2019
DOI: 10.2514/1.j058348
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Sustainable Aviation Fuels Approval Streamlining: Auxiliary Power Unit Lean Blowout Testing

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Cited by 24 publications
(11 citation statements)
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“…The random forest statistical analysis approach used in this work has been described previously (Peiffer et al, 2019;Colborn et al, 2020). In summary, the method employs random sampling and replacement to decrease overfitting and allows for one dependent variable (e.g., LBO or ignition performance) to be evaluated against multiple independent variables (e.g., fuel properties) (Hastie et al, 2008).…”
Section: Discussionmentioning
confidence: 99%
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“…The random forest statistical analysis approach used in this work has been described previously (Peiffer et al, 2019;Colborn et al, 2020). In summary, the method employs random sampling and replacement to decrease overfitting and allows for one dependent variable (e.g., LBO or ignition performance) to be evaluated against multiple independent variables (e.g., fuel properties) (Hastie et al, 2008).…”
Section: Discussionmentioning
confidence: 99%
“…APUs are small gas turbine engines that are used to provide power to spoolup the main engine during starter-assisted air starts. APUs are particularly sensitive to the physical properties that influence atomization and vaporization (Peiffer et al, 2019) because of their small volume, and corresponding low combustor residence time (τ cmb ρ air V cmb /W air ). The 131-9 combustor is swirl-stabilized and relies on a rich-quench-lean combustion process, like many of the much-larger, main engine combustors.…”
Section: Apu-cr Experimentsmentioning
confidence: 99%
“…Surrogates that mimic jet fuel properties have been used historically to understand combustion phenomena, while here we report potentially worst case fuel compositions. Previous efforts from the NJFCP program have shown that certain fuel properties (σ, µ, and ρ) have more of an impact on predicting ignition probabilities [14,15,30]. SAF approval could benefit from the manipulation instead of mimicking surrogate properties to illustrate the complex physical competition of properties.…”
Section: Discussionmentioning
confidence: 99%
“…Recent random forest regression (RFR) results on LBO of SAFs in four combustor rigs showed that derived cetane number (DCN) is the most significant feature importance in both the Referee Rig and toroidal jet-stirred reactor at elevated temperatures, and the second most significant feature importance in the Sheffield rig [13,14]. These three rigs show the dominance of chemical timescales near LBO, where chemical timescales are a function of the fuel chemical properties and accompanying thermodynamic conditions.…”
Section: Introductionmentioning
confidence: 99%
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