Assessment and prediction of airblast overpressure

© 2016 Dr. Alan B. RichardsThis thesis deals predominantly with the assessment and prediction of airblast overpressure resulting from blasting in the mining, quarrying, and construction industries. Some of the meteorological modelling techniques also have a significant application in the control of airblast for military testing purposes. Predictive assessment of airblast overpressure requires that significant factors be identified, and their effect quantified. Commonly used blast vibration control techniques involve relating blast vibration levels to charge mass and distance. Although this simple approach provides usable outcomes for ground transmitted vibration in many cases, it has a more limited application for the prediction of airblast, due an increase in the number of significant factors involved. Significant factors affecting airblast overpressure from blasting are charge mass, distance from blast, face height and orientation, topographic shielding, stemming height and type, blasthole diameter and burden, burden and spacing, sequential initiation timing, and meteorological conditions. This thesis gives details of two predictive models that have been developed by the author to evaluate the effect of face height and orientation (the elliptical airblast model), and the combined effect of the spacing between blastholes, and the sequential detonation sequence of each blasthole (the wavefront reinforcement model). Also described is a predictive methodology that combines outputs from several models that have been developed to assess the effect of each significant factor. In addition to the two models listed above, these include the charge mass / confinement and the charge mass / frequency relationships which were developed by Adrian Moore, the graphical shielding model which was developed jointly by the author and Adrian Moore, and a modelling system that has been developed by the author in collaboration with others to assess the effect of the meteorological conditions. Outcomes from this research have already gained acceptance by end users and are currently in use by mining operators in the Hunter Valley region in New South Wales, Australia. This is illustrated by a number of case studies presented as part of the thesis