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By Randy Martin, Jessie Bonner, Peter Boyd, Mark Leidig, Timothy Rath

We conducted the Vermont Damage Experiment in central Vermont during July 2008. Five single-hole explosions with yields ranging from 60.8 kg (134 lbs) to 122.5 kg (270 lbs) were detonated in homogeneous, low fracture density granite. The goal of the experiment was to quantify the different levels of rock damage around the source and then relate the seismic wave generation to the degree and distribution of damage and fragmentation. In addition, explosives with different velocities of detonation (VOD), including black powder (0.53 km/sec; 1737 ft/sec), heavy ANFO (4.8 km/sec; 15734 ft/sec), and COMP B (8.1 km/sec; 26574 ft/sec) were detonated to relate the VOD to seismic wave generation and extent of damage zones in the source region. Over 120 seismic stations were deployed to record the explosions at distances between 5 m and 30 km (15 ft to 19 miles).

Jan 1, 2010

By Robert Hopler

209. Nitro-glycerine is produced by the action of nitric and sulphuric acids on glycerine, and is a heavy liquid of oily appearance, of specific gravity about 1•6, varying from colourless when quite pure to a yellow or brownish yellow. It is of a very sweet taste, and without odour, and is an active poison. Mere handling of it will in most persons induce sickness and headache. It explodes when heated to about 360° F. or from shock, but in small quantities it ignites and burns with some difficulty by the mere contact of flame.

Jan 1, 2011

By Paul Worsey, Yasutaka Dote

The choreography of large fireworks displays dictates electric initiation for precise timing. It has been common practice to pre-squib products before transportation for reducing set up time. A number of fatal accidents transferring pre-squibbed product during transportation suggests that there is a problem with impact sensitivity. The aim of this paper is to quantify the impact sensitivity of the various configurations of initiating materials used in display fireworks.

Jan 1, 2009

By Ed O'Connor, Per-Anders Persson, Manhong Zhou

This chapter deals with the concepts of shock waves and detonation waves together, because a detonation wave is really a shock wave, supported by the explosive reaction that the shock wave ignites and propagates as it travels through the explosive material. In the context of rock blasting, furthermore, there is justification for treating shock waves and detonation waves together, because the mechanical effect of the detonation in an explosive in a drillhole in rock is propagated and its effects are spread throughout the surrounding rock by means of a shock wave. The overall performance of an explosive in rock blasting or any other application is of course dependent on how much thermal energy is released in the chemical reaction that occurs when the material detonates, and on how much useful mechanical work the reaction products can do as they expand. A major portion of this chapter deals with the prediction and measurement of explosive performance, a subject which is now still in a process of rapid development.

Jan 1, 1997

By W B. Gregg

"A review, update, and expansion of Thiokol’s presentation at BAl’s Fiih High Tech Seminar titled ‘ADetonator - An Era of Precision in All-Electronic Detonators” is provided herein (and should be considered as a supplement to that publication). Thiokol is currently in the development and field evaluation phase of activities for our ACCUBLASTTM all-electronic detonator. The ACCUBLASTTM detonator uses a semiconductor bridge (an electronic match) in place of a conventional hot wire to initiate a safer, less sensitive material, titanium subhydride potassium perchlorate. The device is programmable to provide blast delays in one millisecond increments ranging from 1 to 500 milliseconds. The ACCUBLASTTM detonator combines an all-electronic programmable timer coupled with a semiconductor bridge to ensure detonation timing accuracy with +I00 microsecond precision. Initial development and field testing have been completed. These tests have verified ACCUBLASTTM detonators’ precision."

Jan 1, 1995

By Natalie Zeleznik, Brian Hawkins, David Bradley, Rachel Gooding, Patrick Wilson

"An Event Tree Analysis (ETA) is an established approach for logically deconstructing and assessing scenarios for probabilistic risk assessment. This deconstruction into a series of understandable eventsfacilitates probability estimation for explicitly defined explosive terrorism scenarios with consideration of modes of possible failure during execution (a scenario is defined through selection of a target, selection of an explosive material, and interdiction prior to arriving at general target location, etc.). Further, each event is decomposed into a range of possible outcomes. The physical action or reality ofthe outcome is statistically represented by “branches” of the event tree (e.g., the terrorist may choose totarget a stadium, hotel, or subway; terrorists may be successful or unsuccessful in acquiring the material)."

Jan 1, 2017

By Robert B. Hopler

Reefs, exposed rocks, and fast currents made the Hell Gate section of New York's East River a treacherous passage ever since man attempted to sail through the area. As the harbor's importance grew, attempts to improve the channel were made, starting in 1851. This paper discusses the first major organized effort to clear the area, which began in 1869 and culminated in a single large blast in September 1876.

Jan 1, 1981

By Dr. Calvin J. Konya, Anthony Konya

Blast violence has always been a criteria that has been analyzed without a quantitative approach relying on opinions of those viewing the blast and oftentimes does not transfer between open-pit mines, quarries, and construction projects. Added to this confusion is that on many regulate projects, such as U.S. Army Corp of Engineers construction projects, the definition of "flyrock" or violence can vary, and contractors must be able to meet this requirement. This project analyzed hundreds of blasts from various construction projects to develop a new metric to determine blast violence - the Violence Factor.

Feb 1, 2020

By Dr. Calvin J. Konya, Anthony Konya

Blast violence has always been a criteria that has been analyzed without a quantitative approach relying on opinions of those viewing the blast and oftentimes does not transfer between open-pit mines, quarries, and construction projects. Added to this confusion is that on many regulate projects, such as U.S. Army Corp of Engineers construction projects, the definition of "flyrock" or violence can vary, and contractors must be able to meet this requirement. This project analyzed hundreds of blasts from various construction projects to develop a new metric to determine blast violence - the Violence Factor. If a blast is fired using 1.25" (32 mm) diameter product and a 10-foot (3 m) bench, vertical uplift of 60 feet (18.3 m) would be considered extreme and violent by any professional in the industry. However, a 100-foot-high (30.5 m) bench using 12" (305 mm) bulk product, having a vertical displacement of 60 feet(18.3 m)might be considered typical or non-worrisome. This is where violence factor is beneficial as itprovides a system of scaling the violence of a blast based on the bench height to give manager a keyperformance indicator (KPI) which is easy to monitor and can provide a large amount of information onsite-specific design variables for their performance on blasting and the end-results of the blast. The Violence Factor of a blast is an integer which is scaled to determine how high vertical uplift of a blast is compared to the bench height. This project analyzed numerous blasts to determine what blast design variables contribute to violence. This violence has also been shown to occur when a non-optimal breakage mechanism, cratering, occurs and the design criteria that lead to this cratering. Finally, this paper will present typical results of various levels of violence including backbreak, fragmentation, and muckpile configuration.

By Matt Brandon

This case study demonstrates how integrating drone and GPS surveying with 3D modeling software creates more effective blast designs that address specific geotechnical challenges while improving safety and blast performance. In this case study an 80ft (25m) highwall experienced recurring slip plane failures exacerbated by a previously mined 40ft (12m) bench that removed back support, creating an unstable triangular rock mass. Previous blasting along this wall displaced the upper 40ft (12m) of material, opening geological discontinuities and causing progressive slope failures that compromised crew safety and blast effectiveness. High-resolution drone photogrammetry, GPS surveying, and laser measurements were employed to precisely map slip planes, bedding planes, and fault structures within the bench geometry. These geological features were imported into 3D design software to develop a shot pattern that strategically utilizes natural rock discontinuities rather than working against them. GPS-guided hole placement ensured accurate field implementation, while marking geological features on the surface of the bench provided visual references for the blast crew. The final blast design positioned the last row of holes to break preferentially along an existing slip plane while avoiding intersecting the next slip plane behind the blast. Explosive loading and timing sequences were adjusted based on the hole location relative to the 3D geological model to optimize fragmentation while maintaining wall stability. The optimized design improved highwall stability significantly, by reducing the slip plane failure mechanism that had previously compromised operations. Measurable improvements included enhanced highwall stability, reduced back-break, improved blast performance, and reduced safety risks for equipment operators and blast crews. Two subsequent shots using identical methodology were able to remove the rest of this problem area, confirming the repeatability and effectiveness of this integrated approach. This methodology demonstrates practical integration of surveying technologies with geological understanding to solve complex blasting challenges. Accurate 3D modeling of geological features enables blast designers to work with natural rock structures rather than against them, resulting in safer, more effective blasting practices. This case study shows the value of understanding the precise locations of geological features for optimizing blast design and provides a replicable process for addressing geotechnical challenges in blasting operations.

Jan 26, 2026

By Dale S. Preece, J Paul Tidman, Stephen H. Chung

A discrete element computer program named DMC_BLAST (Distinct Motion Code) has been under development since 1987 for modeling rock blasting (Preece & Taylor, 1989). This program employs explicit time integration and uses spherical or cylindrical elements that are represented as circles in 2-D. DMC_BLAST calculations compare favorably with data from actual bench blasts (Preece et al, 1993).

Jan 1, 1997

By Vitor Fonseca de Barcelos, Jair Carlos Koppe

Our society is experiencing a digital revolution. Technology is demonstrating its significant potential for mining industry. In this paper are presented the measured and estimated impacts of applying new technologies on blasting operations in a copper mine.

Feb 1, 2020

By Koichi Kurokawa, Takeo Ueda, Yoji Tasaki, Masashi Nakano

We have developed a new firing system which simplifies the handling and extensively increases the safety in electric blasting operations. Based on the principle of the transformer, this system is operated as follows: When a high frequency alternating current pulse (70-110 kHz) is applied to the lead wire and connecting wire (primary circuit), magnetic flux is generated in the transcore, and an induced current flows through the looped leg wire of the detonator (secondary circuit). Then the detonators are ignited by the induced current.

Jan 1, 1986

By Saeed Karimifard, Saman Nouranian, Shahram Tafazoli, Bahram Sameti, Frank Chu, Caitlin McKinnon, Tetiana Konstantynivska, Glen Turner

Continuing blast optimization is the cornerstone of any mine-to-mill approach, and particle size analysis is a key metric for meeting blast targets to reduce overall energy consumption and operating costs. To ensure the statistical validity of particle size data, it is important to sample material frequently. In most mines and quarries, the blasted material is loaded onto haul trucks and then transferred to the crusher; measuring the particle size of each haul truck load therefore provides an adequate sampling rate. We propose a particle size analysis solution for haul trucks that does not impact current operational workflows. Using artificial intelligence (AI) and 3D imaging technology, our solution reliably localizes and identifies haul trucks as they drive by, then accurately calculates the particle size distribution of the visible material in each truck load. In this paper, we identify the challenges of designing and implementing the proposed solution and explain the strategies we employ to overcome these. We also discuss a method for boulder detection that leverages the existing deep learning architecture to significantly reduce crusher downtime caused by oversized rocks. Finally, we present field data from a trial installation. To evaluate each change made to the blast design, it is necessary to measure the effect on particle size. An accurate particle size analysis solution is therefore the first step towards optimizing blasting practices and reducing energy consumption throughout the comminution circuit.

By Lon Santis

This paper describes several applications of quantitative risk assessment in the management of commercial explosives operations. The Institute of Makers of Explosives’ (IME) quantitative risk assessment software modeling program IMESAFR was used for this analysis. Modeled activities include the unloading of a ship at port, locating a safe haven, and dealing with encroachment on a manufacturing facility. The layout of actual explosives sites were used for the analysis. The risk of fatality is analyzed and shown it can be used to make informed operational decisions for each activity. A study of the risks to individuals from activities involving commercial explosives compared to individual risks from other daily activities or exposures is also presented.

Jan 1, 2008

By Javier Illanes, Felipe Moroni

In recent years, implementation of Artificial Intelligence and Machine Learning model technology has gained ground in almost every aspect of human activities. The mining industry has not been foreign to these applications, with advantages including the creation of new optimization methods and the elimination of repetitive tasks. Those applications have been implemented in multiple operative areas, from preventive conveyor belt maintenance to energy optimization for minimizing environmental impact. The blasting process aims to use the energy liberated by the detonation of explosives to break the rock mass according to specifications that facilitate the comminution process. To optimize this process, the energy delivered must correspond to the necessary amount to exceed the tensional and compressional resistance of the rock mass. If the energy applied is insufficient, the rock will not reach the desired fragmentation level and the processing plant may incur additional costs. On the other hand, if the energy level required is exceeded, we incur increased blasting costs that correspond to excess explosive used. Optimization of this aspect of the mining process has major impact in the processing chain reflected in lower costs, efficient resources consumption and environmental impact. The Design for Outcome technology (DfO), developed by Orica, is used to characterize the rock mass in detail to classify, borehole by borehole, the rock mass relative hardness to deliver the adequate energy level to achieve optimal fragmentation. This technology uses information collected by drill sensors, producing data typically referred to as Measure While Drilling (MWD) data to classify the rock mass into domains that can later be used to apply optimal blast designs. In DfO, the data flow is fully automated, starting with the data produced by the drilling system and uploaded to the cloud, which is then domained using Machine Learning (ML) techniques, and then published for consumption using a web interface. Automated explosives loading rules are then generated for each rock mass domain, ensuring that for each borehole, the adequate explosive energy is delivered to achieve the desired fragmentation results with unprecedented accuracy. The application of machine learning techniques allows us to optimize the blasting process results by leveraging a deeper understanding of the rock mass. Applying these optimization techniques, we obtain considerable economic benefits, decrease resources consumption, and achieve a more sustainable mining operation. The application of DfO in a Chilean mining operation allowed the characterization of their rock mass into four domains and established specific explosive loading rules for each one. A 60kUSD reduction in explosives cost was achieved during the test period, while maintaining the desired fragmentation results and expected dig rate. These outcomes were the result of a comparison between the blasting costs used applying the technology mentioned above and a “traditional” classification of the rock mass with the corresponding blasting practices.

Jan 21, 2025

By Edward J. Jr Walter, Edward J. Walter

The vibration problem is approximately fifty years old. The original investigation of the U.S. Bureau of Mines was begun in 1930. Significant investigation into the problem was done by Crandell, Langefors, et al, Edwards and Northwood, and again by the Bureau of Mines. This resulted in an effective Safe Limit standard expressed in particle velocity as 2.0 inches per second.

Jan 1, 1979

By Charles Clark, Mark Mukhija, Jaime Klein

Comminution – the reduction in size of solid materials – is the most energy intensive component of the mining process (Bauer, 2015). It is estimated that comminution consumes around three percent of all electricity generated in the world (Ceecthefuture.org, 2017). On an energy equivalent basis, downstream processing consumes six times more energy than drilling and blasting (Kanchibotla, Sarma et al., 2014).

Jan 1, 2018

By Dale S. Preece, Stephen H. Chung

"A discrete element computer program named DMC_BLAST (Distinct Motion Code) has been underdevelopment since 1987 for modeling rock blasting (Preece & Taylor, 1989). This program employsexplicit time integration and uses spherical or cylindrical elements that are represented as circles in two dimensions (2-D). DMC_BLAST calculations compare favorably with data from actual bench blasts (Preece et al, 1993b)."

Jan 1, 1999

By Dale S. Preece, J Paul Tidman, Stephen H. Chung

A discrete element computer program named DMC_BLAST (Distinct Motion Code) has been under development since 1987 for modeling rock blasting (Preece & Taylor, 1989). This program employs explicit time integration and uses spherical or cylindrical elements that are represented as circles in two dimensions (2-D). DMC_BLAST calculations compare favorably with data from actual bench blasts (Preece et al, 1993).

Jan 1, 1998