Combustion and Flame· 2026Q1
A Gas–Solid Two-Phase Mechanistic Model for Predicting the Minimum Ignition Energy of Explosive Dust Clouds
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- 2026year
Short summary
A new gas-solid two-phase mechanistic model accurately predicts the minimum ignition energy (MIE) of explosive dust clouds, validated by RDX dust experiments showing a 1.39% error (36.5 mJ predicted vs. 36 ± 4 mJ experimental).
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Key points
- Developed a gas-solid two-phase mechanistic model for predicting MIE in explosive dust clouds.
- Model incorporates radiation-particle interaction, pyrolysis, intermediate accumulation, and gas-phase heat release.
- A composite ignition criterion ensures physically meaningful ignition identification.
- Model validated against RDX dust clouds, predicting MIE of 36.5 mJ (1.39% error vs. 36 ± 4 mJ experimental).
- Model successfully predicted MIE for HMX and TNT dust clouds, demonstrating transferability.
AI-generated from the title and abstract; the full text is not read.
Abstract
Minimum ignition energy (MIE) is a key parameter for characterizing the ignition sensitivity and explosion hazard of explosive dust clouds, yet its experimental determination is hazardous and mechanistic prediction remains limited. In this study, a gas–solid two-phase mechanistic model is developed for the numerical prediction of MIE in explosive dust clouds. The model accounts for the key processes governing threshold ignition, including radiation–particle interaction, solid-phase pyrolysis, accumulation of combustible intermediates and reaction activity, and the resulting gas-phase heat release. A composite ignition criterion, incorporating both near-source self-sustainability and spatial propagation conditions, is proposed to ensure physically meaningful ignition identification. Taking RDX dust clouds as a representative system, the model is validated against experimental data, predicting an MIE of 36.5 mJ in good agreement with the reported value of 36 ± 4 mJ (relative error of 1.39%). Additional comparisons with HMX and TNT dust clouds also show good agreement with experimental MIE data, supporting the physical basis and transferability of the reduced lumped-variable framework. The model is further employed to examine the influence of particle size, dust concentration, ambient humidity, ambient temperature, ambient pressure, and hot source temperature on MIE. The present study provides a physically interpretable numerical framework for MIE prediction of explosive dust clouds and offers theoretical support for critical ignition analysis and explosion-hazard assessment of energetic dust systems.Novelty and significance statement: This work provides a mechanistic framework for predicting the minimum ignition energy of explosive dust clouds, a problem that remains difficult to resolve experimentally and is still insufficiently described by existing models. Its novelty lies in integrating primary radiative heating, particle re-radiation feedback, pyrolysis-driven intermediate supply, and reaction-activity buildup into a unified gas–solid two-phase threshold-ignition model. The significance of this study is that it moves MIE prediction beyond empirical correlation or purely thermal descriptions, enabling physically interpretable analysis of near-threshold ignition behaviour and multi-factor effects in explosive dust systems.
The authors' abstract, as published at the source. Combustion and Flame, 2026 · DOI ↗
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Field: Aerospace Engineering
Aerospace EngineeringEngineering