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Probabilistic modeling of explosibility of low reactivity dusts

Mohammad Alauddin, Albert Addo, Faisal Khan and Paul Amyotte

Reliability Engineering and System Safety, 2025, vol. 257, issue PB

Abstract: This work presents probabilistic models to estimate dust explosion severity parameters of low reactivity dusts while capturing uncertainty in the parameter estimations. The marginally explosible behavior of combustible dusts has also been explored for different ignition energies and dust concentrations. Low-reactivity dusts are mostly characterized by low-KSt values (i.e., KSt < 45 bar.m/s in the 20-L chamber), also referred to as marginally explosible. These dusts pose a major problem regarding explosion classification due to the uncertainty they present on the industrial scale (i.e., explodes in the 20-L chamber but not in the 1-m3 chamber, and vice versa). The proposed model has been used to study the explosibility of carbon black and zinc dust samples based on data generated in a 20-L Siwek chamber. The outcomes in terms of variability of maximum explosion pressure and maximum rate of pressure rise have been represented using maximum probable values and credible ranges. The likelihood of selected dusts exhibiting marginal explosibility characteristics at varying concentrations and ignition energies is also presented. The findings can be useful for making dust explosion safety decisions and facilitating risk reduction opportunities in the processing and handling of explosible dust.

Keywords: Explosible dust; Probabilistic modeling; Bayesian neural network; Sensitivity analysis; Explosion severity parameters (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:257:y:2025:i:pb:s095183202500064x

DOI: 10.1016/j.ress.2025.110861

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