A predictive model to assess dust explosionoccurrence

TLDR: In this paper, a conceptual framework is developed to use the existing experimental data on dust explosion parameter to assess the likelihood of a dust explosion in a given facility and a detailed implementation in specific process industries is discussed with case studies.

Abstract: The danger of a dust explosion is difficult to avoid in process facilities where combustible dusts are handled. To develop effective prevention and mitigation strategies, it is very important to understand the interaction among dust explosion controlling parameters and to assess the likelihood of an dust explosion occurrence. Six controlling parameters ( Particle Diameter, Minimum Ignition Energy, Minimum Explosible Concentration, Minimum Ignition Temperature, Limiting Oxygen Concentration and Explosion Pressure) are identified to model a predictive tool which can assess the likelihood of dust explosion in a given operating condition. Experiments have been conducted by the dust explosion researcher to understand the characteristics of these parameters and the generated data has a substantial scope in estimating dust explosion probability with the use of probabilistic approach. A conceptual framework is developed to use the existing experimental data on dust explosion parameter to assess the dust explosion prediction in a given facility. The model is further extended with considering dust classes and a detailed implementation in specific process industries are discussed with case studies. The proposed model can assess the dust explosion probability in a given operating condition at a specific process facility. The assessment can be very helpful to strategies effective prevention and mitigating measures in process industries. Three case studies are discussed in this study to demonstrate the real life application of the model.