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By K. Aoki, Y. Mito, S. Shirasagi

The authors developed the TBM Excavation Control System (the TBM Navigator), in order to realize the advanced observational construction. During the excavation using this system, the rock strength value is immediately calculated from the TBM driving data as an index of rock properties, and the drill energy coefficient is also calculated from the drill logging data that is carried out using the probe hole ahead of the tunnel face. In this study, a new, geostatistical simulation-based method is proposed for the automatic prediction of the rock properties ahead of the tunnel face with good precision, using both the drill logging data and the TBM driving data. The applicability of this method is validated through the prediction at the actual tunnel excavation that passes through the faults. Les auteurs ont mis au point un Système de Contrôle de forage avec la machine à pleine section (Navigateur de la machine à pleine section), en vue de réaliser un système de surveillance plus efficace. Avec ce système, la résistance de la roche est immédiatement calculée, au cours du forage, à partir des données de conduite de la machine, comme indice des propriétés de la roche, et le coefficient d'énergie de la foreuse est également calculé à partir des données de log de forage collectées dans un trou de sonde foré dans le front de taille. Dans cette étude, on propose une nouvelle méthode basée sur la simulation géostatistique qui permet de prévoir d’une manière automatique, des propriétés de roches se trouvant derrière le front de taille avec une précision satisfaisante, à l’aide des données de log de forage et celles de conduite de la machine à pleine section. Cette méthode s’est avérée suffisamment précise au cours du forage d’un tunnel réel qui traversait une zone de failles. Die Autoren entwickelten das TBM Ausschachtungssteuerungssystem (den TBM Navigator), um noch besser überwachte Bauarbeiten zu ermöglichen. Unter Einsatz dieses Systems wird die Gesteinsfestigkeit während der Ausschachtungsarbeiten unmittelbar aus den TBM Antriebsdaten als ein Index für die Gesteinseigenschaften berechnet. Gleichzeitig wird auch der Bohrenergiekoeffizient aus den Bohrlogdaten berechnet, die an Hand der Probebohrung am Stirnende des Tunnels erhalten wurden. In der vorliegenden Studie wurde ein neuartiges, auf geostatistischen Methoden basierendes Verfahren für die automatische und angemessen genaue Vorhersage der Gesteinseigenschaften am Stirnende des Tunnels vorgeschlagen, für das sowohl die Bohrlogdaten als auch die TBM Antriebsdaten verwendet werden. Die Anwendbarkeit dieser Methode wird durch die Vorhersage bei einer tatsächlichen, durch Verwerfungen verlaufenden Tunnelausschachtung bewiesen.

Jan 1, 2003

By A. Karadogan, G. Tuncer, A. Kahriman, S. Gorgun

This paper presents the results of ground vibration measurements induced by blasting operations at five different sites located close to the residential areas. Within the scope of this study, ground vibration components were measured for all blast events over a long period of time in order to predict peak particle velocity and determine the slope of the attenuation curve for five sites. During the study, while the parameters of scaled distance were being recorded carefully, suitable monitors for all blast events of five blasting sites measured the ground vibration components. At the end of evaluation of the data pairs, an empirical relation, which gives an average line at 95% confidence level, and upper bound 95% prediction line with a good correlation coefficient was established and suggested for each site

Jan 1, 2003

By K. Oraee

Rate of penetration of Tunnel Boring Machines (TBM) has a significant role in the planning, measurement of productivity and performance of any tunneling project. In this paper, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) in prediction of TBM penetration rate is evaluated. For this purpose, a database including Rock Quality Designation (RQD), Uni-axial Compressive Strength (UCS) of the rock, the Distance between Planes of Weakness (DPW) in the rock mass, and empirical data regarding rate of penetration of TBM from several tunneling projects are collected. The Rate of Penetration is then estimated by using ANFIS. These results are then compared with measured TBM penetration rates (actual data). It is concluded that ANFIS can be applied successfully for such purpose and result in high accuracy for prediction for the rate of penetration of TBM. The method provided in this paper can assist the mining engineer to estimate the performance of tunneling accurately.

Jan 1, 2012

Prediction of the performance of explosives In bench mining by C. M. LOWNDS, B.Se. Hons (Rhodes), Ph.D (Cape) (Visitor) Some of the problems encountered in the calculation of the relative weight strength of explosives are discussed, and a realistic model of the behaviour of explosion products in a borehole is proposed. The heat flow from condensed to gaseous products is calculated as a function of time, and the relationship between the pressure and the volume of the product gases is found by a consideration of the compression of the rock between radial cracks. Work done on the burden is assumed to cease when the cracks first appear at the face. Reasonable values of burden and crack velocities are obtained from the model. Calculations of the relative weight strengths of aluminized mixtures of ammonium nitrate and fuel oil show that the increased density resulting from the addition of aluminium is the main advantage to be gained.

Jan 2, 1975

By M. Fooladi Mahani, M. R. Izadpanah

The knowledge of the thermal shock resistance of refractory materials is of outmost importance due to their wide range of applications in various industries, namely; ceramics, oil refinery, thermal insulation, nuclear power, chemical and petrochemical industries. Thermal shock resistance is measured in terms of the number of cycles that a refractory material can withstand when subjected to sudden temperature changes. This property is measured experimentally by heating a sample of the material and cooling it in a known environment then the number of cycles it withstands this treatment without spalling is a measure of its thermal shock resistance. Although this method of experimentation has long been the practice, but it is both expensive and time consuming. Various studies have been carried out to predict this vital property, however, the rang of applications are limited. The present study employs a test rig by which temperature distributions in magnesite samples are accurately measured. This information plus other results obtained from relevant tests on related properties are used to develop a model which predicts the number of quench cycles withstand by different materials when subjected to sudden temperature changes. The comparison of the theoretical values using the solution of the presented model with experimental data for different materials having different thermal resistance shows a closed agreement.

Jan 1, 2004

By R. M. Morris, G. A. Matthesius, M. J. Desai

Slow pyrolysis experiments were caried out on samples of coal from north em Natal having a volatile mater content ranging between 10 and 25 per cent by mass and a constant particle-size distribution. The tests were conducted at atmospheric pressure in a helium atmosphere, and ata heating rate of 10 KImin and a final temperature of 1220 K. The pyrolysis products were taken as coke and volatile mater (tar and eight other species), and tMir respective yields were measured. The experimental results were used in the modification of an existing mathematical model and in the derivation of new corelations for some of the parameters of the model, so that the volatile products of a coal can be predicted from ultimate and proximate analyses of the coal. The pyrolysis tests showed good agreement between the model predictions and the experimental results.

Jan 1, 1987

By A. McLean, W. Q. Chen, W. Yan, M. Barati, Y. D. Yang

In order to maximally remove the harmful impurities phosphorus and reduce the loss of valuable elements from Si-based alloy for production of solar-grade silicon, thermodynamic properties of the Si-based alloy were studied. In this work a new model, the Molecular Interaction Volume Model (MIVM) derived from statistical thermodynamics, was successfully used in the Si-based and Si-Fe-based alloy. The calculation started from binary Si-Fe, Si-P and Fe-P systems, then the thermodynamic parameters of ternary systems could be derived based sub-binary systems. Using the activity coefficients of the elements in the Si-based alloys and the saturated vapor pressure of the pure substance of the components, mass fraction of P during vapor-liquid equilibrium can be calculated. The calculated thermodynamic parameters were compared with experimental data available in different publications, and it is found that the thermodynamic parameters calculated using MIVM model are in good agreement with the measured results. The calculated result shows that the mass fraction of phosphorus during vapor-liquid equilibrium of Si-Fe-P melt increases with the increasing phosphorus content and decreasing temperature. This is an important direction for experimental practice in vacuum or low-pressure EML refining of ferrosilicon for potential production of solar-grade silicon without significant vaporization loss of valuable element.

Jan 1, 2015

By Xiaodong Yu, Jinxia Zhang, Fusheng Niu, Hongmei Zhang

The three-dimensional (3D) fractal dimension is an important parameter to analyze the 3D structure and flocculation effect of the hematite flocs. In this work, the 3D fractal dimension of hematite flocs was predicted by establishing the particle swarm optimization (PSO) algorithm optimized with the back propagation (BP) neural network (PSO-BP). The proposed model considers four factors, namely, the flocculant quantity, flocculation time, stirring speed, and temperature, as the input parameters. We normalize the input data during the preprocessing stage. The BP neural network was optimized by using the PSO algorithm for realizing the 3D fractal dimension. The prediction accuracy and effectiveness of the model were evaluated. The experimental results showed that the predictions performed by the proposed PSO-BP neural network were better than that of BP neural network. In addition, the root mean square error (RMSE), mean squared relative error (MSRE), mean absolute error (MAE), and mean absolute relative error (MARE) of the proposed model are lower, compared with the errors of the BP network. Similarly, the measurement coefficient R2 of the proposed model is higher, compared with the BP network. The maximum absolute error of the model is 0.0772, the maximum relative error is 0.02405, and the regression coefficient r is 0.98592. These results showed that the proposed model has a good performance and high prediction accuracy. When verifying the practicability and the effectiveness of the proposed PSO-BP model, the prediction results of 10 groups of hematite flocculation experimental data under different conditions showed that the prediction value of the proposed PSO-BP model was closer to the ground truth as compared to the BP model. Therefore, the proposed model is suitable for predicting the 3D fractal dimension of hematite flocculation.

Oct 3, 2022

By Christian Ludwig, Virginie Silberstein, Rizlan Bernier-Latmani, Simona Regenspurg

"Residues from waste incineration (bottom ashes) form large amounts of heavy metal-rich waste. Theoretically, heating and the addition of chloride to the ashes could remove these metals by formation of volatile metal chlorides. The remaining heavy metal-poor ashes could be used, for example, as cement additives. In the proposed process of our study we used bypass dust from the cement industry as chloride additives to the bottom ashes. We aim to determine experimentally the optimal conditions to remove heavy metals from ashes and to simulate this process by thermo- chemical modeling. In our experiment we investigate heavy metal flows by heating of differently composed mixtures of bottoms ash and bypass dust in dependence of different furnace temperatures (500-1200 °C). Furthermore, we investigate the reactivity (leaching characteristic) of the resulting product in order to predict if secondary residues can be landfilled in agreement to Swiss regulations for inert materials.IntroductionThe incineration of garbage is generally considered as the most environmentally friendly method for the reduction of municipal solid waste. This is because, compared to traditional storage of waste on landfills, incineration produces less greenhouse gases and destroys toxic organic compounds. The released exothermic energy can be recuperated and the residues from the combustion chamber (bottom ash) are strongly reduced in volume. However, they still form about 600 kt of waste per year in Switzerland, which needs to be landfilled. However, these residues could be potentially used as construction materials after mechanically recovering ferrous and non-ferrous metals. However, the resulting ashes (discharged dry or wet) still contain increased amount of heavy metals (exceeding state regulation) requiring them to be finally deposed on a hazardous waste site. A thermal treatment of these ashes could enable both, to separate and recuperate the remaining heavy metals and an inorganic heavy-metal poor material. The evaporation of metals depends on temperature and can be lowered by addition of chlorides, which would lower the boiling point of most metals by formation of metal chlorides (table 1)."

Jan 1, 2008

By Christian Ludwig, Virginie Silberstein, Rizlan Bernier-Latmani, Simona Regenspurg

"Residues from waste incineration (bottom ashes) form large amounts of heavy metal-rich waste. Theoretically, heating and the addition of chloride to the ashes could remove these metals by formation of volatile metal chlorides. The remaining heavy metal-poor ashes could be used, for example, as cement additives. In the proposed process of our study we used bypass dust from the cement industry as chloride additives to the bottom ashes. We aim to determine experimentally the optimal conditions to remove heavy metals from ashes and to simulate this process by thermo- chemical modeling. In our experiment we investigate heavy metal flows by heating of differently composed mixtures of bottoms ash and bypass dust in dependence of different furnace temperatures (500-1200 °C). Furthermore, we investigate the reactivity (leaching characteristic) of the resulting product in order to predict if secondary residues can be landfilled in agreement to Swiss regulations for inert materials.IntroductionThe incineration of garbage is generally considered as the most environmentally friendly method for the reduction of municipal solid waste. This is because, compared to traditional storage of waste on landfills, incineration produces less greenhouse gases and destroys toxic organic compounds. The released exothermic energy can be recuperated and the residues from the combustion chamber (bottom ash) are strongly reduced in volume. However, they still form about 600 kt of waste per year in Switzerland, which needs to be landfilled. However, these residues could be potentially used as construction materials after mechanically recovering ferrous and non-ferrous metals. However, the resulting ashes (discharged dry or wet) still contain increased amount of heavy metals (exceeding state regulation) requiring them to be finally deposed on a hazardous waste site. A thermal treatment of these ashes could enable both, to separate and recuperate the remaining heavy metals and an inorganic heavy-metal poor material. The evaporation of metals depends on temperature and can be lowered by addition of chlorides, which would lower the boiling point of most metals by formation of metal chlorides (table 1). 745"

Jan 1, 2008

By R. G. Shen

The relation curve of strain and acceleration is presented in this paper. The steel pipe pile of 609.6 mm in external diameter driven by IDH-45 diesel motor hammer on the esturial shoal of Yangtze River. The ultimate bearing capacity of pile is analyzed by one dimensional wave equation and the effect of computational parameters of the equation is discussed.

Jan 1, 2010

By Vahid Tajdar

The behavior similarity between pile and cone penetration test, has guided the researchers to use the CPT results in prediction of piles bearing capacity. In this article, artificial neural networks have been used to study about relation between cone tip and sleeve friction strength obtained from cone penetration test and ultimate pile bearing capacity, obtained from static pile load test. Artificial neural networks "ANNS" is a form of artificial intelligence. ANN tries to dramatize the human nerves & brain system biology structure in self-structure. In this article, the results of relevant studies about the prediction of ultimate pile bearing capacity in especial area of soils are presented by use of back - propagation neural networks. The results of static pile load test up to failure on 63 piles with closed end and CPT test results in the place of construction these piles use in order to confirm and creation ANN model. Comparing predicted ultimate pile bearing capacity by utilizing ANN with the numbers which are predicted by 5 common traditional methods shows that using of artificial neural networks is a suitable method for predicted ultimate pile bearing capacity in identified area of texture of soil moreover it has a better operation in comparison with common traditional methods.

Jan 1, 2006

By Sufi Md Gulzar, L B. Roy

Rock engineering tasks like tunnelling, dam and building construction, and rock slope stability rely heavily on properly estimating the rock’s uniaxial compressive strength (UCS), a crucial rock geomechanical characteristic. As high-quality specimen are not always possible, scientists often estimate UCS indirectly. The primary objective of this paper is to assess the efficacy of long short-term memory (LSTM), K-nearest neighbour (KNN), a combination of particle swarm optimisation (PSO) with an artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) to estimate the UCS of sandstones from Jharia, Dhanbad, India. Point load index (PLI), porosity (n), P-wave velocity (Vp), density (ρ), and moisture content (%) are the parameters used for the present study. Finally, a comparison was made between the various prediction algorithms outputs. The findings of the study validated the effectiveness of computational intelligence methods in forecasting UCS compared to other models used in this paper. The KNN achieves overall the best results, with an R2 of 0.95 for training, 0.94 for testing, and an RMSE of 0.03 for training and 0.05 for testing.

Nov 23, 2023

By M. E. Grimes

A method of predicting uranium extraction rate in underground bacterial leaching of as-blasted ore has been developed. The method is based on the hypothesis that extraction is directly proportional to the volume of a piece of ore that is penetrated by the leaching agent, and that each piece of ore, regardless of size, has been penetrated radially from the external surface to the same depth at a given leaching time. Consequently, given an initial size and assay distribution, extraction should be predictable for a given penetration. Two laboratory bacterial leaching tests under simulated stope leaching conditions were carried out for a periods of 89 and 96 weeks. On completion, the residual ore was screened and analyzed. The information so obtained was employed to provide an elapsed time base for the penetration model, from which predictions of future extraction were made. The finding of solubilized uranium trapped within apparently sol id ore pieces was unexpected. However, it is not recoverable except after crushing, and hence does not affect calculations of underground leaching .

Jan 1, 1974

By R. G. Reddy

Viscosities of alkaline metal oxide-silicate melts were estimated using our previously developed mathematical model. The structural based model considers depolymerization effects and related breakdown of the silicate network structure, on the addition of metal oxides to the melt. The developed expression: n =4.9x10 9 NO 0 T ½ exp(E/RT) poise was used to calculate the viscosities of various binary silicate systems such as, CaO-SiO,, MgO-SiO, and MnO-SiO,, as a function of temperature and composition. Excellent agreement was obtained between the calculated and experimentally determined viscosities.

Jan 1, 1991

By A H. Bagherieh, S Mesroghli, H Jorjani, S Chehreh Chelgani

The rare earth elements (REEs) assay and recovery in leaching processes is being determined using expensive analytical methods, ICP-AES, and ICP-MS. This paper presents a neural network model to predict the effects of operational variables on the lanthanum, cerium, yttrium, neodymium recovery in the leaching of apatite concentrate. The effects of leaching times: ten to 40 min, pulp densities: 30 to 50 per cent, acid concentrations: 20 to 60 per cent and agitation rates: 100 to 200 rpm were investigated and optimised on REEs recovery in laboratory at a leaching temperature of 60¦C. The obtained data, on the laboratory optimisation process were used for training and testing of a neural network. A feed-forward artificial neural network with 4-5-5-1 arrangement, was capable of estimating the REEs leaching recovery. Neural network predicted values were in good agreement with the experimental results. The correlations of R = 1 in training stages, and R =  0.971, 0.952, 0.985 and 0.98 in testing stages were results for Ce, Nd, La and Y recovery predictions respectively and that theses values are considerably acceptable. It was shown that the proposed neural network model accurately reproduces all the effects of operation variables, and can be used in the simulation of a REEs leaching plant.

Jan 1, 2008

By Ashish Kumar Vishwakarma, Vivek Kumar Himanshu, Kaushik Dey

The accurate prediction of blast-induced ground vibration due to underground ring blasting is a prominent need for ensuring the safety of structures. Different site-specific empirical equations are available for the prediction of ground vibration. These empirical equations are best suited when the monitoring and blasting locations are present in the same medium. The change in the medium alters the behavior of wave propagation. Hence, existing empirical equations have limitations in peak particle velocity (PPV) prediction when the blasting location is an underground hard rock mine and the monitoring location is ground surface. This is because the underground metal mine comprises different levels having void in the form of excavated stope or paste-filled stope. It is very difficult to predict the magnitude of PPV on the surface in such instances. Therefore, this study has been carried out to predict the PPV at surface due to underground blasting. In this paper, PPV data was recorded at surface for 207-ring blasts. Furthermore, the PPV has also been measured at different underground locations for 47-ring blasts. Different empirical equations along with k-nearest neighbor (KNN) and random forest (RF) model of machine learning technique were developed for the prediction of PPV. Most of the empirical models have higher accuracy in the prediction of PPV at an underground location. This shows that scaled distance-based empirical predictors are best suited when the monitoring and blasting media are the same. However, the empirical models do not predict PPV accurately when the monitoring location is ground surface and the blast is conducted underground. The machine learning models are better suited for PPV prediction in such cases. Based on the analysis performed for the case study site, RF model predicts PPV at surface with the highest accuracy. The coefficient of determination and root mean square error for RF model used for predicting PPV at ground surface are 0.94 and 0.438 mm/s respectively. The RF-based model is also the best suited among all the models for predicting PPV at underground locations as well.

Apr 20, 2024

By Pratoomkhuan N. Lertsgoon

A large underground cavern with dimensions of 25m × 175m × 49m (W×L×H) was excavated in sandstone and siltstone to house 4 units of hydropower generator and was completed in 2000. In feasibility study stage, the property of the siltstone which governs the ceiling of the cavern was questionable due to slaking phenomenon. Parameters on rock properties for design were back calculated from actual ground response measured from a trial excavation. For safety of construction, comparison between prediction and actual ground responses during excavation had proceeded. The prediction was provided by means of PHASES and PHASE2 software and the actual rock response was detected by the provided monitoring system.

Jan 1, 2003

By D. Dunbar

Flooding of open pits now receives considerable attention from the mining industry as an option that may minimize environmental impacts, particularly when anoxia in pit lake deep waters can effectively eliminate oxidation of pit-wall sulphides. A state-of-the-art, coupled physical-geochemical pit lake model is used to verify that a cost-effective, environmentally responsible closure strategy for the open pit at the Kori Kollo gold mine, southeast of La Paz, Bolivia is to adopt a controlled, two-stage infilling of the open pit upon cessation of operations. By filling the pit initially with highly saline waters from evaporation/infiltration basins and naturally saline deep groundwater, followed by capping with fresh river water, a very stable and strongly stratified pit lake will be developed. In addition, the stratification will result in the isolation of metal-rich saline bottom waters from surface waters of good quality. Results of this model provide defensible predictions of the physical stability and evolution of water quality in the Kori Kollo pit lake over time. The model results indicate that anoxic conditions will develop below the fresh-saline water boundary within 1 to 2 years, followed by the rapid onset of sulphate reducing conditions in the bottom waters. Hydrogen sulphide produced by sulphate reduction will readily react with dissolved metals to form highly insoluble metal sulphides. The process results in the gradual removal of metals from the water column and the concomitant improvement of water quality over time. A notable benefit of this strategy is that it can be fully integrated with other mine site closure options as well as future environmental management strategies. The proposed plan allows for: 1) safe storage of saline evaporation basin waters; 2) the potential for passive treatment in anoxic bottom waters of ARD seepages from other mine site operations should they arise; and 3) a repository for future reactive wastes that could be effectively isolated in a physically and chemically stable environment.

Jan 1, 2001

By Quin Dennis

Process Optimization ?What is it really? It is NOT ?a larger fan to increase draft through a process ?a larger pump on a wet circuit ?a wider conveyor belt for solid materials ?a larger feed elevator into or out of a process These relieve individual constraints ??bottlenecks??and allow operation to the next constraint in the process ?It is also NOT about automating the operator ?which captures consistency but is not continuous optimization

Nov 1, 2011