Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification
Partially reacting candidate fuels under highly dilute conditions across a range of temperatures provides a means to classify the candidates based on traditional ignition characteristics using much lower quantities (sub-mL) than the full octane tests. Using a classifier based on a Gaussian Process m...
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Veröffentlicht in: | Energy & fuels 2018-09, Vol.32 (9), p.9581-9591 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Partially reacting candidate fuels under highly dilute conditions across a range of temperatures provides a means to classify the candidates based on traditional ignition characteristics using much lower quantities (sub-mL) than the full octane tests. Using a classifier based on a Gaussian Process model, synthetic species profiles obtained by plug flow reactor simulations at seven temperatures are used to demonstrate that the configuration can be used to classify 95% of the samples correctly for autoignition sensitivity exceeding a threshold (S ≥ 8) and 100%of the samples correctly for research octane number exceeding a threshold (RON ≥ 90). Molecular beam mass spectrometry (MBMS) experimental data at four temperatures is then used as the model input in a real-world test. Despite the nontrivial relationship between the MBMS measurements and speciation as well as experimental noise it is still possible to classify 95% of the samples correctly for RON and 85% of the samples correctly for S in a “leave-one-out” cross validation exercise. The test data set consists of 45 fuels and includes a variety of primary reference fuels, ethanol blends and other oxygenates. |
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ISSN: | 0887-0624 1520-5029 |
DOI: | 10.1021/acs.energyfuels.8b02112 |