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By Duk-Won Park

Since geologic anomalies are one of the governing factors of instability of underground openings, it is extremely important to know in advance the locations and extent of these anomalies such as faults and weak zones. At an underground coal mine in the Black Warrior Basin, core drilling was conducted to find a fault in an area where they were planning to locate longwall panels and possibly a shaft. Core logging did not provide sufficient information to delineate the exact location, strike, and dip of the fault. However, a high resolution reflection seismic study successfully solved this problem. This experience proved the seismic exploration technique could be used for premining coal exploration by reducing drilling costs and providing more accurate and detailed information about geologic anomalies.

Jan 1, 1988

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 Ravi Sahu, 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.

Feb 1, 2020

By Hector Carreon

This paper presents experimental data for the magnetic field produced by thermoelectric currents around uncracked hard-alpha inclusions in a Ti?6Al?4V specimen under external thermal excitation for different nitrogen content ranging from 1.6% to 5.9%. According to our preliminary results, the magnetic flux density measurements were found to be rather sensitive to changes in nitrogen content with the exception of the intrinsic material background magnetic signal that affected deeply the detectability of inclusions and imperfections in non-contacting thermoelectric measurements. Hopefully, these preliminary results can help identify a non-destructive test method that can detect material inclusions with a level of nitrogen that could be detrimental to Ti?6Al?4V alloy components.

Jan 1, 2009

By Joseph L. Condon

The U.S. Department of the Interior, Bureau of Mines, is doing research on methods to obtain premining information on problems such as detection of old mine workings, abandoned oil wells, channel sands, faults, and other geologic features that are undesirable from a production or safety aspect. Techniques being developed to acquire the necessary information include seismic and electromagnetic. The seismic methods include high-resolution seismic and acoustic methods applied from the surface and inseam channel waves applied under- ground. The electromagnetic, or radar, methods are applied from the surface, from boreholes, and from the working face underground. All of these methods are useful under certain site-specific conditions, but none of these methods is universally applicable for all mining conditions.

Jan 1, 1980

By Arnaud Faucher, Claude Bazin, Marilène Renaud, Mohamed Mai Manga

"Grinding circuits are operated in the presence of disturbances due to ore changes and equipment malfunctions. One of the challenges faced by the operators is the detection of a disturbance, the identification of its origin and of the action needed to minimize its impact on the process. Hydrocyclones overloading, worn or partly plugged apexes of the units of a nest, surging and internal liner detachment may cause a loss of classification capacity and quality. Recovery losses in downstream leaching or flotation circuits justify the effort in developing techniques for the detection of hydrocyclone malfunction. Two approaches for the detection of hydrocyclone fault are presented in this paper. The first proposed method uses the conventional sensors available in a grinding circuit allowing real time detection of hydrocyclone abnormal operation. The second technique is based on the use of vibration sensors installed on the hydrocyclone of a nest. This last technique enables the classification of the hydrocyclone malfunction as surging, overloading and plugged apex. The two techniques can be combined to increase the robustness of the problem detection.INTRODUCTIONHydrocyclones are used for many purposes ranging from water separation, fines removal and obviously for the preparation of the feed for subsequent concentration circuits in a mineral processing plant. The strategic role of the hydrocyclones for the preparation of the feed to the concentration circuit is often underestimated because of their simplicity of operation and robustness (Napier-Munn et al., 1996; McIvor, 1988). It remains that despite their simplicity, hydrocyclones have been studied extensively from 1970 to 1990 with the objective of developing mathematical models of their operation to be incorporated into grinding circuit simulators (Napier-Munn et al., 1996; Lynch, 1977; Flintoff et al., 1987). Such a development effort is already an acknowledgement of the importance of these units in a mineral processing plant. Several authors (Del Villar et al., 1996; Plitt and Kawatra, 1979; Casali et al., 1998) proposed soft sensors to estimate the classification efficiency of hydrocyclones using sensor measurements. However, few of the proposed sensors are used in the industry. More recently several papers were published to discuss the application of 3-D modelling of the hydrocyclones (Narasimha et al., 2005; Cullivan et al., 2004) and sensors (Bond et al., 1999; Neesse et al., 2003; Hou et al., 1998; Olson and Waterman, 2004; Williams et al., 1995; Willams et al., 1997) to help in the detection of hydrocyclone malfunction."

Jan 1, 2010

By X. Shi, N. S. Dala, V. Vallaythan

"Cellular damage induced by silica dust is known to be associated with increased fragility and destabilization or destruction of the cell membranes. The mechanism by which silica dust effects biological membranes is still unknown. Using the ESR spin-trap methodology, we find that hydroxyl radicals are generated in aqueous suspensions of freshly ground silica. The amount of the radicals generated depends on the extent of grinding and ""freshness"" of the dust. Using linoleic acid as a model lipid, we show that the silica dust causes lipid peroxidation via ·OH, 02-, or linoleic acid related radicals as intermediates. Catalase and superoxide dismutase inhibit the formation of these radicals. The results suggest that free radicals associated with freshly ground silica and the related lipid peroxidation of the memberanes may be the starting point of the silicotic processes.INTRODUCTIONDespite considerable-effort over the years, the mechanism by which the quartz particles exert their toxic action on cells and the process(es) by which these actions progress to fibrosis are still not fully understood (1,2). It is generally thought, nevertheless, that the interaction of the quartz particles with the cell membranes is the starting point of the silicotic process (3). We felt that the mechanism of the membrane damage by quartz might involve oxygenated free radicals because (a) a suspension of quartz particles in contact with alveolar macrophages has been reported.(4,5) to initiate an enhancement of lipid peroxidation, defined broadly as the ;oxidative deterioration of polyunsaturated components of lipids, and (b) hydroxyl (·OH) radicals are known to be capable of peroxidation by abstracting hydrogen atoms from cell-membrane lipids (6) and initiating lipid peroxidation in lysosomal membranes (7). Moreover it is known that exposure of cell membranes, fatty acids and unsaturated food oils to ionizing radiation, which generates ·OH. radicals, causes rapid peroxidation (6). Earlier studies o~ the aqueous chemistry of quartz suspensions have reported detection of HzOz (8), implicating the formation of ·OH radicals as transient species, but, we are not aware of any report of the detection of ·OH radicals in quartz suspensions and this provided the motivation for the present undertaking. Since it is known that, because of their high reactivity (hence short life time) in aqueous media, the ·OH radicals cannot be detected via electron spin resonance (ESR) directly (9,10), we have used ESR combined with the spin-trap methodology (9) for studying the •OH formation."

Jan 1, 1988

By N. S. Dalal, B. Jafari, F. H. Y. Green, M. M. Suryan, V. Vallyathan

"Freshly ground and aged anthracite and bituminous coal samples were investigated by electron spin resonance (ESR) spectroscopy to detect the presence, concentration and reactivity of free radicals. Freshly ground anthracite coal produced greater concentration of free radicals than the bituminous coal, and the radical reactivity was also greater for the anthracite. The reactivity of the newly produced free radicals in the anthracite dust correlated with the dust's toxicity. Furthermore similar coal-based free radicals were detected in the lung tissue of autopsied coal miners, suggestive of persistent reactivity by the embedded coal dust leading to the progressive disease process. Results of the studies on the severity of coal workers' pneumoconiosis (CWP) and free radical concentration m lung tissue support this hypothesis.INTRODUCTIONCOAL WORKERS' PNEUMOCONIOSIS (CWP) has been an important topic of concern to miners, mining engineers, epidemiologists and medical researchers for decades. It is well known that the prevalence and severity of CWP differ markedly between different regions and mines despite comparable exposures to respirable dust (REISNER and RoBOCK, 1977; HURLEY et al., 1979). These variations in pathogenicity of coal mine dusts can only partially be explained by differences in the mineral composition and by rank of coal (CHRISTIAN and NELSON, 1978; CHRISTIAN et al., 1979; HATCH et al., 1980). Cytotoxity studies on mammalian cells do not correspond well with the human disease pattern (CHRISTIAN and NELSON, 1978; CHRISTIAN et al., 1979; HATCH et al.,1980; VALL YA THAN et al., 1988). For example, while epidemiological studies of coal miners (REISNER and ROBECK, 1977; HURLEY et al., 1979) indicate that the prevalence of CWP correlates roughly with the rank of coal, such correlation has not yet been established in biological studies, despite considerable effort (CHRISTIAN and NELSON, 1978; CHRISTIAN et al., 1979; HATCH et al., 1980). In order to help resolve this apparent paradox we have undertaken a systematic study to evaluate whether any correlation exists between the concentration of free radicals present in fresh or aged coal dusts from two well-characterized U.S. coals. This study was also prompted in part by observations reported in the literature that organic free radicals can be formed on the surface of freshly fractured coals (LEBEDEV et al., 1978; DULIBA and CLARKSON, 1984). In particular, ARTEMOV and REZNIK (1980) noted that the decay lifetimes and, hence, the reactivity of the organic free radicals formed on crushing Russian coals, .depended"

Jan 1, 1989

By J. ?H. Chen

Remote sensing technologies have been applied to numerous fields and already benefited those in improving efficiency and recognition accuracy. Change of streamflow can be devastating to residents living along riversides. Still it is difficult to detect such deathly change in large area scale by traditional field surveys. The research aims at provision of detecting streamflow change using a mathematic method based on remote sensing technologies. The scope is on remote sensing stream images taken during the invasion by Typhoon Morakot, bringing one of the major catastrophes to Taiwan. An algorithm was adopted to deal with streamflow recognition on RGB images. The algorithm is capable of yielding change measured by meters and illustrates how main streams shift. An practical example for the Baolai area surrounded by Laonong stream shows that the streamflow moved 88 meters (36 pixels) toward the downtown area during the invasion by Typhoon Morakot. In addition, the results highlight all dangerous zones (scouring zones) for residents to prevent further potential damage.

Aug 1, 2013

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By M. Z. Naghadehi, F. F. Nasategay, J. Sattarvand, R. Battulwar, E. E. Gohari

After the recent increase in catastrophic failures of tailings dams such as the Burmadinho, Brazil failure in 2019, the mining industry has actively engaged in the stabilisation of tailings dams. Most of the tailings storage facility (TSF) guidelines suggest a laborious action that can be facilitated through imaging by unmanned aerial vehicles (UAVs). Although UAVs are not unknown to most mining operations, automated rill detection through aerial image processing is a new concept. This study utilises images from sites in the U.S. and employs semantic segmentation with a UNet architecture to detect location and size of these rills. The developed model can be used as a tool for monitoring surface erosion of TSFs.

Sep 1, 2021

By N Winkelmann

Underground coal heating is a significant hazard in some coal mines. The broad principles of how underground coal heatings occur is reasonably known, however the technique for locating the heatings in often inaccessible goaf has been proved to be difficult. Since 2002, CSIRO, with the support of the Australian Coal Association Research Program (ACARP) has been undertaking investigations to apply and develop innovative surface-based radon technique for locating the underground heatings in Australia. This paper presents the progress of the investigation.

Jan 1, 2005

By C. H. Lau, I. T. Ng

Uniaxial Compressive Strength (UCS) of rocks is an important mechanical parameter for many civil engineering and rock engineering applications such as tunnel excavation, slope stability and foundation design. Macau is one of the world's fastest growing and most densely populated cities, many large and important infrastructures have been being continuously built using pile foundations which are designed to be supported by granitic bedrock. In Macau, the UCS of the granitic bedrock is required almost for every project involving pile foundations and is always measured directly from UCS test in the laboratory. However, direct measurement of UCS requires high quality rock core sample which is not only time-consuming and expensive but also requires high level of operating skill. In view of this fact, estimation of UCS using some empirical correlations will be more practical and efficient because they are relatively fast and economical compared to the direct measurement from UCS test. In the past, some empirical correlations had been established and widely used for estimating UCS of rocks in common engineering practice. However, it has been well recognized that the rock properties are generally varied with sites or geological regions in other words an empirical correlation developed from one region or one country may not be applicable for other regions or countries. Due to the reason that the empirical correlations for predicting UCS for granite are scarce in practice, in this study an extensive experimental program has been performed and a large database containing data such as UCS, Point Load Index (Is50), Schmidt Rebound Hardness (RL), porosity (?), water absorption (S), specific gravity (Gs) and dry density (?d) has been developed. An attempt has been made for developing a new empirical correlation for estimating the UCS of Macau granite. Accordingly, a comprehensive statistical analysis for correlating UCS with Is50, RL, ?, S, Gs and ?d has been performed and a local empirical relationship based on the developed database is proposed for obtaining reliable estimation of UCS for the granite of Macau. Finally, the performance of the proposed correlation is accessed by using another independent testing database developed in this study. It indicates that Is50, RL, ? and S have strong correlation with UCS whereas Gs, ?d have poor correlation with UCS. This study not only proposed a proper predictive empirical correlation for UCS determination for Macau granite but also provides detailed statistical information which is beneficial to engineers for obtaining better characterization of Macau granite.

Jan 1, 2015

By P. M. Soupios

The study of soft soil (wastes above the rock bed) an issue of great importance in civil engineering, is usually addressed by drilling boreholes. This method is rather expensive and time-consuming and although the information obtained is usually accurate, on the other hand it is much localized. Recently published researches have demonstrated the ability of the combination of geophysical exploration methods to estimate the thickness of deposited wastes, which provides the layered structure of the study area and certain, method depended, mechanical parameters as well. By theory, the frequency of resonance of an upper layer is a function of its thickness and the average shear velocity in it. Furthermore, the application of H/V spectral ratios of micro-tremors is a fast, straight forward and cost effective methodology, yielding the determination of the main resonant frequency of the soil. Based on this framework, 20 microtremor measurements have been carried out in a Landfill in Heraklion-Crete. Some of these measurements were deliberately close to drilled sites, where the basement had been reached. Three electrical resistivity tomographies were also used, in order to define the landfill structure such as, thickness, determination of different wastes distribution in the study area and other parameters. In addition, estimation of predictive Vs using empirical relationship between shear velocity and penetration resistance (SPT?s) were also conducted. Knowing the thickness and the resonant frequency, we estimated the shear (Vs) velocity of the waste cover. The final Vs model was confirmed using the results from the Vs-SPT correlation. The combinative implementation of the above mentioned geophysical and geotechnical methods have successfully defined geometrical and geotechnical/geophysical characteristics of the area under investigation in a fast and cost effective way.

Jan 1, 2005

By R. V. Ramani

In 1970, of the 603 million tons of coal produced in the United States, 339 million tons, or 56%, were produced by under- ground mines. While the ratio of underground to surface production has been decreasing in the last few years, it is anticipated that a 60:40 ratio of underground to surface-mined coal will remain for some time. Underground coal operators are continuing to invest in new mines and are interested in increasing the efficiency of all their operations. One area for improvement is in mine planning and design, particularly in the area of selection of equipment for operation. Because of the availability of a wide variety of equipment, a fair degree of selectivity can be exercised in the choice of equipment for a particular job. However, such a choice must be made on the basis of technological facts and forecasts related to the mining operation. If the mining conditions can be reasonably predicted, along with a mining plan, it should be possible to insure the selection of the right equipment for the particular application. In order to increase the efficiency of underground coal operations, it is necessary to understand not only the operating system in detail, but the inter-relationships between system components and the operating environment. With such an understanding comes the application of simulation and other operations research techniques to plan and operate mining systems. Computer simulation studies have been successfully adapted to underground coal mining, and applications by Prelaz et al. (1965), and Manula and Sanford (1969) are some that are being used by the mining companies. However, a need still exists for better understanding of certain intra-system and system-environment interactions in order that computer simulation programs may be provided with better input data for more effective application. This paper deals with one aspect of the coal-winning system in need of better definition, namely, studying the performance of continuous miners.

Jan 1, 1973

By François Robert, Steve Green, Tyson Birkett, Dan Richardson

Abstract -Detailed sampling using a portable diamond drill, and interlaboratory comparison of selected samples have been combined with statistical studies of truncated populations to establish the gold content of several outcrops in the Val d'Or area. The outcrops chosen are non-mineralized. The background gold concentration in the rocks of the region is 5 ppb or Jess. Gold is distributed relatively homogeneously within the outcrops studied except for slightly increased concentrations within quartz-tourmaline veinlets. Three samples, of which 20 grams of powder are analyzed for each, can adequately determine the gold concentration of a structurally simple outcrop in the Val d'Or area.

Jan 1, 1992

By Tyson Birketi, Françoi Robert, Steve Green, Dan Richardson

Detailed sampling using a portable diamond drill, and inter laboratory comparison of selected samples have been combined with statistical studies of truncated populations to establish the gold content of several outcrops in the Val d'Or area. The outcrops chosen are non-mineralized. The background gold concentration in the rocks of the region is 5 ppb or less. Gold is distributed relatively homogeneously within the outcrops studied except for slightly increased concentrations within quartz-tourmaline veinlets. Three samples, of which 20 grams of powder are analyzed for each, can adequately determine the gold concentration of a structurally simple outcrop in the Val d'Or area.

Jan 1, 1992

By J. Wyn Prior

The seismic refraction technique is probably the most popular geophysical method of bedrock profiling in geotechnical site investigations but is somewhat restricted by the inherent assumptions in the method. This paper describes how Hales' method of profile interpretation is modified to overcome the assumptions of increasing velocity and layer thickness with depth when only first arrival data is available. A further expansion of Hales method enables presentation of refraction data in a form whereby bedrock features, such as changes in velocity, relief and dip in particular, are more readily recognized. Characteristic curves of the more common bedrock features are presented as an aid to bedrock feature recognition.

Jan 1, 1976

By J. Wyn Prior

The seismic refraction technique is probably the most popular geophysical method of bedrock profiling in geotechnical site investigations but is somewhat restricted by the inherent assumptions in the method. This paper describes how Hales' method of profile interpretation is modified to overcome the assumptions of increasing velocity and layer thickness with depth when only first arrival data is available. A further expansion of Hales' method enables presentation of refraction data in a form whereby bedrock features, such as changes in velocity, relief and dip in particular, are more readily recognized. Characteristic curves of the more common bedrock features are presented as an aid to bedrock feature recognition.

Jan 1, 1979