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By Brendan Demich, Linda L. Chasko, Brendan Macdonald, Timothy J. Orr, Jessie J. Mechling, Cassandra Hoebbel, Jason Navoyski, William Helfrich, Jessica Cohen, Paul E. Schmidt, Jennica L. Bellanca

The National Institute for Occupational Safety and Health (NIOSH) in partnership with the Mine Safety and Health Administration (MSHA) developed VR Mine Rescue Training (VR-MRT). It is a training platform that allows mine rescue team members to explore virtual emergency scenarios collaboratively. Team members use a head-mounted display to visualize and interact together with equipment, hazards, and dynamic ventilation. All player actions are recorded and displayed for debriefing. Researchers at NIOSH demonstrated the training platform at various mine rescue competitions, including the International Mine Rescue Competition, and collected feedback. Participants’ responses were overwhelmingly positive. This paper describes the development of the software platform and the results of the usability surveys and interviews.

Jun 25, 2023

By Josiah Pohl, Christopher Utter, Kyle Everly, Akshay Chowdu

Battery Electric Vehicles offer increased energy efficiency for open-pit load & haul operations at a potentially lower overall carbon cost. Electrifying a mine’s fleet, however, presents a unique set of operational challenges. In this study, we explore the effects of electrification on productivity at real operations using a Discrete Event Simulator. The model can simulate multiple shifts, a mixed fleet of diesel and electric trucks, charging and refueling stations, trolley systems, and accurate shovel-truck loading cycles. This study helps determine the trade-offs of adopting electric fleets and how they interact with the layout of today's mines.

Jun 25, 2023

By Alessandro Navarra, Aldo Quelopana

For decades, open-pit mine planning algorithms have incorporated geological uncertainty and other elements or characteristics for increasingly realistic representations. Among these complexities is the detailing of downstream processes that occur inside processing plants. Previous studies have demonstrated that the strategic mine plan and mineral concentrator design are coupled, and should therefore be optimized simultaneously within the same quantitative framework. However, existing frameworks offer limited representation of operational modes. This work demonstrates an approach to resolving this gap, in an optimization based on a parallelized Variable Neighborhood Descent (VND). The resulting algorithm embeds mass-balancing linear programming (LP) using a DantzigWolfe decomposition. A case study of a Zn-Pb deposit is presented to show the performance reached.

Jun 25, 2023

By Augusto Andres Torres Toledo, João Felipe Coimbra Leite Costa, Luciano Nunes Capponi, Diego Machado Marques

Short-term mine planning to open pit requires defining diglines to orientate the excavation geometry. In deposits with multiple chemical variables, it is necessary to have more rigorous control over the feeding of the processing plant. This study analyzes the impact of incorporating multiple chemical variables, the risks generated by geological uncertainty, and the number and starting point locations of shovels in the sequential design of diglines. The objective is to maintain and preserve the low-grade variability, required tonnage, and continuity in sequentially selecting blocks. To achieve this, the probability distribution function of each chemical variable is used while attempting to maintain the ore grades as constant as possible. As it is difficult to maintain multiple elements with low variability simultaneously, the relevance of each chemical variable in the economic benefit is identified. Weights are assigned to signal the importance of each element based on its significance in the recovery process. Several diglines, consisting of sequential blocks, were generated on the same seed point to meet the weekly ore demand. Optimizing the stationarity of multiple chemical variables, accessing and reducing the geological uncertainty performed through geostatistical simulation of grades and transfers functions, considering the number and location of shovels, while meeting the operational restrictions of the selected blocks. The optimized digline with the multiple grades as stationary as possible is retained. The process is illustrated in a phosphate mine. The results show that the proposed method is viable and allows for a quick solution.

Jun 25, 2023

By Ademar Lopes, Victor Silva, Heitor Silva, Gustavo Usero, Roberto Rolo, Lucas Pereira, Gabriel Moreira, João Lague, Arthur Endlein, Matheus Feitosa

Grade control models are supposed to provide a higher resolution than long-term or interim models. However, available grids from diamond or reverse circulation drilling do not provide that required resolution. In this study, a geostatistical workflow is proposed to integrate available grade data from production blastholes with its operational parameters taken when drilling downhole. The step of geological logging can be replaced by machine learning models for classifying blastholes into lithologies and hardness classes. Next, indicator and ordinary kriging use the classified blastholes and previous data for estimating the model domains and the grades within each one. The workflow is applied in a world class iron ore mine in Brazil.

Jun 25, 2023

By Katherine Hynard, Colin Eustace

Development quarterly mine plans is generally time-consuming and requires consideration for many operational constraints and competing objectives. With lengthy turnaround times, there is often limited opportunity to adjust the quarterly plan details to account for differences between actual state of the mine operation at the time of execution and expected state at the time that the plan was developed. Actual mining task completion times can vary significantly from the expected task completion times, due to many factors. In the absence of revision to account for differences between the planned and actual state, resource allocations and mining sequences, embodied in the quarterly mine plan may no longer be the best approach at the time of execution to achieve an efficient mining operation. Simulation and optimisation tools can be used to support rapid refinements for development and execution of weekly mine plans. When initialized with an operations data feed to establish the actual state of the mine operation, optimisation models can be used to facilitate both automation and revision of the quarterly plan to produce a weekly or daily plan for execution. This approach can remove much of the manual burden of revision if the existing quarterly plan no longer represents the best approach to meeting production objectives. Following initialisation with mining actuals, simulation models can provide a representation of the range of likely mine operations outcomes. The models can be used to accelerate the planning process by providing visibility of future performance and identifying likely operational issues. They can also be used to test the robustness of the plan with respect to performance variability and response to disturbances. Following identification of issues, simulation models can also be used for evaluating mitigation measures, through automated testing of alternative plans. Integration of mine data feeds with simulation and optimisation tools enables automated optimal responses to variations between the quarterly mine plan and actuals to be tested prior to release of and execution plan and implementation. The use of simulation and optimisation in weekly mine planning will be discussed in this paper with reference to surface mining examples.

Jun 25, 2023

By Jay Nopola, Christopher Johnson, Matthew Minnick, Erik Hemstad, Erik Walega

Mining data collection, storage, and interpretation methods have progressively changed over time. Data collection, for the most part, has transitioned from handwritten notes and logs based on manual gauge readings to real-time data streaming through instrumentation capable of directly communicating with site-based data historians or cloud storage. Data collection and storage have had to adjust commensurately with the volume of data, leading to more complex database architecture. Geoscience interpretation methods have also changed; however, the first goals of modeling and understandings from first principles remain the same and are typically deeply rooted in historical academic work. Machine learning methods are becoming more common, available, and implemented by industry and practitioners. Despite the wide accessibility of machine learning methods, the population of geoscience subject matter experts in the underlying theory of this analysis type is limited. This form of analysis, therefore, must be conducted carefully and in conjunction with subject matter experts, on both machine learning theory and the field it is being applied to. This paper aims to provide background history on data analytics and machine learning, current methods and practices, and high-level geoscience case study examples, as well as take aways regarding the mining industry, potential pitfalls specific to geosciences, and possible perspectives on the direction of artificial intelligence in the future.

Jun 25, 2023

By Miguel Carrera, Jose Arnal, Julian Ortiz, Maarten Haest, Fouad Faraj

ShovelSense is a complete solution for bulk ore sorting at the mine face that combines robust shovel bucket mounted X-ray fluorescence sensors, with real-time material classification, fleet management integration and supporting cloud-based data infrastructure, to ensure each truck always goes to the right destination. Correct truck destinations are a challenge in many current mining settings because the material classification of a truck, which is the key input into the truck destination, is often based on estimates at block resolution (~20x20x15m), with limited adjustment for blast movement and mixing. In this contribution, we present a geostatistical, data driven approach to estimate the potential value of bulk ore sorting at the mine-face for seven open pit mines. The approach is premised on the assumption that truck loads within blocks follow a simple gamma distribution. Standard ore control data from the seven mines have been used to estimate the potential bulk sorting value at these operations and ShovelSense-integrated dispatch datasets have been used to validate these estimates for specific benches on which ShovelSense operated. ShovelSense results validate the ore control data-based value predictions and show how at mine-face bulk ore sorting value varies between distinct deposit types. In general, deposit types that have higher bulk ore grade contrasts, display more potential ShovelSense value. The manuscript concludes with the limitations and opportunities of applying the proposed value estimation approach to evaluate at mine-face bulk ore sorting opportunities for open pit operations.

Jun 25, 2023

By Javad Sattarvand, Milad Ghahramanieisalou

As new technologies are introduced to the mining industry, the challenges related to their safe assimilation and the potential changes they bring to mining techniques necessitate adjustments to the current operations. Predictive simulations are critical to understanding unforeseen scenarios and shifting costly changes from the operational stage to the design. The Digital Twin methodology has gained a lot of attention in recent years. Many industries, from manufacturing to engineering and even social sciences, are adopting this approach to understand better the complex systems they are working with. By considering the enormous expenses and risks related to a pilot project, DT could replace that by acting as a prototype in which realistic tests and simulations are carried out with close to zero cost. DT includes a data hub, simulation and analysis tools, and visualization platforms to enable appropriate designs and monitoring plans focusing on unknown areas. A few examples of DT's application in mining include fleet management, Mine-to-Mill optimization (especially D&B), geotechnical digital twin (gDT), etc. When developing regulations, testing the efficiency of the mine layout, design, and magnitude of the restricted area and its access points, human-machine interactions, risk identification, and management processes, examining the efficacy of control systems, and monitoring, DT could help speed up (or completely replace) the process in the physical world.

Jun 25, 2023

By Jose A. Gomez, Javad Sattarvand

Failures of tailings dams have been happening lately. Due to the lack of laws on particular design criteria and stability requirements related monitoring during construction and maintenance, they are thought to be more fragile than hydraulic dams. Monitoring the dam is therefore necessary to understand its current condition and guarantee its safety. The physical condition of the dam could be evaluated with the early identification of seepage. Additionally, due to their adaptability and capacity for high-resolution data collecting, UAVs are an excellent choice for efficiently covering the tailings dam site. UAVs may capture high-quality photos when equipped with a high-resolution RGB camera, thermal sensors, or multispectral sensors. When these sensors are paired with image processing and machine learning algorithms, the result is a reliable estimate of the dam condition.

Jun 25, 2023

By Cesar Carrasco, Heath Arvidson, Mark Forster

Block models built to represent the geology and rock characteristics of mineral deposits represent huge complex data sets, which form the basis of strategic and business planning, and public reporting of Mineral Resources and Mineral Reserves. Recent advances in cloud computing and database technology developed for the Internet of Things offer a different way of working with these critical data sets. Enabling a cloud based, open data structure with high performance data analytics capability presents a compelling improvement in governance and a democratization of ore body knowledge that can lead to automation use cases that support the digitalization of mining.

Jun 25, 2023

By Angelina Anani, Nathalie Risso, Carlos Olmos de Aguilera

The traditional approach to safety clearance monitoring and proper PPE usage in underground mines is time-consuming, costly, and susceptible to negligence. However, automated real-time monitoring can be implemented using computer vision-based approaches. This study aims to develop a system that provides timely information based on the automatic detection of proper PPE use and safety clearance in underground mines. Deep learning and a decentralized computing structure between the cloud and sensing devices (fog technology) are used. We hypothesize that a camera-based system can provide near real-time assessment of proper PPE use and verified clearance to access restricted areas in underground mines.

Jun 25, 2023

By Christoph Mueller, Grzegorz Tabak

Basing on five years of experience, this paper discusses modern e-drive systems used in underground transport. This covers Energy distribution and cabling principles, inverters and motors as well as auxiliary aggregates. Also an overview of different regimes for battery charging and the energy management and the method of control of the traction are lined out: This means that throttle and brake are not handled separately, but integrated into “longitudinal control” algorithms which assure that a commanded speed is maintained while synchronizing the multi motor systems and taking into account the constraints imposed by e.g. slope grade and battery parameters.

Jun 25, 2023

By Rodrigo Peroni, Vitor Campos

Carajás is one of the largest open pit mines in the world. The mine is comprised by a haul road network more than 100 km long, where the need for good roads is paramount and determining of the truck performances. This work integrates, regarding the ultimate pit design, an approach to consider an economic value to an originally unfit material, assuming it has the appropriate characteristics for haul road construction, which sometimes lies over economic iron ore. This measure demonstrated an improvement in the utilization of resources and guarantee the necessary material to the haul road design and Mining Pads maintenance.

Jun 25, 2023

By Erik Marsh, Frederick C. Harris Jr., Javad Sattarvand, Joshua Dahl, Alireza Kamran Pishhesari

Based on the mine safety and health administration (MSHA)reports, mining truck accidents are among the significant causes of fatalities in the mining industry. The major causes of haulage accidents can be divided into non-driving and driving factors, such as truck-related sudden failures and operator performance. Numerous parameters affect trucks' safe operation, but situational awareness plays a significant role. Due to the distinct structure of mining trucks, making them efficient for mining purposes, the operator has a very limited field of view (FOV), making them prone to accidents resulting in losing lives. The cabin's position blocks the truck's right and rear sides, creating several blind points around it. Aiming to test/train the operator's awareness of the surrounding, a proximity detection system is developed through a multiplayer virtual reality (VR) application to investigate the human factor in equipment collisions. The operators were examined and monitored when asked to conduct what exactly happened in the Marigold mine truck accident without being aware of the scenario. After receiving sound, vibration, and visual alarm warnings, their reaction and performance were analyzed. The platform is developed using the Unity game engine for HTC VIVE virtual reality goggles. An Omni-direction treadmill and a motion simulator platform are utilized for the player and dump truck operators. Fifteen students were monitored when driving the dump truck receiving/not receiving proximity detection alarms. None of them repeated the accident when receiving proximity alarms. Also, they found the visual alarm the most comfortable while driving the truck.

Jun 25, 2023

By Rainer Antretter

The city of Garmisch-Partenkirchen in southern Germany is located at a main transit road to Tyrol in Austria and suffers of a very heavy traffic load. Therefore, the Kramertunnel as a by-pass tunnel is built to release/mitigate the traffic through the city centre. The 3,600 m long single tube road tunnel is designed with a parallel but smaller emergency tunnel and with cross passages, fitted with single- and doublesided emergency bays, a vent shaft, and an intermediate ceiling to separate fresh air supply from the road traffic. The tunnel, concrete lined along its entire length provided the challenge to find smart formwork solutions for quick set-up, repositioning, setup and pouring. Three particularly specific sections are discussed in this paper.

Jun 13, 2023

By Stan Tang, Yiming Sun, S. Amir Reza Beyabanaki, N. Sathi Sathialingam

The Kurve mixed-use development project including a 22-story tower at 2801 Sunset Place was constructed on a site consisting of a roughly rectangular-shaped lot at the intersection of Wilshire Boulevard and Hoover Street in Los Angeles. Two Metro Red Line tunnels, with depths of approximately 30 feet and 58 feet, respectively, cross below the building at distances of approximately 1 foot to over 63 feet from the site. This paper presents numerical modeling performed to evaluate the ground and tunnel behavior in response to building construction. Results of geotechnical instrumentation and monitoring undertaken during the building construction are also discussed.

Jun 13, 2023

By Negar Elhami Khorasani, Anthony Tessari, Nan Hua

Fire hazards can cause severe and irrecoverable damage to reinforced concrete (RC) tunnel linings, threatening the serviceability and resilience of transportation networks. This paper first examines the existing methodologies that are used to classify damage to tunnel linings from fire. These approaches are then supplemented with the results of advanced modeling and inputs from industry experts to propose new fire damage/ repair classifications with the associated thresholds. The results of the presented research can be used to guide fire risk assessment as well as the performance-based design of tunnel fire protection.

Jun 13, 2023

By Savita Schlesinger, Mike Hanna, Nathan Scalla, James O’Shaughnessy, Steve Miller

Loudoun Water’s Quarry A (Milestone Reservoir) project involves conversion of a rock quarry to a billion-gallon raw water reservoir. The project includes a new 40 MGD pump station, deep intake shaft, and three drill and blast intake tunnels for accessing the reservoir. Due to concerns regarding constructability and construction risks, the project design was paused while a Construction Manager At-Risk (CMAR) contractor was procured. The CMAR contractor was engaged collaboratively with the design team to provide risk and constructability input for refining the design. Aspects of the original design, design modifications, and benefits of the CMAR collaboration will be presented.

Jun 13, 2023

By Cary Hirner, Tony Cicchetti, Daniel G. Cressman, Jeff F. Wallace, Prapan Dave, Malcolm Sheehan

The City of Toronto is currently undertaking the design of the Black Creek Sanitary Trunk Sewer Relief Project. The Project involves the design and construction of approximately 20 kilometers of tunnel through shale rock of the Georgian Bay Formation and soft ground soil consisting of glacial till, glaciolacustrine and glaciofluvial sand, silt and clay deposits. The 20 kilometer alignment has been split into four sections of tunnel (1) the 12.9 km, 3.0 meter diameter Keele Trunk Relief Sewer, (2) the 2.9 km, 1.5 meter diameter Keele Trunk Relief Sewer Microtunnel, (3) the 3.9 km, 1.8 meter diameter Jane Relief Sewer, and (4) the 0.5 km,1.5 meter diameter Combined Sewer Overflow Storage Tunnel. Additionally, one 40,000 m3 wet weather flow (WWF) storage tank and numerous WWF connection shafts are to be constructed and connected to the Keele Trunk Relief Sewer to pick up WWF from existing outfalls currently discharging to Black Creek. The anticipated cost of the project is approximately $600 million with construction of the Project’s Phase One Works, the Keele Trunk Relief Sewer and Jane Relief Sewer, scheduled to commence in 2025. This paper provides an overview of the project in terms of the anticipated geotechnical conditions, the scheme developed for design and construction of the tunnel system and the associated schedule and procurement strategy. The consideration for planning of the tunnel system, the risk-based analysis and decision-making process are presented and form the basis for selection of a precast tunnel lining support method in the rock and soft ground.

Jun 13, 2023