Empirical Models of Zones Protecting Against Coal Dust Explosion

Explosion dust particle size measurements.

In situ measurements of the sizes and concentrations of dust particles generated by the detonation of high explosives in clay soil near Leesville, La., sandy clay soil near Huntsville, Ala., and sandy soils near Orogrande, N.M. are reported. Measurements were generally made within 1 m of the surface (in one case 10 m) at distances ranging from 10 to approximately 50 m from the detonation point ...

Overall characterization of cork dust explosion.

Explosibility and ignitability studies of air/cork dust mixtures were conducted in a near-spherical 22.7 L explosibility test chamber using pyrotechnic ignitors and in a furnace of 1.23 L. The suspension dust burned as air-dispersed dust clouds and the uniformity of the dispersion inside the chamber was evaluated through optical dust probes. The range of tested particle sizes went from a mass m...

Dust Explosion Propagation: Myths and Realities

How does limestone rock dust prevent coal dust explosions in coal mines?

Coal dust explosions in underground coal mines are pre­ vented by a generous application of rock dust (usually lime­ stone). If an explosion should occur, the rock dust disperses, mixes with the coal dust and prevents fl ame propagation by acting as a thermal inhibitor or heat sink. To investigate this process in more detail, a number of ex­ plosion experiments using various coal dust and limes...

Defense-gan: Protecting Classifiers against Adversarial Attacks Using Generative Models

In recent years, deep neural network approaches have been widely adopted for machine learning tasks, including classification. However, they were shown to be vulnerable to adversarial perturbations: carefully crafted small perturbations can cause misclassification of legitimate images. We propose Defense-GAN, a new framework leveraging the expressive capability of generative models to defend de...