Search Documents

By Jamal Rostami, Alireza Salimi, Christian Moormann

"Rock mass classification systems are often applied in many empirical design practices in rock engineering, some contrasting with the original intent and applications of these classification systems, for example, estimation of TBM performance in various ground conditions. While accurate estimation of machine performance is significantly impacted by rock mass properties, parameters used in many of the existing classifications are more related to ground support design and not rock mass boreablity. The results of many investigations on this issue have shown a weak correlation between TBM rate of penetration and rock mass classification. This limitation can be overcome by fine tuning the rock mass classification input parameters to represent influence of rock mass properties on TBM performance as has been the objective of RME or QTBM. This paper will offer an overview of the impact of rock mass on TBM performance and introduces an empirical equation for predicting performance of rock TBMs based on rock mass classification. The results of the preliminary analysis of a new model has revealed that the use of the proposed system can offer a reasonable accuracy for estimation of TBM performance in various rock masses. 1. INTRODUCTION Hard rock tunnel boring has become more or less the standard method of tunneling for tunnels of various sizes with lengths over 1.5–2 km. Estimating the performance of TBM is a vital phase in tunnel design, and for the choice of the most appropriate excavation machine. During the past three decades, numerous TBM performance prediction models for evaluation of TBM rate of penetration and advance been proposed. In brief, all the TBM performance prediction models can be divided into two distinguished approaches, namely theoretical and empirical ones (Rostami et al., 1996). The most common and recent works on this topic are summarized in Table 1. Currently, two models including Colorado School of Mines or CSM (Rostami and Ozdemir, 1993; Rostami, 1997) and Norwegian University of Science and Technology or NTNU (Blindheim, 1979; Bruland, 1998) models are the most recognized TBM performance prediction and prognosis models in use around the world."

Jan 1, 2016

By R. W. Bartlett

High salinity geothermal brines typically contain up to several hundred parts per million of valuable heavy metals, and because of the large potential flow of geothermal brines from future power plants, metal production as a by-product could be significant A-planned 55-MW demonstration plant near Niland, California should generate enough spent brine to contain approximately $670,000 per year in gross metal values. Lawrence Livermore Laboratory estimates (1) a Salton Sea Geothermal potential of 1300 to 8700 MW, which would translate to possible yearly heavy metal values between $5,800,000 and .$l05,000,000. Since these estimates were made on a conservative basis, this geothermal reservoir is potentially a large ore deposit. The heavy metals in order of decreasing abundance in high salinity brines from the Salton Sea geothermal field are usually manganese, zinc, iron, lead, and silver. All but manganese and iron are valuable enough to be of commercial interest. Minor amounts of copper and arsenic are also present. Although heavy metal precipitates, particularly lead, have been found in scales within pipelines and obtained from steam flashing, most of the metals remain soluble during steam production; hence removal of the valuable metals from the spent brine before reinjection in ground reservoirs is indicated. Because the heavy metal concentrations are low, a very simple and inexpensive process is required. The heavy metal value in Niland brine is only ' about $1 per 1000 gallons; see Table 1. The brine composition shown in Table 1 was taken from one of the brine samples used in our study. Projected post-flash brine from a steam plant has somewhat higher Zn and Pb values, but the gross heavy metal value is still less than $2 per 1000 gallons.

Jan 1, 1980

By G. Bonifazi

Certain deposits of incoherent materials which are near the surface and exploitable by open-pit mining may be characterized in real time before they are mined through an analysis of ground-surface imagery. If the slice to be stripped is not overly thick, in fact, surface texture and color properties may be extrapolated to its entire thickness. Image analysis techniques to process ground surface images acquired in situ (or in the laboratory shortly after their acquisition) which yield pattern vectors representative of RGB color component distributions and HSB texture parameters have been developed. The techniques were applied to a mineral sandy ore deposit containing three different lithotypes. Geostatistical analyses showed that the data used to characterize the lithotypes were reliable. The correct recognition of the lithotypes was carried out using a multi-barycenter classification algorithm. Such in situ image-analysis procedures open the way to the proper selection of the ore to be mined, or the proper way for run of mine (r.o.m). processing, or the appropriate blend to be processed before or at the same time as the mining process itself is enacted.

Jan 1, 1999

By M. K. Boateng, K. Awuah-Offei

"Mining companies have started using quantitative tools, including computer models of community interaction, to gain intelligence on social risks surrounding their projects. Models of changes in community preferences regarding mining projects over time are useful for evaluating changes in project risk due to changes in the social license to operate. For example, agent-based models that use information diffusion models and social networks are useful for studying those changes due to information diffusion. However, such agent-based models are sensitive to many input parameters including the parameters of the diffusion model and the average degree of the social network. This work evaluates the sensitivity of such a model to diffusion and network model parameters (probability of imitation, probability of innovation, and average degree) using the first order and total sensitivity indices. The results show that the model is much more sensitive to the probability of imitation than the other two parameters. Thus, to reduce uncertainty surrounding the model’s predictions of community acceptance of mining, mines need to obtain accurate estimates of the probability of imitation. INTRODUCTION Mining companies have started using quantitative tools, including computer models of community interaction, to gain intelligence on social risks surrounding their projects. Models of changes in community preferences regarding mining projects over time are useful for evaluating changes in project risk due to changes in the social license to operate. For example, agent-based models that use information diffusion models and social networks are useful for studying those changes due to information diffusion. However, such agent-based models are sensitive to many input parameters including the parameters of the diffusion model and the average degree of the social network. This work evaluates the sensitivity of such a model to diffusion and network model parameters (probability of imitation, probability of innovation, and average degree) using the first order and total sensitivity indices. AGENT-BASED MODEL OF COMMUNITY ACCEPTANCE A few researchers have started using agent-based models to study mining systems (Fujiono 2011; Nakagawa et al. 2013; Bahr 2015; Boateng and Awuah-Offei 2017a, b). Nakagawa and co-workers used ABM to evaluate dynamics of a mining project’s stakeholder networks whereas Fujiono used ABM to study innovation diffusion in the mining industry. Our previous work has presented models and a framework for modeling information diffusion in a mining community and its impact on level of acceptance (a measure of SLO) of the mining project (Boateng and Awuah-Offei 2017a, b)."

Jan 1, 2018

By J. Ke

Traditional geostatistical methods have been used in ore reserve estimation for decades. Neural Networks (NNs) have provided an alternative approach to data analysis and ore reserve estimation. Unlike the traditional geostatistical methods, neural network uses a highly non-linear complex algorithm to do the estimation. Although Neural Networks have been demonstrated to be attractive alternatives as with every new techniques, there are questions which remain unanswered. This paper presents a comparative analysis with different types of metamodeling approaches -- Triangular, Kriging, Spline, and Neural Network. The neural-network is organized in a multiple-layers and Back-propagation model is used to handle the non-linearity and hidden slabs for smoothing the predicted results. With multiple dimensional and very noisy drill hole sample data, the ore grade is predicted and the overall performance is validated by the analysis of R-squared (R2), Root-Mean-Squared (RMS), and contours of ore grade spatial variability. The ore grade and tonnage of estimated outputs are also compared with various cut-off grades.

Jan 1, 2003

By Leslie G. McMillion

A field project to develop and demonstrate a method for alleviating problems of highly-mineralized ground water where they occur as isolated zones or pockets in fresh-water aquifers is being conducted in the Ogallala Aquifer of eastern New Mexico by the Robert S. Kerr Water Research Center. Removal of contaminated water is by a large-capacity well and the pumped poor-quality water is used locally for secondary recovery of oil, Benefits of the operation are threefold in that the aquifer is being reclaimed for future fresh water production, contaminated water is being used beneficially, and fresh water which otherwise would have been used for waterflooding is available for other purposes. Ground-water quality in the site has improved markedly after 21 months of operation. Water quality in 15 specially-drilled monitoring wells has returned to the original quality level of the aquifer, and chloride concen¬trations in the pumping well have dropped to half the maximum level recorded thus far. Project results are very favorable and provide guidelines for initiation of similar undertakings in localities where needed.

Jan 1, 1970

By Gary L. Simmons

Noranda's Grey Eagle Mine and Mill, located in the Siskiyou Mountains of Northern California, began shakedown operations in the late fall and early winter of 1982. This paper describes some of the unique features in mining, milling and water treatment operation at Grey Eagle. In addition, major start-up problems in the mill and water treatment plant are discussed along with measures taken to correct these problems.

Jan 1, 1984

By W. R. Bull

This paper examines water-only cyclone performance for the cleaning of fine coal, and the effects of changes in feed flow rate, feed pulp density, and vortex finder diameter. A model is presented for performance simulation which can be used to predict products obtained based on feed washability data.

Jan 1, 1987

By A. Röttger, W. Theisen, J. Küpferle, M. Alber

"Wear of TBM tools significantly affects tunneling advance rates. Wear-prediction models are based (amongst others) on the abrasivity of the present geology, which is determined via laboratory tests. To evaluate the results from such tests in context, this work considers the tribological system TBM tool from a materials technology perspective. In so doing, the microstructures of different application-oriented materials are presented and discussed in terms of their wear behavior and wear resistance. The significant influence of tool materials on the abrasivity of the geology and thus wear prediction models has already be identified. LCPC, Cerchar and nano-scratch experiments have been performed as confirmation. Material-dependent wear mechanisms and their correlation in terms of tunneling have shown that it is mandatory to consider the complete tribological system to estimate the wear of TBM tools. 1 INTRODUCTION Mechanized tunneling is vital to ensure necessary infrastructure development in megacities like Tokyo (Bay Tunnel), Istanbul (Eurasia Tunnel) and Mexico City (Tunnel Emisor Oriente). The use of Tunnel Boring Machines (TBMs) has been established for many years. In contrast to other methods such as boring and blasting or excavation using dredgers, tunneling with TBMs allows simultaneous excavation and removal of both the mineral and tunnel lining by tubbing segments or shotcrete. This makes tunneling more efficient, allowing for faster development of the tunnel in both hard rock and soil [1]. When budgeting such tunneling projects, precise planning and coordination in terms of tunneling technique choice (e.g. EPB or Slurry-shield), the relevant geology, and the associated penetration rates and tool wear are required. In particular, wear to TBM tools has a significant impact on tunneling progress. Due to wear, tools become dulled or lose their functionality because of brittle material behavior, thus reducing penetration rates and therefore tunneling efficiency [1]. As a result, additional tool changes are necessary, leading to higher overall costs due to down times and maintenance costs. Therefore, there is strong interest in a reliable and precise wear prediction model for TBMs. As already mentioned, the geology and associated wear of the tunneling tools define the maintenance times."

Jan 1, 2016

Adsorption of acrylamide based homo and copolymers on hematite was investigated as a function of phe nature of the polymer charge and functionality of the polymer. Effect of addition of sodium dodecylsulfonate and dodecylamine hydrochloride was also studied and was determined to result in an increase or decrease in the amount of polymer adsorbed depending on, the charge characteristics of the surfactant and the polymer, pH of the suspension, concentration of the various species and the order in which these species were added to the system. The surfactant adsorption under given conditions on the other hand, was found not to be affected by the presence of the polymer molecules. The data is analyzed to elucidate the mechanism of adsorption of polyacrylanide type polymers on hematite both with and without the surfactant species king present in the system.

Jan 1, 1982

By M. J. Virnig

A flowsheet for the recovery of nickel and cobalt from laterite ores has been developed which involves acid leaching followed by hydroxide precipitation of the metal values and then releaching of the hydroxide cake with ammonia. Investigations of the chemistry of extraction of nickel by LIX® 84-1 and a developmental reagent, XI-84-IT, along with the physical properties of the organic phases are described. Based on these investigations, suggestions with regard to design of a solvent extraction plant and operating conditions are made.

Jan 1, 1999

By Robert L. Randall

The mineral industries have a continuing need for market forecasting and analysis for a variety of purposes, among which are organization and control of the sales effort, financial and corporate planning, and evaluation of the anticipated revenue from investment in proposed projects. For anything beyond the simplest extrapolation, some kind of economic reasoning or analysis is called for, which may or may not be incorporated into a formal or quantitative model. The principles described here apply to most of the commercially significant minerals and metals. The examples are drawn largely from the copper market, as it is the one with which I have the most practical experience. Practical forecasting is the process of analysis and synthesis from three categories of knowledge: facts and statistics, theory, and practical knowledge and informed opinion. Although many attempts have been made to build forecasts on only one of these three pillars, none has been successful as an operating procedure because of the lack of balance. There are no facts about the future-only about the present and the past. Facts can illuminate the future, but the future can be described only in terms of probability or more or less likely states of affairs-not as a continuous extension of the past and present. Likewise, theory, although useful as an organizing discipline and for providing a methodology of analysis, is inadequate for the complexities of reality. This is especially so when there is feedback between plans and forecasts to produce a new outcome and when there are significant elements of unpredictable free will, such as presidential jawboning or foreign policy considerations. Such elements are difficult to accommodate in neat theories, although they must certainly be reflected in the forecasts. Pure opinion frequently suffers from both a lack of-disciplined reasoning and the presence of biases or self-interest. While the future is unknown, it tends to cast its shadow before it; hence, forecasting is the art and science of positioning oneself so that the shadow becomes visible to the forecaster.

Jan 1, 1979

By Haydn H. Murray

This paper presents the results of test work performed with a Pacific Electric Motors (PEM) high intensity magnetic separator (20 kilogauss) , a unit capable of separating weakly, as well as strongly, magnetic minerals in the particle size range of sands to clays. Tests were performed on some 40 industrial minerals. With some minerals excellent separations were attained and with others intermediate and poor separations were accomplished. This study is a preliminary survey and many of the intermediate and poor results can be improved as separation problems are worked out with additional test work. It is demonstrated that with a number of industrial minerals high intensity magnetic separation is a viable beneficiation technique that is economic ally feasible.

Jan 1, 1976

By Brandon Barnes, Michael Haggerty

"Around Minneapolis and Saint Paul, Minnesota, the local geology includes the St. Peter Sandstone, which is easily minable and has facilitated construction of interceptor tunnels for storm water and sanitary tunnels since the 1800s. The elevation of the geologic units allowed gravity-driven flows from the downtown areas all the way to the Mississippi River. Through many years of service, some of these tunnels have experienced degradation and require maintenance. Additionally, increased stormwater surface runoff can result in internal pressurization of the tunnels, accelerating degradation. Because structural failure or collapse of any of these interceptor tunnels would create a significant repair challenge, the city of Minneapolis has been inspecting and designating tunnels in its system for periodic review and repair. One of these, the St. Mary’s/Hiawatha tunnel, was rehabilitated using a grouting program. A hydrologic model was also used to improve understanding of pressurization events during some storms, leading to construction of a near-surface pressure dissipation chamber to provide increased hydraulic capacity. BACKGROUND The St. Mary’s/Hiawatha tunnel in Minneapolis has three segments; the first two were constructed in 1942 and the third was added in 1987 (Figure 1). Segment 1 is approximately 4,700 feet in length and outlets to the Mississippi River. Segment 2 intersects Segment 1 approximately 3,500 feet upstream of the river outlet and continues for approximately 2,500 feet in a southeasterly direction. The third and newest segment is approximately 500 feet long. There are four different cross sections of tunnel along the entire system.Originally, tunnel construction often consisted of mining the St. Peter sandstone with a pressurized water lance and constructing wood lagging support (Payne, 1967). An underdrain was generally installed below the invert during construction; this resulted in localized dewatering and provided groundwater control during construction. Non-reinforced concrete liner sections were cast in place. Often void space existed between the tunnel liner and the native sandstone bedrock. These voids, particularly in the crown, prevent direct contact between the liner and the bedrock."

Jan 1, 2016

By T. E. Mccandless

Detrital minerals of mantle origin have been found in the Green River Basin of Southwestern Wyoming (Figure 1). Pyrope, pyrope-almandine, and chrome-bearing clinopyroxene and orthopyroxene occur on the antmounds of Pogonomyrmex Occidentalis. These antmounds are a common sight throughout the western U.S., and were used by early paleontologists as fossil mammal collection sites. The mound is composed of two types of material; (1) soil excavated during the digging of the nest below the surface (maximum depth 3 meters) and (2) larger grains collected from the surface and placed on the mound, probably to prevent erosion. The selection of grains to armor the mound seems to be based largely on the mean diameter of the grain, with other factors such as weight, sphericity, roundness and composition in decreasing order of importance (Wheeler and Wheeler, 1963). The minerals of this study happen to fall within that mean diameter range. The garnets are found on the mounds as 3-6 mm diameter subrounded to subangular grains. The pyroxenes are also 3-6 mm in diameter and are most commonly subangular laths. The minerals themselves show evidence of abrasion, such as frosted surfaces and rounded edges. Orange peel texture is present on some of the grains, which suggests that kelyphitic rims were once present, but have been removed. Also, no similar minerals were found in sieved soil auger samples to depths of 2 to 6 meters taken near the antmounds. These observations imply a distal rather than proximal source for the minerals. Lamproitic rocks of upper mantle origin are found bordering the "Green River Basin. The best known are the Leucite Hills, a series of ultrapotassic volcanics found on the north flank of the Rock Springs Uplift (Carmichael, 1967). Minor occurrences of mica peridotite and ultrapotassic volcanics are also found on the western end of the Uinta Mountains in Utah (Best, et al, 1968). None of these rocks are known to contain minerals like those on the antmounds. The garnets are comprised of purple chrome pyrope, red chrome pyrope-almandine, and pink to orange low chrome pyrope/pyrope-almandine. Oxide statistics for these groups are summarized in Table 1. These three groups are distinct when their Cr203 values are plotted against magnesium number (Figure 2). The chrome pyropes are highest in Cr203 (1.28-2.66%) and have high, restricted Mg number values (0.781-0.826). The chrome pyrope almandines have similarly high Cr203 (1.29-2.62%) but a lower Mg number range. The low chrome pyrope/pyrope-almandines have the lowest Cr203 content (0.09-0.73) and the widest Mg number range (0.534-0.836). Using the classification scheme of Dawson and Stephens (1975) the chrome pyropes are most similar to garnets derived from kimberlite and from garnet lherzolite, websterite, and harzburgite xenoliths in kimberlite. The chrome pyrope-almandines and the low chrome pyrope/ pyrope almandines are similar to garnets derived from eclogite nodules (Figure 3).

Jan 1, 1984

By S. Goodfellow, J. C. Ordóñez-Calderón, K. Esmaeili, N. Houshmand

A good understanding of the hardness of ore being handled and processed in a mining operation can significantly improve operational efficiencies by providing valuable data to support decision-making through the mining value chain (drilling, blasting, comminution). This study presents the results from the application of Machine Learning (ML) to predict rock hardness using various geophysical and geochemical features. Core samples from a mine site were logged using a multi-sensor core logging system. Measurements including ultrasonic p-wave and s-wave velocity, elemental concentration via portable XRF, and Leeb Hardness, were measured every 2 cm along the length of the core. The ML model was set up to predict the Leeb Hardness using the elemental concentrations and ultrasonic velocities as predictors. The Leeb Hardness values were grouped into three bins and used as a classification target for the ML models. Various ML models, including linear regression, support vector machines, decision tree, XGBoost, Random Forest, K-Nearest Neighbors, and Naïve Bayes were tested. The model performance demonstrated that the Random Forest and XGBoost models produced the highest accuracy of 74-91%. Random forest and XGBoost were then selected to perform regression models to estimate a Leeb hardness value rather than a hardness class. These models were able to estimate the Leeb hardness value by 4.57-4.87 % error.

Mar 2, 2022

By H. Kiyama

In order to further elucidate the mechanisms involved in autogenous grinding, the fracture of rock specimens in free-fall impact was studied using the theory of elasticity. Stress distributions in rock specimens under various conditions of impact were analyzed and the conditions for failure were examined in relation to the compressive and tensile strength of rock. The energy equation derived for autogenous grinding coincides basically with Lewis' generalized formula or Oka and Majima's formula, and it is sufficiently general to incorporate all of the three older theories, viz; those of Rittinger, Bond and Kick.

Jan 1, 1972

By K. C. Kane, D. L. Meredith, B. E. Davis, D. A. Stanley, O&apos

Computer control of the minerals beneficiation process is limited by a lack of adequate sensors to provide information on the current state of the process. Recent reduction in the cost of image acquisition and powerful inexpensive computers make use of computer vision as sensory input in process control a possibility. In the phosphate industry, the amount of apatite in phosphate tailings is estimated by inspection. For machine vision, a simple 256 x 512 color image of the tailings was captured via an inexpensive color video camera on an IBM PC. Initially, the image is converted to gray scale and displayed on an EGA color monitor. A program was written which identifies the different constituents of the sample by analyzing the gray scale levels for the digitized picture. In other instances the minerals are identified by their relative color intensities. The amount of each constituent is determined with good accuracy from the area it occupies on the image.

Jan 1, 1990

By R. Hogg, S. Chander

An overview of various physical and interfacial characterization methods for use in mineral processing is presented in this paper. The availability of a large number of characterization techniques and commercial instruments requires that the reliability and limitation of each be carefully examined. The choice of a method may depend upon the manner in which the information is to be used, for example, in development of new processes, plant and process design, plant control, problem solving, etc.

Jan 1, 1987

By Daniel R. Walton

This paper covers several points of interest to mine engineers and planners involved in evaluating or conducting geostatistical coal reserve estimates. In particular, the ability to optimize borehole drilling locations and minimize drilling costs is addressed. Also discussed is the concept of confidence intervals for estimated coal characteristics obtained through geostatistical estimates and their importance in decision-making for mine planners. Finally, a discussion is presented on how geostatistics enables identification of invalid data points and actually forces strict attention to data editing and proper geologic interpretation.

Jan 1, 1982