Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust
The industrial sector continues to face difficulties in preventing dust explosions. Ignition, in particular, is a phenomenon that has yet to be fully comprehended. As a result, safety conditions pertaining to ignition control are rarely assessed to an adequate level. It is generally recognised that...
| Main Authors: | Arshad, U., Taqvi, S.A.A., Buang, A. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.33012 / |
| Published: |
Elsevier Ltd
2022
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130144978&doi=10.1016%2fj.fuel.2022.124569&partnerID=40&md5=cd74933c230631dbe848a735805ef4e7 http://eprints.utp.edu.my/33012/ |
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