography was used to determine the composition and size distribution of 20 alternative fuels, and Monte Carlo sampling was subsequently performed with a hydrocarbon database to predict eight properties that are important for combustor operability. These predicted properties were compared to experimentally measured properties, and uncertainty quantification was performed to validate the Tier α prescreening tool. The result of this validation suggests that four out of eight property confidence intervals are valid. Untuned predictions for properties with lower property variance across a given hydrocarbon type and carbon number, such as density and flash point, perform better than properties with significant property variance, such as freeze point and viscosity. The Tier α evaluation is outside of the ASTM evaluation process; however, this tool can provide feedback on downstream approval issues and facilitate fuel producer chemical process modeling thereby de-risking technology development. Thus, Tier α provides an early, rapid, and cost-effective evaluation for SAF candidates that requires minimal material volumes.