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Investigating dust explosibility using exploratory data analysis
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DOI：10.1016/j.psep.2025.108241.png)
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Abstract
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Dust explosibility using exploratory data analysis on explosibility testing data and physico-chemical parameters of dust samples was investigated. The analysis was founded on explosion severity testing data, key influencing factors (e.g., particle size distribution prior to dispersion, nominal dust loading, inter-particle spacing, and number particle density in the explosion chamber), and relevant physical and chemical parameters, including density, thermal conductivity, specific heat capacity, and specific heat of reaction. The correlation coefficients of selected factors and influencing features for the maximum explosion pressure and maximum rate of pressure rise were computed and visually depicted for the given dust samples. For better understanding via simpler representation in 2D-space, the resulting high-dimensional datasets from dust explosibility testing and physico-chemical properties were processed using an unsupervised data-driven technique— namely, principal component analysis, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection. By providing statistical analyses to understand the interdependence of key physico-chemical parameters influencing dust explosibility, this work can help in further exploration of dust explosions and devising strategies for safer handling and processing of different dusts.
Keywords:
Dust explosion
Explosion pressure
Correlation plot
Feature influence
UMAP
T-SNE
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