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We note that confirmation of this concept would denote the first detection of purely organic signals from both fractions, because previous stepped combustion data contain a potentially wide mixture of combustible carbon-bearing components.
This paper introduces a novel post-processing technique for analyzing high dimensional combustion data.
We analyse our formulae for typical in situ combustion data and compare the results with numerical simulations.
Combustion data were also collected during the emission test at each altitude, which was helpful for the analysis of the emission results.
The updated high temperature model was validated on the present experimental data and a vast amount of previous n-butanol combustion data.
Then, the model is subjected to a rigorous mathematical analysis by constraining the rate coefficients against the combustion data, as well as a consistency-screening process.
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Principal component analysis (PCA) has been successfully applied to the analysis of combustion data-sets.
The prediction of NOx emission in turbojet engines by combining combustion operational data produced information showing correlation between the analytical and empirical results.
Finally, model predictions are compared with new high pressure ignition and combustion time data.
The combustion rate data could be fitted well to both the power law and redox (Mars Van Krevelen) models.
Reasonable agreement between the predicted scaling and measured combustion recession data is shown over a very wide range of ambient conditions, injector parameters, and end-of-injection transients.
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