Filtern
Dokumenttyp
Sprache
- Englisch (3)
Schlagworte
- Explosives (3) (entfernen)
Organisationseinheit der BAM
Shock tube systems are non-electric explosive fuses employed in blasting and demolition applications to trigger the detonation of explosive charges. Their working principle is based on the explosive reaction of a fine explosive powder on the tubing's inner surface, generating a shock wave traveling at a velocity of 2,100 m/s along the length of the tube, without destroying it. One of
the key aspects of the manufacturing process of these shock tubes is the size and morphology of the explosive powder grains and their distribution on the inner wall of the tube, in order to propagate the shockwave efficiently and reliably. For the first time, synchrotron X-ray computed tomography has been used to characterize non-destructively the explosive powder grains, typically Al/HMX between 10 and 20 μm in size, in terms of morphology and 3D distribution but also to characterise the presence and location of defects
within the shock tube walls.
The mixture of ammonium nitrate (AN) prills and fuel oil (FO), usually referred to as ANFO, is extensively used in the mining industry as a bulk explosive. One of the major performance predictors of ANFO mixtures is the fuel oil retention, which is itself governed by the complex pore structure of the AN prills. In this study, we present how X-ray computed tomography (XCT), and the associated advanced data processing workflow, can be used to fully characterise the structure and morphology of AN prills. We show that structural parameters such as volume fraction of the different phases and morphological parameters such as specific surface area and shape factor can be reliably extracted from the XCT data, and that there is a good agreement with the measured oil retention values. Importantly, oil retention measurements (qualifying the efficiency of ANFO as explosives) correlate well with the specific surface area determined by XCT. XCT can therefore be employed non-destructively; it can accurately evaluate and characterise porosity in ammonium nitrate prills, and even predict their efficiency.