| 1 |
Quantitative Structure-Property Relationship (QSPR) models for Minimum Ignition Energy (MIE) prediction of combustible dusts using machine learning
Chaudhari P, Ade N, Perez LM, Kolis S, Mashuga CV
Powder Technology, 372, 227, 2020 |
| 2 |
Effect of particle size polydispersity on dust cloud minimum ignition energy
Castellanos D, Bagaria P, Mashuga CV
Powder Technology, 367, 782, 2020 |
| 3 |
Measurement of minimum ignition energies (MIEs) of dust clouds - History, present, future
Eckhoff RK
Journal of Loss Prevention in The Process Industries, 61, 147, 2019 |
| 4 |
Effect of particle morphology on dust minimum ignition energy
Bagaria P, Prasad S, Sun JZ, Bellair R, Mashuga C
Powder Technology, 355, 1, 2019 |
| 5 |
Effect of Impurities Argon and Moisture Additives on Laser Ignition of n-Decane/Air Mixtures
Mokrani N, Rudz S, Gillard P
Combustion Science and Technology, 188(11-12), 1741, 2016 |
| 6 |
Minimum ignition energy of medicinal powder - Florfenicol and Tilmicosin
Zhang XL, Shen Q, Shen XB, Zhang ZK, Xu SJ, Ye SJ
Journal of Loss Prevention in The Process Industries, 39, 30, 2016 |
| 7 |
Measurements of minimum ignition energy in premixed laminar methane/air flow by using laser induced spark
Beduneau JL, Kim B, Zimmer L, Ikeda Y
Combustion and Flame, 132(4), 653, 2003 |
