Identification of local extinction and prediction of reignition in a spark-ignited sparse spray flame using data mining

Wandel, Andrew P. (2018) Identification of local extinction and prediction of reignition in a spark-ignited sparse spray flame using data mining. Combustion and Flame, 198. pp. 342-355. ISSN 0010-2180

Abstract

Direct Numerical Simulations (DNS) of droplet fields which are ignited using a spark are investigated to deduce any behaviour that distinguishes between the cases where successful flame propagation occurs and where a flame ignites but subsequently extinguishes. At the instant the spark was deactivated, some of the studied cases displayed no local extinction, others showed some local extinction (one with reigni- tion and the rest with global extinction) and the rest showed global extinction. The gaseous field at this instant was analysed using the data mining technique the Gaussian Mixture Model on each case sepa- rately; this method groups data points, enabling distinction between the various behaviours. The results from this analysis showed that in the case with local extinction–reignition, the regions of space near the flame kernel which produced local quenching were caused by evaporating droplets. These regions of local quenching were relatively small compared to the strong flame front surrounding them; the regions of lo- cal quenching were also relatively far from the centre of the flame kernel. In contrast, in cases with local then global extinction, the droplets created regions which were extensions of the relatively-small flame front, and these regions behaved in a similar manner to the flame propagation. As a consequence, these cases were unable to support a self-sustaining flame. Such distinctive behaviour promises opportunities to detect situations where global extinction is imminent and implement appropriate control strategies to prevent global extinction.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Accepted version embargoed until 1 January 2020 in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Date Deposited: 30 Jan 2019 01:29
Last Modified: 05 Feb 2019 02:07
Uncontrolled Keywords: Direct Numerical Simulations; DNS; Spark ignition; Sprays; Sata mining; Gaussian Mixture Model
Fields of Research : 09 Engineering > 0913 Mechanical Engineering > 091305 Energy Generation, Conversion and Storage Engineering
09 Engineering > 0902 Automotive Engineering > 090201 Automotive Combustion and Fuel Engineering (incl. Alternative/Renewable Fuels)
09 Engineering > 0915 Interdisciplinary Engineering > 091502 Computational Heat Transfer
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
B Economic Development > 85 Energy > 8507 Energy Conservation and Efficiency > 850702 Energy Conservation and Efficiency in Transport
Identification Number or DOI: 10.1016/j.combustflame.2018.09.028
URI: http://eprints.usq.edu.au/id/eprint/35057

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