Underground Gold Mine Research Articles

Experimental Investigation into Deploying a Wi-Fi6 Mesh System for Underground Gold and Platinum Mine Stopes

Stopes suffer from unreliable wireless communication due to their harsh environment. There is a lack of confidence within industry regarding the effectiveness of existing solutions in providing reliable high-bandwidth performance in hard rock stopes. This work proposes that Wi-Fi6 is a good candidate for reliable high-bandwidth communications in underground hard rock stopes. Experiments in a tunnel and mine stope were conducted to evaluate the performance of Wi-Fi6 in terms of latency, jitter, and throughput. Different criteria, such as multi-hop systems, varying multipath, mesh routing protocols, and frequencies at different bandwidths, were used to evaluate performance. The results show that Wi-Fi6 performance is greater in stopes compared to tunnels. Signal quality evaluations were conducted using the Asus RT-AX53U running OpenWrt, and an additional experiment was conducted on the nrf7002dk running Zephyr OS to evaluate the power consumption of Wi-Fi6 against the industry standard for low-powered wireless communications, IEEE 802.15.4. Wi-Fi6 was found to be more power-efficient than IEEE 802.15.4 for Mbps communications. These experiments highlight the signal robustness of Wi-Fi6 in stope environments and also highlights its low-powered nature. This work also highlights the performance of the two most widely used open-source mesh routing protocols for Wi-Fi.

Baseline Study and Statistical Analysis of Natural Radioactivity, Radon, and Soil Properties in Proposed Underground Mine in Prestea Huni-Valley Municipality of Western Region, Ghana

The study aims to establish a natural radioactivity and radon gas baseline for the proposed concession for an underground gold mine in the Bonteboni within the Prestea Hun-Valley Municipality of the Western Region, Ghana. The CR-39 and HPGe detectors were used to determine radon gas and 226Ra, 232Th, and 40K concentrations with sieving and weighing methods to determine the porosity and composition of soils, in sixty (60) soil samples and one hundred twenty (120) dwellings. The studied data for dwellings were found to range from 82.9 to 165.8 Bq/m3 (131.0 ± 12.7 Bq/m3). The radionuclides of 226Ra, 232Th, and 40K and soil radon gas were in the range of 12.5–35.9 Bq/kg (23.3 ± 0.9 Bq/kg), 35.8–134.7 Bq/kg (83.2 ± 3.7 Bq/kg), 30.4–324.6 Bq/kg (143.2 ± 11.3 Bq/kg) and 8.0–19.3 (14.7 ± 0.4 µBqm−2 h−1), respectively. Indoor radon gas was found in increasing order in dwelling types as clay > sandcrete > wooden while the natural radionuclides were also found to follow the order 40K > 232Th > 226Ra. Sixty-three dwellings obtained indoor radon levels above the World Health Organization’s recommended limit of 100 Bq/m3. Fifteen locations had levels of the radionuclides 226Ra and 232Th exceeding guidelines set by the UNSCEAR. The effective doses due to natural radionuclides were found to be less than 1 mSv/yr with thirty-five locations having values greater than the ICRP’s lower recommended limit of 3 mSv/yr. The ventilation systems were found to have a greater influence on the indoor radon concentration in different dwellings. The linkage and composition analysis between the porosity and soil particles indicated a direct impact on natural radionuclides and radon levels, thereby influencing the amount of radiation exposure to the public and environment.

Radiological Impact Assessment of Soil and Rock Samples in Underground Goldmine

Radiological Impact Assessment of Soil and Rock Samples in Underground Goldmine

Hybrid method for analyzing air thermal conditions in underground mines

Thermal prediction of underground mine air is required to develop control measures against heat problems. Researchers have extensively studied this topic using numerical simulations; however, these require long processing times. Recently, researchers have begun using artificial intelligence algorithms; however, the predictive capabilities of the model are still limited because an intelligent system is formed from field measurement data. This study presents a fast and accurate prediction of the Wet Bulb Globe Temperature (WBGT) in underground mines using a hybrid integrated numerical method and an adaptive neuro fuzzy inference system (ANFIS) method. The mine air thermal conditions in various scenarios were analyzed by numerical simulation, and the results were utilized to develop intelligence for ANFIS model-based predictors. A case study was conducted in two underground gold mine areas to demonstrate the effectiveness of this method. The ANFIS model was trained and tested with 81 scenarios generated from numerical simulations. Accurate predictors were obtained, with a coefficient of determination (R2) of 0.98 and 0.97. In addition to predicting the WBGT, the developed ANFIS model optimized the selection of the auxiliary fan power, minimizing the power consumption while simultaneously providing a comfortable WBGT.

Real-time multi-agent fleet management strategy for autonomous underground mines vehicles

ABSTRACT This paper proposes a real-time multi-agent fleet management strategy for autonomous underground mines vehicles. The fleet management strategy is based on multi-agent technology and includes a novel variation of the Contract-Net protocol. This paper also proposes a set of conflict management procedures to deal with the narrow nature of underground drifts, as well as the sequencing of trucks’ loading activities. This strategy is tested in a simulated environment based on an industrial case study. Both the strategy and the test environment were implanted using AnyLogic. More specifically, the fleet management activities addressed are dispatching, routing and traffic management of mining vehicles, which deal respectively with the assignment of the next destination to a vehicle that has just completed a task; the choice of the route to be followed to reach the selected destination; and traffic coordination in the underground transportation network, made up of one-lane bi-directional road segments. To evaluate the proposed solution, an agent-based simulation model of a Canadian underground gold mine is implemented with AnyLogic. Results show that the proposed coordination strategy outperform the one currently employed strategy by the mine under investigation.

TIME SERIES ANALYSIS OF RADON CONCENTRATION AT DIFFERENT DEPTHS IN AN UNDERGROUND GOLDMINE

Indoor radon concentrations were collected monthly over a period of one year in 10 different levels in an underground goldmine and the data was analysed using a four moving average time series to determine the relationship between depths of the underground mine and the indoor radon concentration. The detectors were installed in batches within four quarters. The measurements were carried out using LR115 solid state nuclear track detectors. Statistical models are applied in the prediction and analysis of the radon concentration at various depths. The time series model predicted a positive relationship between the depth of the underground mine and the indoor radon concentration. Thus, elevated radon concentrations are expected at deeper levels of the underground mine, but the relationship was insignificant at the 5% level of significance with a negative adjusted R 2 (R 2 = – 0.021) due to an appropriate engineering and adequate ventilation rate in the underground mine. Keywords : LR115, Radon Concentration, Time Series, Underground goldmine, DOI: 10.7176/APTA/87-03 Publication date: April 30 th 2023

A Network Flow Model for Operational Planning in an Underground Gold Mine

In underground mines, the problem of efficiently scheduling and allocating weekly operations has a major impact on the long-term productivity of the mine. The problem of selecting the optimal locations for operations in an underground gold mine is a complex task. It is not solved by simply selecting the levels with the richest grade because the transportation network for ore in an underground mine has a diverse set of capacity constraints that can frustrate immediate mining of all the richest levels. To solve this scheduling difficulty, we formulated a new mixed-integer network flow model of the problem of weekly allocating mining operations in an underground goldmine such that the total gold mined (in ounces) was maximized subject transportation capacity constraints. The model was applied an underground gold mine in Red Lake, Ontario, Canada. The results were compared to those of a two greedy heuristic models that were designed to represent the decision-making heuristics that are currently used at the mine. It was found that the new model yielded solutions that improved upon the two greedy heuristics by 14.7% and 6.0%, respectively. The results of this research illustrate that the development of this optimization model can support decisions to improve a gold mine’s productivity.

Analysis of heat sources: Alternatives for improving environmental conditions in an underground gold mine

Heat generation in underground mines is a factor of extreme influence on the production, safety and comfort of workers. This article aims to analyze heat sources in an underground mine and propose, as one of the alternatives to improve ventilation conditions, replace the diesel fleet with electric. The case study shows that this is the second source of heat, being the first autocompression, the second diesel equipment and the third are the fans. The heat emitted by the rock then stabilizes a certain time having no significance in the temperature in the year of 2019, but in 2026 it will be a significant heat source. This evaluation was carried out in a gold mine near Belo Horizonte, capital of the State of Minas Gerais using the software Ventsim. In the study, sensitive heat and latent heat would be reduced by about 56% and 80%, respectively, if the change is made. This reduction in the heat generated by the system may improve working conditions because of lower temperature and gas concentration, which reflect on the safety conditions for higher worker's efficiency.

Optimization of Truck–Loader Matching Based on a Simulation Method for Underground Mines

The choice of transportation system has an important impact on the production efficiency and economic behavior of underground mines. Trackless vehicle transportation has gradually become the main method in underground mines because mining companies have realized that mining efficiency can be improved using advanced vehicle mechanization and automation in the mining process. The extracted ore is loaded onto trucks by loaders in situ, then the trucks drive to ore passes for unloading Trucks load and unload ore in a cyclical manner between stopes and ore passes. Numerous trucks drive in tunnels simultaneously to achieve production targets, and there are interactions and influences among trucks, such as blocking and queuing, due to limited underground space. To address this issue, a transportation route model was built, and the ore transportation process was divided into three parts, including ore loading, truck transportation, and ore unloading. The simulation method was applied to optimize the number of loaders and trucks under the constraints of stope production capacity, transportation route and capacity, and vehicle capacity, to achieve the optimal vehicle utilization rate and transportation capability. The Monte Carlo simulation method was utilized to take the uncertainties of the transportation parameters into account to improve the robustness of the simulation results. The model was verified using the case study of an underground gold mine located in Shandong Province, China, with the objective of accomplishing optimal truck–loader matching considering various stopes in a mining area.

A Goal Programming Model for Dispatching Trucks in an Underground Gold Mine

The cost of transporting mined materials in an underground mine is major. This cost typically represents between 50 to 60 percent of a mine’s total operating costs. The problem of dispatching trucks in an underground gold mine is of major economic importance and warrants the use of a decision support model. The developments of a realistic decision-support model for the dispatching problem in an underground gold mine were addressed in this paper. The problem must address multiple conflicting objectives, and therefore, a goal programming model was formulated. The model was applied to a case study, the Red Lake underground gold mine, in Ontario, Canada. The results showed major improvements in meeting the multiple objectives of this problem versus a single objective model. The results also illustrate the flexibility that the dispatching problem (in underground gold mines) yields when solved for multiple objectives using a goal programming model.

Assessing health risk associated with uranium in Rietspruit water, far West Rand goldfield, South Africa

Uranium, U, as a radiological and chemically toxic element has detrimental impacts on human health when ingested at elevated concentration in water. Effluents from an underground gold mine located in the head water region of the Rietspruit contaminated the stream with waterborne uranium. The Rietspruit is a tributary of the Vaal River and subsequently flows through residential and agricultural land. Water samples from the stream were collected and analysed using inductively coupled plasma mass spectrometry to determine the concentrations of dissolved U. The maximum concentration of U recorded was 781.9 µg/L at the mine from where it decreases with growing distance from the mine. Results from calculations showed that the maximum annual effective dose at the mine was above the regulatory limit for public exposure for all age groups. The radiological risk associated with consumption of untreated water from the Rietspruit is lower than the chemical risk. The chemical risk ranges from 0 to 37.2 while the highest life-time cancer risk was 1.7 E-03 for morbidity cancer risk and 1.1 E-03 for mortality cancer risk. The chemical risk analysis showed that within 24 km of downstream of the mine, stream users are exposed to toxic U levels. Therefore, adequate interventions by relevant government agencies are required.

A Network Flow Model for Operational Planning in an Underground Gold Mine

The difficulty of effectively planning and assigning weekly activities has a significant influence on the long-term productivity of an underground mine. It is an especially difficult task to choose the best places for operations inside an underground gold mine. It cannot be resolved by only selecting the levels with the highest grade of ore because the underground mine’s ore transport network has a range of capacity limitations that may prohibit the immediate mining of all the levels with the highest grade. To solve this scheduling difficulty, we formulated a new mixed-integer network flow model of the problem of weekly allocating mining operations in an underground gold mine such that the total gold mined (in ounces) was maximized subject to the transportation capacity constraints. The model was applied to an underground gold mine in Red Lake, Ontario, Canada. The results were compared to those of two greedy heuristic models that were designed to represent the decision-making heuristics that are currently used at the mine. It was found that the new model yielded solutions that improved upon the two greedy heuristics by 14.7% and 6.0%, respectively. The results of this research illustrate that the development of this optimization model can support decisions to improve a gold mine’s productivity.

Measurements and Models of 915 MHz LoRa Radio Propagation in an Underground Gold Mine.

Underground mining increasingly relies on wireless communications for its operations. The move to automating many underground mining processes makes an understanding of the propagation characteristics of key wireless technologies underground a topic of considerable importance. LoRa has great potential for communications in underground mines, but data on its propagation are quite scarce. In this paper, we describe our measurements of LoRa radio propagation in an underground gold mine. We took measurements in an extraction tunnel with line of sight and in extraction and access tunnels without line of sight. We observed excellent propagation, both with and without line of sight. Our observations support claims by others that the steel-lined tunnels act as a waveguide. As well as reporting measurements, we also developed models of propagation. For line of sight, we show that pathloss is well modelled by a power law with pathloss index of 1.25 and that variability of signal strength is well modelled by a lognormal distribution. We also successfully modelled propagation without line of sight over short distances using a Fresnel Diffraction and Free Space model.

Effects evaluation of Heat Stress Index and workload to miner’s fatigue level in underground gold mining area PT Dwinad Nusa Sejahtera

Mining is an activity with a high risk of accidents in open pit and underground mining sites. Various factors that cause accidents have been found through accident investigation, such as miners’ fatigue. Miner’s fatigue can be caused by environmental factors and workload that can be controlled to make a safe and comfortable working environment and prevent accidents. This research objective is to evaluate the relationship between environment factors in the form of heat stress index using humidex method and workload to miner’s fatigue level in the underground mining area PT. Dwinad Nusa Sejahtera. This research was done by measuring the working environment to know humidex, workload and miners fatigue level. Working environment conditions in the underground gold mine of PT. Dwinad Nusa Sejahtera is in a hot and humid condition with wet temperature range are 28.5–32.9°C, dry temperature range are 29.7–33.0°C, globe temperature range are 29.7–33.5°C wet bulb globe temperature range are 29.0–32.1°C, relative humidity range are 83.1–100% and humidex are 49.5–59.5°C. Multivariate analysis of miner’s fatigue level in all activity groups shows that the humidex variable gives more significant effects than the workload variable.

The Occurrence of Platinum (Pt) and Skaergaardite (Pd Cu) in the Hutti Underground Gold Mines, Eastern Dharwar Craton, Karnataka, India

Abstract The novelty of this study consists, use of the Powder X-Ray Diffraction (PXRD) technique facility at CSIR-NGRI to report the occurrence of platinum and skaergaardite (Pd Cu) in the Hutti underground gold mines. This study utilized a quartz-bearing sample from the Hutti underground gold mines. One of the split samples were analyzed by PXRD. In this study, quartz samples are found to be associated with sulphides composed of pyrite, chalcopyrite, and arseno-pyrite with intense chemical alterations. The mineral phase of skaergaardite shows a strong intensity at 2θ 43.5° and confirmed with database of International Centre for Diffraction Data Powder Diffraction File – ICDD-2021-PDF4+ PDF00-057-0606 and native platinum, syn (Pt) Pt 0.0999 Sn 0.001 matched with PDF 04-001-3300. Further research work is planned on this interesting mineral association with primary gold ore in Hutti underground gold mine.

A Goal Programming Model for Dispatching Trucks in an Underground Gold Mine

The cost of transporting mined material in an underground mine is major. This cost typically represents between 50 to 60 percent of a mine’s total operating costs. The problem of dispatching trucks in an underground gold mine is, therefore, of major economic importance and warrants the use of a decision support model. The developments of a realistic decision-support model for the dispatching problem in an underground gold mine is addressed in this paper. The problem must address multiple conflicting objectives and therefore a goal programming model was formulated. The model was applied to a case study, the Red Lake underground gold mine, in Ontario, Canada. The results showed major improvements in meeting the multiple objectives of this problem versus a single objective model. The results illustrate the flexibility that the dispatching problem (in underground gold mines) yields when solved for multiple objectives using a goal programming model.

Integrated stochastic optimization of stope design and long-term underground mine production scheduling

In the commonly used underground mine planning framework, mine design is first established and is the main input for the subsequent long-term mine production scheduling optimization. This sequential optimization approach cannot, therefore, capture the synergies between the involved planning steps, generating solutions that depart substantially from a global optimum. In addition, traditional underground mine planning methods for stope design and life-of-mine production scheduling are deterministic and are based on a single estimated orebody model. As a result, the uncertainty and variability in grades and material types are not incorporated into the optimization process, resulting in designs that misrepresent all high-, medium- and low-grade stoping volumes and production schedules with misleading forecasts. A two-stage stochastic integer program (SIP) for integrated optimization of stope and development network designs and an underground mine production scheduling are proposed for the sublevel open stoping mining method under grade uncertainty and variability, quantified by a set of geostatistical simulations of the mineral deposit considered. Assuming a mine is accessed through a shaft, the model defines a schedule of levels and stopes, which aims to maximize the discounted revenues, minimize development costs, and manage the risk of not meeting production targets, while satisfying geotechnical constraints. The practical aspects of the proposed method are presented through an application at an underground gold mine. A comparison with the stepwise framework, where the stope design is input to a subsequent optimization of the production schedule, shows that the proposed approach provides a physically different design and production schedule with an 11% higher net present value (NPV) and a life-of-mine that is two years shorter, affirming the advantages of the integrated optimization process.

A Goal Programming Model for Dispatching Trucks in an Underground Gold Mine

The cost of transporting mined material in an underground mine is major. This cost typically represents between 50 to 60 percent of a mine’s total operating costs. The problem of dispatching trucks in an underground gold mine is, therefore, of major economic importance and warrants the use of a decision support model. The developments of a realistic decision-support model for the dispatching problem in an underground gold mine is addressed in this paper. The problem must address multiple conflicting objectives and therefore a goal programming model was formulated. The model was applied to a case study, the Red Lake underground gold mine, in Ontario, Canada. The results showed major improvements in meeting the multiple objectives of this problem versus a single objective model. The results illustrate the flexibility that the dispatching problem (in underground gold mines) yields when solved for multiple objectives using a goal programming model.

The Clean Water Act and biosolids: A 45‐year chronological review of biosolids land application research in Colorado

The 1972 U.S. Clean Water Act set forth the generation of biosolids. In Colorado, biosolids land application research began in 1976 and continues today. Pastureland research suggested that sewage effluent could effectively be land applied to benefit aboveground plant growth and to polish water prior to reaching receiving waters. Forest wildfire-affected ecosystems can also benefit from biosolids applications; application rates of up to 80 Mg ha-1 can lead to greater plant establishment, soil microbial activity, and nutrient turnover and reduced nutrient and heavy metal concentrations in runoff below livestock and USEPA drinking water standards. Long-term (24-yr) observations in oil shale-mined lands showed that biosolids (up to 224 Mg ha-1 ) can have a positive effect on microbial-mediated nutrient cycling and, in turn, on aboveground plant community structure. Biosolids applications of up to 40 Mg ha-1 in high-elevation shrubland ecosystems, dominated by Mo-containing shale deposits, can aid in reducing imbalances between Mo and Cu in soils and plants; excessive plant Mo, when consumed by ruminants, can lead to molybdenosis. Biosolids and lime applications (both at 224 Mg ha-1 ) have been shown to improve long-term reclamation success on acid-generating, heavy metal-containing fluvial mine tailings. Thirty years of grazing land research, focused on soil and aboveground plant benefits, illustrate that soil health and plant productivity can be improved to the greatest extent at biosolids application rates close to 10 Mg ha-1 . Finally, 40 yr of dryland agroecosystem research (a) have helped identify biosolids N fertilizer equivalency (∼8kg N Mg-1 ) and thus dryland winter wheat application rates (e.g., 4.5-6.7 dry Mg ha-1 ); (b) have identified first-year mineralization rates of 25-32%; (c) dispute the "time bomb" theory by showing that plant metal uptake follows an exponential rise to a maximum; (d) showcase economic return to producers via increased wheat grain protein content; (e) suggest that biosolids-borne proteins and their degradation products are labile C and N sources; (f) have led to long-term tracking of micronutrients and heavy metals in soils and revealed that plants-soil concentrations will not lead to groundwater degradation and that plants are safe for human consumption; and (g) have shown that biosolids provide Zn, helping to overcome soil deficiencies and enhancing Zn biofortification in wheat grain. This latter point is important because ∼2 billion people globally suffer from Zn deficiencies. Forty-five years of research in Colorado have proven that biosolids can enhance environmental quality, improve soil health, and produce healthy food products.

Evolution models of the damage to the near-field rocks surrounding the drift under the disturbance caused by extraction of the longhole stope

Strong blasting disturbances and excavation unloading effects may result in rib spalling and roof collapse of the near-field rocks surrounding the drift during longhole stope mining. An underground gold mine in Shandong Province, China, was selected as a case study to investigate the evolution of the damage to the near-field rocks surrounding the drift through theoretical analysis and field tests, and the relationship between the convergence deformation and damage zone radius of the rock surrounding the drift was established. The results of this study revealed that the convergent deformation of the near-field rocks surrounding the drift exhibited a stepwise increase with time. At the moment of stope blasting, the maximum increment of the convergent deformation of the rock surrounding the drift reached 30.90 mm. Moreover, the convergence deformation of the rock surrounding the drift exhibited exponential decay with increasing distance from the stope boundary. The area within the vicinity of the drift and 7.32 m from the stope boundary was defined as the strongly affected zone, and the area within 7.32–21.62 m of the stope boundary was defined as the moderately affected zone. In view of the functional relationship between the convergence deformation and the damage zone radius of the rock surrounding the drift, a method of calculating the damage zone depth of the rock surrounding the drift was established by considering the effects of the deformation relief before convergence monitoring and the disturbance caused by the extraction of the longhole stope based on the unified strength theory. The error between the damage zone depth obtained using the proposed method and the actual value was less than 3.00%. It was found that the increment of the damage zone depth reached 2.07 m in the strongly affected zone and the average increment was 1.76 m. The method developed in this study can be used to assess the depth of the damage zone in the near-field rocks surrounding the drift in the longhole stope in similar mines.