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By J T. Sharp, M A. Styler, D McGowan, P W. Mayne

Static liquefaction is a geotechnical hazard in mine tailings facilities. Soils that are contractive in shear are susceptible to static liquefaction. Tailings facilities are dynamic structures, typically growing in height each year. Dilative tailings may become contractive under increased effective stress. In this paper we show that Cone Penetration Test (CPT) data can be used to estimate the future state of in-place tailings under changes in effective stress. Susceptibility to static liquefaction is typically evaluated with the CPT by using a clean-sand equivalent normalized cone tip resistance (Qtn,cs) or by estimating the state parameter (?). An alternative approach is to evaluate the soil-state using the yield-stress-ratio (YSR = ?’y/?’v0). If the YSR equals one it is on the normal consolidation line and the soil-state is contractive. YSR values greater than three are typically dense of the critical state line (CSL) and the soil-state is dilative. In this paper we review how to calculate Qtn,cs, ?, and ?’y; and how the YSR can be used to screen for contractive soil behaviour. Unlike Qtn,cs and ?, it is very simple to estimate how the YSR will change due to an increase in overburden stress. This YSR approach was evaluated at three locations that saw increases in overburden of 10 m, 20 m, and 25 m. We show that the ?’y calculations are consistent and the increase in effective stress moves the soil state towards looser soil states. CITATION:Styler, M A, Mayne, P W, McGowan, D and Sharp, J T, 2018. Predicting changes in static liquefaction susceptibility using cone penetration test results, in Proceedings Mine Waste and Tailings Stewardship Conference 2018, pp 317–332 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 23, 2018

By J. N. Van der Merwe

The data base of failed coal pillars in South Africa was analysed with regard to the time of failure in an effort to develop a method to predict how long after their formation coal pillars will fail. It was found that meaningful results could only be obtained by splitting the data base up into groups that displayed similar behaviour. It was postulated, based on observation and experience, that coal pillars fail by a process of progressive weakening progressing into the pillar from the edges. Minimum pillar dimensions to ensure failure were calculated?these were the dimensions that corresponded to a minimum ?real? factor of safety. From the scaling distance required to reach the minimum safety factor, rates of scaling for the failed pillars were calculated based on the observed real lives of the pillars. It was found that the rates of scaling were unique for different mining areas and that they correlated directly with mining height and inversely with time. Using the derived scaling rates, the predicted pillar lives were back calculated for the pillars in the data base of failed pillars. In two of the three groups, the predicted lives correlated well with the observed lives on a one-to-one comparison. In all cases, the predicted lives were in the same time range as the observed lives. Overall, the frequency of predicted lives closely replicated the observed frequency of observed lives of the pillars in the data base of failed pillars. The method was successful in distinguishing between the data base of failed and a representative sample of intact pillars. While the predictions matched the observed lives of failed pillars, the predictions of expected lives for intact (hitherto unfailed) pillars were orders of magnitude greater. It is now possible to estimate the frequencies of future pillar failures for the purposes of mine closure and undermining of surface structures within broad bands.

Jan 1, 2003

By A. Whillier

Methods are given for estimating heat flows into mining excavations of various types, with an example to illustrate how the refrigeration requirements are then determined after allowing for the cooling effects of the ventilation air.

Jan 1, 1981

By Ronald B. DeDiemar

It is generally held that cone crusher application technology is strictly an art and thus subject to the vagaries of emphirical and/or trial and error judgments. While this is basically true, certain factors have been identified which, when properly defined, can significantly reduce the element of chance. This paper will bring out these factors as well as pointing out other technologies available to predict and/or analyze cone crusher performance.

Jan 1, 1977

By Richard R. Parizek, E. Scott Blair

Numerical modeling of ground water flow systems can be used to help analyze many practical problems encountered in the mining industry. Numerical models can be used to predict ground-water seepage rates into surface mines, shafts, and other large excavations; to predict water-level changes under adjacent properties; and to predict the effectiveness of various deep-well dewatering schemes. As with any model, the results from a numerical model are limited by the quality and quantity of data, and by the restrictions of any simplifying assumptions. A case study is presented that shows how a numerical model was used for engineering purposes to help analyze the hydrologic impact of a proposed open-pit mine by Predicting changes in the dewatering rate caused by the lateral growth and deepening of the mine and by predicting the effectiveness of various deep-well dewatering schemes.

Jan 1, 1982

By D. Goodings, W. L. Fourney, Bonenberger, R., Uli Leiste

The Dynamics Effects Laboratory at the University of Maryland conducted a series of very small scale tests to measure the impulse delivered to a plate by the detonation of an explosive charge which was buried in saturated sand. These tests were conducted to support a full scale tests series being supported by the Navy (NSWC Indian Head Division) to learn more about loads applied to structures by explosive detonation. For each of the tests being predicted, a series of three tests were conducted at Maryland, one with a 0.203 gm charge, one with a .609 gm charge, and one with a 3.3 gm charge. A high speed digital camera (500 frames per second) was used to record the displacement of the plate as a function of time. From this the initial velocity of the plate was determined and then the impulse delivered to the plate by the explosive. A best fit line through the data was determined for the three model tests conducted and this equation was used to extrapolate the predicted impulse for the full scale tests.

Jan 1, 2005

By S L. Barbour

Measurement of the net percolation from the base of a cover system into the underlying waste material is a key component of a cover system monitoring program. The units of measure (ie a percentage of precipitation or rainfall) are simple to understand for all stakeholders, which increases the importance of obtaining representative net percolation values. In general, lysimeters are used to measure net percolation across the cover material-waste material interface; however, the design of lysimeters for cover system monitoring programs in the mining industry have typically not considered fundamental aspects of lysimeter design. Lysimeter design is typically thought of as being conceptually simple, when in reality the design, installation, and operation of lysimeters is often counter-intuitive, due to the complexities of flow through unsaturated soil systems. This paper puts forward a methodology for lysimeter design while also presenting the fundamental design variables that should be considered. Lysimeter design for differing climates, cover materials, and waste materials is discussed. Finally, the performance of lysimeter designs previously installed in the field at sites in Australia, Canada, and the United States are subjected to numerical modelling to determine whether net percolation is being measured properly.

Jan 1, 2003

By J E. Everett

An essential requirement of product quality control in the mining industry is to be able to reliably predict key quality properties of finished product from the data available before the extraction of the ore. From a production viewpoint, the unit of data collection is generally the input and output data set for each shift of crusher production, but could be any period where mine precrusher data can be reliably matched with product data.This paper demonstrates that linear regression models can be used to predict crush grades from blast grades, even where the crush material is blended from multiple sources or pits for each of which differing regression models might apply. The advantage of using increasingly complex regressions models to match the available data to give increasingly more powerful models is examined. The best model for any application will be a balance between required predictability, available data and the business’ tolerance for complex models.The regression modelling approach has several advantages over the more classic method of run-of-mine (ROM) crusher trials, which will be discussed.The models can use any predictor variable such as grade, geotype and in situ density provided the preextraction data set can be reliably matched with post-crusher data and is significant as a predictor. The models have been used extensively in the generation of the daily crusher plan with the aim of maintaining finished product grade. This approach has also been used associated with exploration drilling and long-term planning.It is acknowledged that there are inherent problems in fitting lump and fines grade to a linear model. However, these problems are minor when they are used for interpolation within the window spanned by the shift blend records used to produce the model. This paper discusses some of the issues limiting linear regression models in this application, and suggests methods enabling consistent models to be formulated

Sep 5, 2011

Predicting Flotation Response from Liberation Information

Sep 13, 2010

By James G. Ulinski, Sebastian Lobo-Guerrero, Vishal B. Patel

"Recently modified design equations used in the transportation industry to calculate side friction and end bearing capacity for drilled shafts are now providing more realistic estimations of capacities than did previous methods. Using multiple case studies and test results from various projects, a more realistic design approach was formulated by the Federal Highway Administration (FHWA), which resulted in greater values of ultimate capacity for side friction and end bearing and in a more efficient design overall.In 2010, the FHWA published GEC-10 – Drilled Shafts: Construction Procedures and LRFD Design Methods, which illustrates a different method of calculating side friction and end bearing resistance and results in greater values for design. In 2014, the Association of State Highway and Transportation Officials (AASHTO) adopted the method put forth by FHWA, which was included in its LRFD Bridge Design th Specifications, 7 Edition. The Pennsylvania Department of Transportation (PennDOT) recently adopted and incorporated the similar methodology as AASHTO for calculating side friction and end bearing for drilled shafts in rock, and these changes are reflected in the 2015 edition of the PennDOT Design Manual, Part 4 (DM-4). This article discusses the past and current design methodology along with a project case study with results from Osterberg Cell (O-cell) load testing, which presents a comparison between the design resistances of ultimate side friction and end bearing and the measured capacities at failure.The Old and the NewEditions of the AASHTO LRFD Bridge Design Manual from 2012 and earlier estimated ultimate side resistance, qs, in rock using the following equation (modified from Horvath and Kenney, 1979):qs=0.65aEpa(qu/pa)0.5 < 7.8pa(f ’c/pa)0.5 where: qu is the uniaxial compressive strength of the rock in ksf; pa is the atmospheric pressure in ksf; aE is the reduction factor to account for jointing in rock; and f ’c is the compressive strength of the concrete in ksi. For intact rock, previous versions of the AASHTO manual required that the ultimate end bearing resistance, qp, was calculated using the following equation: qp=2.5qu."

Jan 1, 2017

By F. Vincent, A. Boulet, M. Noaparast, F. Woodcock, A. R. Laplante

A novel methodology to estimate gold recovery by gravity is presented. It makes use of a population balance model which represents gold liberation, breakage and classification behaviour and applies pre-concentration and recovery data to gravity recoverable gold (GRG) to predict overall recovery. The methodology is designed for gravity circuits located in the circulating load of secondary grinding mills. Gold liberation is estimated by processing a sample of representative ore with a laboratory Knelson Concentrator (LKC) in three successive steps, each at a finer grind than the previous one. Breakage behaviour is represented by a matrix H, which redistributes GRG in the feed of the secondary mill in the various size classes of its discharge. Provision is also made to account for gold overgrinding, which decreases the overall amount of GRG. Classification, pre-concentration and recovery data are estimated from plant performance, and are represented by the diagonal matrices C, P and R. The methodology is demonstrated with case studies of greenfield, retrofit and optimization applications.

Jan 1, 1995

By A. R. Laplante

A novel methodology to estimate gold recovery by gravity is presented. The methodology makes use of a population balance model which represents gold liberation, breakage and classification behaviour and applies pre-concentration and recovery performance curves to gravity-recoverable gold to predict overall recovery. Derivation of the necessary parameters is explained and demonstrated using data from an actual gravity circuit and one projected application. The methodology makes it possible to estimate the performance of circuits with large gold circulating loads and relatively low unit recoveries (e.g. jigs), or with high recoveries on a bleed of the circulating load (e.g. Knelson concentrators).

Jan 1, 1994

By M. Noaparast, F. Woodcock, A. R. Laplante

A novel methodology for estimating gold recoveries in gravity-separation circuits is presented. The methodology makes use of a population-balance model. The model represents gold liberation, breakage and classification behavior and applies preconcentration and recovery performance curves to gravity-recoverable gold. The derivation of the necessary parameters is explained and demonstrated using data from an actual gravity circuit and from a projected application. The methodology makes it possible to estimate the performance of a gravity circuit having a large gold circulating load and a relatively-low unit recovery (e.g., a jig) or having a high recovery on a bleed of the circulating load (e.g., a Knelson Concentrator).

Jan 1, 1996

By Wojciech Klecan, John H. Raymer

Baseline quantities of difficult ground and support types were estimated for the Chattahoochee Tunnel using the Rock Mass Rating system. RMR classifies the ground into five categories, ranging from “very good” to “very poor,” based on five main parameters: intact rock strength, RQD, joint spacing, joint condition, and groundwater inflow. For the Chattahoochee Tunnel, these parameters were independently measured in the cores and shown graphically on the boring logs. A 55 matrix was calculated to obtain the statistical distribution of RMR for the project. Three baseline ground types were defined based on the RMR. Geologic mapping inside the tunnel during construction has verified the accuracy of this method.

Jan 1, 2003

By E. Azrag, A. MacDonald

A hydrogeologic investigation was conducted to predict inflow to underground mine workings and mining-induced hydrologic impacts for a proposed underground mine beneath a lake in northern Canada. Flow and shut-in tests were conducted to determine hydraulic conductivity values and to estimate the hydraulic head. A conceptual hydrogeologic model was developed and incorporated into a numerical ground-water flow model (utilizing MINEDW, a three-dimensional, finite-element code with special attributes designed for mine dewatering). The mining sequence was represented in detail(e.g., driving ramps and drifts, extracting panels, and backfilling mined areas). Due to limited field data, a quantitative assessment of uncertainty was implemented to estimate limits of possible inflows.

Jan 1, 2003

By John H. Raymer

The accuracy of inflow estimates depends largely on how well permeability is characterized. Permeability is best evaluated as a statistical distribution. For the Chattahoochee Tunnel, this distribution was obtained with a large number of packer tests performed in 50 boreholes along the alignment. The distribution of packer-test data may not accurately reflect permeability, however, due to the limits of the test method and the luck of the field investigation. These discrepancies may be overcome by using log-normal plots of the data to develop a permeability model that will be use din lieu of the data to calculate inflow.

Jan 1, 2001

By Nn Li

Energy consumption in commercial buildings has been increasing rapidly in the past decade. The knowledge of future energy consumption can bring significant value to commercial building energy management. For example, prediction of energy consumption decomposition helps analyze the energy consumption patterns and efficiencies as well as waste, and identify the prime targets for energy conservation. Moreover, prediction of temporal energy consumption enables building managers to plan out the energy usage over time, shift energy usage to off-peak periods, and make more effective energy purchase plans. This paper proposes a novel model for predicting heating, ventilation and air conditioning (HVAC) energy consumption in commercial buildings. The model simulates energy behaviors of HVAC systems in commercial buildings, and interacts with a multiagent systems (MAS) based framework for energy consumption prediction. Prediction is done on a daily, weekly and monthly basis. Ground truth energy consumption data is collected from a test bed office building over 267 consecutive days, and is compared to predicted energy consumption for the same period. Results show that the prediction can match 92.6 to 98.2% of total HVAC energy consumption with coefficient of variation of the root mean square error (CV-RMSE) values of 7.8 to 22.2%. Ventilation energy consumption can be predicted at high accuracies (over 99%) and low variations (CV-RMSE values of 3.1 to 16.3%), while cooling energy consumption accounts for majority of inaccuracies and variations in total energy consumption prediction.

Aug 1, 2013

By Y. C. Kim

Three rock fracture parameters define three points along empirical cumulative size (of rock fragments) distribution curves at Inspiration copper mine. These parameters are: rock quality designation (RQD), longest piece of intact rock and % of +1 inch. The RQD and the longest piece are actually measured on drill hole cores whereas % of +1 inch is visually estimated on the same cores. These size distribution curves are then utilized in a variety of engineering applications such as; slope instability analysis, blast design, copper recovery prediction from heap leaching, etc. The three rock fracture parameters for two dominant rock types (porphyry and schist) in the pit had to be estimated separately due to different rock fracture characteristics.&apos; Both ordinary kriging (OK) with measured hard data only and soft kriging (SFTK) with hard and soft data were used to estimate each parameter. The cross validation of 100 measured sample values served as the-basis for evaluating the potential benefits of SFTK over OK. Use of subjective information during SFTK required obtaining (prior) probability distributions for all three rock fracture parameters. These distributions were obtained from the typical rock fracture parameters observed in drill hole cores falling inside the geologically interpreted structural domains with varying degrees. of fracture intensity and also through direct mapping along the exposed bench faces. Two different types of soft information were developed for this study; namely, Type "A" and Type "K". The former is based on sample distribution of fracture parameters whereas the latter is based on two step estimation designed to narrow the range of variation observed in data Type "A". The results of the cross validation were analyzed using a linear regression of actual values versus estimated values. The results confirm an improvement on the estimates made by SFTK with hard and. both types of soft data over those produced by OK with hard data only.

Jan 1, 1989

By İsmail İnce

The purpose of this study is to investigate the index-mechanical properties of igneous rocks by using the electrical resistivity method. Electrical resistivity, index (P-wave velocity, dry density, and porosity), and uniaxial compressive strength values of 48 different igneous rock samples were measured in the laboratory. Simple regression analysis was performed between index-mechanical properties and electrical resistivity values. Strong exponential and logarithmic correlations were found between electrical resistivity and the index-mechanical properties of the igneous rock samples.

Jan 21, 2022

By J E. Everett, D Linden, P Maney

In response to the implementation of a new schedule for iron ore fines in the International Maritime OrganizationÆs (IMO) International Maritime Solid Bulk Cargoes (IMSBC) Code, improved measures for the management of moisture have been developed. In particular, prediction of cargo moisture allows management of iron ore fines within the supply?chain to facilitate the safe?shipping of iron ore fines.An ARIMA model, augmented to allow for shipment tonnage, has been developed to predict the moisture level from previous shipments of the same product. The model explains about 60 per cent of the moisture variance. It was found that inclusion of other available information, such as ore composition, train/rake assays and recent rainfall at port and mine, did not add to the predictive power of the model.CITATION:Everett, J E, Linden, D and Maney, P, 2013. Predicting iron ore fines shipment moisture, in Proceedings Iron Ore 2013 , pp 17-26 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 12, 2013