Renew your ISEE Membership today! 
Click Here
Given the limited efficiency of blast-induced ground vibrations prediction empirical models, due to the complex geological system from a Peruvian mine. An artificial neural network was built in order to get better results. More accurate and precise predictions allowed the generation of blasting domains for future designs and decision making.
Mina El toro has been making substantial changes in its operation to improve its social impact and productivity. Because of the use of gasified emulsions and electronic initiation system, it was possible to mitigate vibrations and carry out massive blasting, increasing its production by 4.2% and minimizing complaints from communities.
Reactive ground conditions at an open pit manganese mine in the Northern Cape of South Africa resulted in an unexpected detonation.
Site formation works requiring excavation of rock at the Queen Mary Hospital redevelopment site was restricted due to extremely low ground vibration limits. Non-Explosive excavation method called Electro Power Impactor (EPI), sometimes called Plasma Blasting, was utilised to help ensure the rock excavation rate could meet the required programme.
A highwall blast vibration project was carried out to quantify the level of blast vibrations produced from a trim blast in soft rock and a combined production and trim blast in hard rock. Combining production and trim blasts could be performed without exceeding the mine’s vibration limits.
Blasting within 250 ft of a crusher was successfully executed through the application of electronic detonators, 3-D imagery, signature hole analysis, custom loading of blast holes. The blast was well contained, the vibrations were minimal, and there was no flyrock.
The application of the Kuz-Ram model for the prediction of fragmentation is used worldwide, in Coimolache Mine it was used to determine blast domains and optimize the process by obtaining drilling patterns that meet a required X80 and reducing the uncertainty of drilling.
A new technology for energy distribution optimization, supported by NIOSH.