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By Robert Cefalo

Drill and Blast Engineer Abstract In 2019, the Bingham Canyon Mine, owned by Rio Tinto Kennecott Utah Copper Company, mined through the active underground that dewaters the pit. The active underground required the limitation of vibrations to avoid catastrophic damage or damage that would require work to the shotcrete and additional roof support. The surface design of the current sector next to and through portions of the active underground. The drill and blast group was required to test site law vibration parameters to ensure that vibration limitations were lower than limits set by the underground management team. Seismographs were used to validate the vibration prediction model and check performance of blast in areas of the underground. The bench conditions and limited pounds-per-delay created large obstacles for the blasting team, making it difficult for them to accurately load the pattern with the number of decks in the blast. Methods were used to improve the loading instructions and ensure that each hole achieved pound requirements based off of the distance to the underground that it was designed to protect. The project evolved from start to finish, and the process to estimate distances and loading improved to make the blast a more repeatable process for the size of the project.

By David Jones, Jeff Bregar, Damien Bell

We have analyzed overpressure and ground vibration measurements for construction blasting for a large pipeline project. These field-measured levels have been compared to existing prediction curves in the literature and new curves have been proposed for overpressure and ground vibration for pipeline construction blasting activities.

Feb 1, 2020

By M E. Hanson, K Chong, R H. Jacobson, S C. Way

To create conditions for economic rates of mineral recovery in a deep, hard rock mass, enhancement of naturally occurring permeability is necessary, and may be achieved through explosives detonated in boreholes. Previous theories of explosively created permeability are reviewed and found to relate permeability solely to the degree of fracturing, neglecting porosity. A theory is presented that includes both fracture density and porosity, and its results are applied, together with a knowledge of explosive behavior, to derive design parameters for in-situ mining.

Jan 1, 1983

By John Cory, Ran Tamir

Blasting data analytics are being increasing used to increase mining productivity, reduce mining costs, maximize high margin aggregate products, and to reduce fines. Three examples will be illustrated using simple models to maximize the percentage of blasted rock within established dimensions and reduce fines-one from video fragmentation distribution information, the second from sieved crusher fragmentation data, and the third from plant production data. In addition, the use of sieved crusher results to determine blasting related fines and the use of mine productivity data to maximize aggregate sizes when pattern (burden and spacing) areas are changed will be illustrated

Jan 1, 2012

By Dale Preece, Joergen Pilz, Zavis Zavodni

An overland conveyor was constructed at a surface coal mine to reduce the truck haul distance and make the operation more efficient. An important element in this system is a truck dump facility to transfer coal from truck to conveyor. Mechanically stabilized earth retaining walls were employed to accommodate the coal processing equipment, including the crusher, in this facility. These retaining walls are close enough to the pits being mined that blasting induced vibrations must be considered in analyses of the wall structural stability.

Jan 1, 2010

By Ulf Nyberg, Changping Yi, Daniel Johansson, Håkan Schunnesson

To investigate the non-ideal detonation properties of aluminized emulsion explosive, a series of tests for an emulsion explosive with 5% aluminum powder additive were carried out with mortar confinement. The velocity of detonation (VoD) and the curvature of the detonation front for different charge diameters were obtained from the tests with a high-speed camera. The burning process of the aluminized emulsion explosive has been modelled with the ignition and growth (I&G) flow model in the LS-DYNA code. A routine based on the optimization program LS-OPT code was developed to identify the parameters in the burning rate function with the detonation velocities and the front curvature radii from two tests. A Perl code was implemented in the routine and was used to calculate the VoD, fit the detonation front and obtain the detonation front curvature radii. The calibrated parameters were used to predict the VoDs and the detonation front curvature radii for the rest cases. The results indicate that both the VoDs and the detonation front curvature radii from the numerical modelling are in good agreement with the experimental results. The numerical results also indicate that the variety of the burn fraction and the peak pressure with the change of charge diameters is reasonable with the calibrated parameters.

By Ulf Nyberg, Changping Yi, Daniel Johansson, Håkan Schunnesson

To investigate the non-ideal detonation properties of aluminized emulsion explosive, a series of tests for an emulsion explosive with 5% aluminum powder additive were carried out with mortar confinement. The velocity of detonation (VoD) and the curvature of the detonation front for different charge diameters were obtained from the tests with a high-speed camera

Feb 1, 2020

By Dale S. Preece, Ruilin Yang

"Air-decks are often employed for presplitting along the final highwall of a blast and are sometimes also included at the bottom or in the middle of explosive columns in the production portion of a blast. Shock wave physics is an important part of air-deck behavior since the bulk explosives in the column impart a shock into the air-deck where the air shock then passes through the air-deck at a rapidlyattenuating velocity. Through both high-fidelity modeling and shock physics theory it is shown that theresulting pressure in the air-deck is two orders of magnitude less than the detonation pressure of theexplosive."

Jan 1, 2017

By Nolan Eckroade

The demand for blast optimization within the quarrying industry calls for more effective, faster and safer methods of quantification of blast performance. Drones provide the ability to safely and quickly capture high resolution imagery of a muckpile for use in fragmentation photo analysis. Oversize material within a muckpile is an expensive and universal problem affecting quarries, especially in situations where cap rock is present. Although the amount of oversize material in a blast is a key indicator of blast performance, it is difficult, hazardous and slow to measure across an entire muckpile using traditional methods. By piloting a drone using an automated flight plan with set amount of overlap across images, the images can be processed into a single, high resolution orthomosaic image for use in fragmentation photo analysis software.

Jan 1, 2018

By David Nemir, Jan Beck

A challenge in materials science is the production of a bulk solid material from a powder precursor. One solution is to use shockwave consolidation whereby a ductile tube is loaded with the powder of interest and then surrounded by an explosive. A detonator at the top of the explosive column initiates a symmetrical high-pressure pulse that moves inward and down the tube, causing the tube to deform and the interior powders to consolidate into a dense, well bonded bulk material.

Jan 1, 2016

By Ruilin Yang

Kinematic approach of blast modeling refers to using the velocity, strain, or displacement as controlling parameters to model blasting, rather than the stress and the material constitutive relations. The rock stiffness or constitutive relations is very hard or impossible to obtain due to the complexity of the rock mass property.

Feb 1, 2020

By Ankit Jha, Sudarshan Rajagopal, Purushotham Tukkaraja

Geologic structures are one of the crucial parameters in blast design. Structural geology and rock properties influence drilling patterns, blast layout, and initiation systems. A comprehensive understanding of structural characteristics is essential to achieve the desired blasting objectives. This paper aims to identify geologic features in a bench using images obtained from the drone. Images obtained from mine site are annotated for geological features such as faults and joints. Semantic segmentation of images is achieved using an encoder and decoder structure available in the machine-learning pipeline. The encoder consists of initial convolution and pooling layers to capture essential features of the geology and rock patterns from two-dimensional RGB images. Batch normalization is used to put all the features on the same scale. These images are then inputted as training data for the machine-learning algorithm. Machine learning model is trained on sub-section of interest to achieve reasonable accuracy. Initially, 1000 best annotations were used to train the model and additional samples were added later to achieve more accuracy and avoid iteration of machine learning model in wrong convergence. After the model achieves reasonable accuracy, it is used to recognize geological features on new data. Geological features identified on the new data can be used by the blasting crew in blast design and keeps the geological maps updated that can help the geotechnical team.

By Emmett J. Ientilucci, Martin Held, Xuesong Liu

Mining is crucial for advancing technology and science by providing essential resources and materials. Quarry blasting, a necessary process in mining, releases these resources and chemicals, driving research and engineering improvements. However, NOx (nitrogen oxides) is an undesired contaminant produced during quarry blasts, posing a significant negative impact on mining activities. Therefore, detecting and quantifying NOx emissions is essential for designing effective blasts, analyzing their dynamics, and reducing contaminant production. Image processing and machine learning, including deep learning methods, have been applied to solve smoke plume detection and segmentation tasks. Most research has focused on smoke from campfires or forest fires, which are important for early fire and smoke detection. However, there is limited research on quarry blast smoke using machine learning methods, which presents challenges for recognizing the smoke plume from complex background scenarios and objects, including collapsed rocks, scattered soil dust and dirt, and the dynamic movement of the scene due to blast vibrations. Detecting NOx within the smoke plumes is further challenging because NOx must be distinguished from the overall smoke plume, as they share many common spatial features. To resolve this issue, we propose an ensemble method for NOx detection that combines smoke plume segmentation with NOx fume detection. First, we apply a smoke plume segmentation model to identify the smoke plume regions. Then, we use these masked-out smoke plume regions to detect NOx based on its unique color features. The first stage of the ensemble method helps block out complicated confusers in the background, such as reddish and brownish dirt. Next, we specifically design a color classifier for NOx to further improve its sensitivity. We evaluate the overall video-wise performance using accuracy, false alarm, and miss rates based on sampled image frames from videos. Additionally, we assess the mean Intersection over Union (mIoU) for smoke plume segmentation and the mean Average Precision (mAP) for image-wise performance from an algorithmic perspective. In summary, this paper represents the first attempt to apply machine learning approaches to NOx detection in a memory-efficient and time-efficient manner.

Jan 21, 2025

By L C. Taylor

Very small scale testing has been shown to be able to predict quite accurately, in many situations, the results of full scale testing. Small scale tests are more cost efficient, easily observed, and easily instrumented than full scale tests. Over the past 10 years small scale testing in the Dynamic Effects Laboratory at the University of Maryland has been used to successfully study the response of structures and soils to explosive detonation. Small scale testing has been successfully used to predict full scale results in underwater cratering and channeling, the loading (both pressures and impulse) on vehicles due to the detonation of buried charges, the positive effects of bottom shaping for military vehicles to reduce this loading, and the movement of obstacles underwater by explosive charges.

Jan 1, 2012

By U. Steiner

Electronic detonators have been in commercial use for a decade, with an excellent safety record. This paper lists known incidents involving electronic detonators. Typical standards required by regulatory bodies for static electricity and electromagnetic fields are reviewed. The performance of some detonators is compared to these standards; in general the minimum standards are easily exceeded. The general resistance of electronic detonators to extraneous electrical energy that can be derived from the body of test results is compared to danger levels for exposure of humans to these energies; it is shown that electronic detonators can safely tolerate higher electrical energies than people can. This comparison includes comparable data for electric detonators, which are shown to be more vulnerable to extraneous electrical energy than people are. Electronic detonators also bring significant safety benefits in blasting due to their testability, two-way communications, reliability, programmability and precision. The links between these attributes and enhanced safety are discussed with examples from actual blasting. Although electronic detonators are usually more vulnerable to extraneous electricity than non-electric initiation systems, the paper shows that the net safety benefit in handling and blasting is in favor of electronic detonators, which are the safest initiation system that has ever been offered to the mining industry.

Jan 1, 2010

By Pavel A. Torres, Darwin Torres, Sandro Huaman

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.

Feb 1, 2020

By Lon Santis, David Buckwalter, Ken Steinmetz

This paper describes a magazine security system using two readily available cellular telephone-based technologies. The system is comprised of vibration sensors and remote cameras. The system is used at a Bureau of Alcohol, Tobacco, Firearms, and Explosives (ATF) licensed explosives storage location in Pennsylvania to comply with PA Department of Environmental Protection (PADEP) regulations. The system provides instant notification to the licensee via cellular modems, text messaging, phone call, and e-mail. Likewise, the licensee can control the system remotely over the internet and using text messaging commands. The vibration sensors attach to the door of the metal type I magazines magnetically and detect any movement or vibration. The cameras trigger on movement and thermal radiation changes and can also be triggered manually to check alarms received from the vibration sensors. The previous system was comprised of a base unit and magnetic strips. The magnetic strips were powered by a hard line from the control unit and mounted on the doors and top of magazine creating a bond, that when broken triggered an alarm. Our main issues with the unit were the delay in alert times and tech support. Because of these issues, we decided an upgrade was necessary. Compared to that previous system used at this site, these new systems are highly affordable, carefree and reliable.

Jan 1, 2014

By Anderson da Cunha Meireles, Pedro Garcia, Ernst Young, Leandro Coelho, Carlos Eduardo Soares Feliciano, Key Fonseca de Lima

Rock blasting is a crucial technique employed in mining construction and quarrying industries to fragment large rocks into smaller, more manageable pieces. However, it often generates ground vibrations that can pose significant challenges. This study explores the application of Conformal Prediction (CP) in the context of rock blasting to develop predictive models that estimate blasting-induced vibrations and quantify the associated uncertainties. Various machine learning models were integrated within the CP framework using MAPIE and CREPES libraries. The results demonstrated the effectiveness of CP in providing statistically reliable prediction intervals, making it particularly useful for applications where the stakes of underestimating uncertainty can be high.

Jan 21, 2025

By A. Gontijo, A. Matos, P. Lincoln, L. Fonsecail

This paper investigates how to manage and model the vibrations caused by rock blasting in a Brazilian underground mine. Considering the frequent detonations and the previous lack of effective vibration control, understanding, and reducing the impact of these seismic waves is critical. We emphasize the use of the near field model technique, which considers the varied physical properties of different rocks, optimizes blasting plans, and minimizes damage to the rock mass. We detail a case study that demonstrates a comprehensive approach to vibration control. The discussion includes the creation of a monitoring plan, the methodology used, results and the specific challenges and solutions found during the blasting process. This study provides a practical guide for similar future projects. Finally, we present a predictive model based on the collected data, offering insights into the vibrations caused by blasting. This model helps decision-makers minimize the risk of displacing rock blocks in the blasting area, improving safety and operational efficiency

Jan 1, 2024

By Allan King

Ammonium Nitrate (AN) is most commonly encountered as either a prilled solid or a highly concentrated aqueous solution, with or without organic ( e.g amine) nitrates. Under certain conditions of fire exposure involving prilled or solid AN, the molten state can be formed. The shock sensitivity of the molten material at temperatures greater than 220 Celsius has been found to be much higher than that of the prilled or solid form. Molten AN can be a precursor to events leading up to explosion of a bulk prill storage pile as a result of fire exposure. The explosion hazards presented by molten AN are a function of two factors; 1) its shock sensitivity and the deflagration to detonation ( DDT ) properties of the molten material, and: 2) the ability of large masses of unfueled prilled AN to be initiated and detonate. This paper presents the results of tests designed to determine the shock initiation and DDT properties of the solid ( prilled ) and molten AN.

Jan 1, 2008