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Experimental study of detonation of large-scale powder–droplet–vapor mixtures

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Abstract

Large-scale experiments were carried out to investigate the detonation performance of a 1600-\(\hbox {m}^{3}\) ternary cloud consisting of aluminum powder, fuel droplets, and vapor, which were dispersed by a central explosive in a cylindrically stratified configuration. High-frame-rate video cameras and pressure gauges were used to analyze the large-scale explosive dispersal of the mixture and the ensuing blast wave generated by the detonation of the cloud. Special attention was focused on the effect of the descending motion of the charge on the detonation performance of the dispersed ternary cloud. The charge was parachuted by an ensemble of apparatus from the designated height in order to achieve the required terminal velocity when the central explosive was detonated. A descending charge with a terminal velocity of 32 m/s produced a cloud with discernably increased concentration compared with that dispersed from a stationary charge, the detonation of which hence generates a significantly enhanced blast wave beyond the scaled distance of \(6\,\hbox {m}/\hbox {kg}^{1/3}\). The results also show the influence of the descending motion of the charge on the jetting phenomenon and the distorted shock front.

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Acknowledgements

The authors gratefully acknowledge the support from the National Natural Science Foundation of China (Grant No. 11302029).

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Authors and Affiliations

  1. State Key Laboratory of Explosive Science and Technology, Beijing Institute of Technology, Beijing, 100081, China

    C.-H. Bai & K. Xue

  2. North China Institute of Science and Technology, Yanjiao, Beijing-East, 101601, China

    Y. Wang

  3. Department of Mechanical Engineering, Stony Brook University, Stony Brook, NY, 11794-2300, USA

    L.-F. Wang

Authors
  1. C.-H. Bai
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  2. Y. Wang
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  3. K. Xue
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  4. L.-F. Wang
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Corresponding author

Correspondence to K. Xue.

Additional information

Communicated by D. Frost and A. Higgins.

Appendix: Setup of numerical simulations

Appendix: Setup of numerical simulations

All computations were performed using AUTODYN, a general-purpose nonlinear dynamics modeling and simulation software. A Lagrangian processor is used to model the thin-walled aluminum outer casing and the thin-walled steel inner casing. The burster charge (TNT), multiphase payload—which is substituted by water—gaseous detonation products, and the surrounding air are modeled using the multimaterial Euler processors. Different regions of the air/outer casing/payload/inner casing/explosive model are allowed to interact and self-interact using the AUTODYN interaction options.

Fig. 14
figure 14

Schematic of the computational model

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Table 1 Material models used in the present simulations
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The computational model is identical to the actual major charge as illustrated in Fig. 14. A cylindrical barrel with a outer diameter of 370 mm and an overall height of 1150 mm is filled with water (substitute of the payload) to its top. The thickness of the wall is 3 mm. Sixteen longitudinal notches with a depth of 0.6 mm are cut into the surface of the barrel. A 1.08-kg cylindrical TNT explosive with the length of the barrel is buried into water along the centerline of the barrel. The central explosive is wrapped by a cylindrical inner casing with a thickness of 2 mm. Due to the inherent axial symmetry of the setup, this problem is analyzed as a 3D axisymmetric problem.

The following five materials are utilized within the computational domains: air, steel 1006 (inner casing), Al7039 (outer casing), water (payload), and TNT (dispersing explosive). Respective material models are listed in Table 1. The values of all the material parameters for each material are available in the AUTODYN materials library. A standard mesh-sensitivity analysis is carried out (the results not shown for brevity) in order to ensure that the results obtained are insensitive to the size of the cells used.

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Bai, CH., Wang, Y., Xue, K. et al. Experimental study of detonation of large-scale powder–droplet–vapor mixtures. Shock Waves 28, 599–611 (2018). https://doi.org/10.1007/s00193-017-0795-8

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  • DOI: https://doi.org/10.1007/s00193-017-0795-8

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