Modelling external particle jet formation in explosive granular dispersal systems

We investigate the evolution of an external particle jet in a dense particle bed subjected to a radially divergent air-blast. Both random and single-mode perturbations are considered. By analysing the particle dynamics, we show that the Rayleigh–Taylor instability (RTI), the Richtmyer–Meshkov instability (RMI) and large particle inertia contribute to the formation of the external jet. The external particle jet exhibits a spike-like structure at its top and a bubble-like structure near its bottom. As the expanding particle bed lowers the internal gas pressure, particles near the bubble experience strong inward coupling forces and undergo RTI with variable acceleration. Meanwhile, particles in the spike experience weak gas–particle coupling and collision forces due to large particle inertia and low particle volume fraction, respectively. Consequently, the particles in the spike retain a nearly constant velocity, in contrast to the accelerating spikes observed in cylindrical RTI. To investigate the contributions of RMI to the particle jet growth, we track the trough-near particles in the single-mode perturbation case. It is revealed that the trough-near particles accelerate under the perturbation-induced pressure gradient, overtaking the crest-near particles and inducing phase inversion, thereby resulting in an increase in jet length. We establish a linear-growth model for the jet length increment, similar to the planar Richtmyer–Meshkov impulsive model. Combined with the jet-length-increment model, we propose an external-particle-jet-length model that is consistent with both numerical and experimental results for diverse initial gas pocket central pressures and particle bed thicknesses.

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Publication Details

Journal
Journal of Fluid Mechanics
Published
2025-11-26
DOI
https://doi.org/10.1017/jfm.2025.10807
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
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article

Modelling external particle jet formation in explosive granular dispersal systems

Yue Yang, Baolin Tian, Junsheng Zeng, Yifeng He
Journal of Fluid Mechanics
Particle Dynamics in Fluid Flows
article

Modelling external particle jet formation in explosive granular dispersal systems

Yue Yang, Baolin Tian, Junsheng Zeng, Yifeng He
article en

Abstract

We investigate the evolution of an external particle jet in a dense particle bed subjected to a radially divergent air-blast. Both random and single-mode perturbations are considered. By analysing the particle dynamics, we show that the Rayleigh–Taylor instability (RTI), the Richtmyer–Meshkov instability (RMI) and large particle inertia contribute to the formation of the external jet. The external particle jet exhibits a spike-like structure at its top and a bubble-like structure near its bottom. As the expanding particle bed lowers the internal gas pressure, particles near the bubble experience strong inward coupling forces and undergo RTI with variable acceleration. Meanwhile, particles in the spike experience weak gas–particle coupling and collision forces due to large particle inertia and low particle volume fraction, respectively. Consequently, the particles in the spike retain a nearly constant velocity, in contrast to the accelerating spikes observed in cylindrical RTI. To investigate the contributions of RMI to the particle jet growth, we track the trough-near particles in the single-mode perturbation case. It is revealed that the trough-near particles accelerate under the perturbation-induced pressure gradient, overtaking the crest-near particles and inducing phase inversion, thereby resulting in an increase in jet length. We establish a linear-growth model for the jet length increment, similar to the planar Richtmyer–Meshkov impulsive model. Combined with the jet-length-increment model, we propose an external-particle-jet-length model that is consistent with both numerical and experimental results for diverse initial gas pocket central pressures and particle bed thicknesses.

Journal of Fluid MechanicsVol. 1024
Peking University (CN), Shanghai Zhangjiang Laboratory (CN), Czech Academy of Sciences, Institute of Mathematics (CZ), Beihang University (CN)
Openalex Percentile: Top 55%
Particle Dynamics in Fluid Flows
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