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  • 1.
    Idris, Musa Adebayo
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Probabilistic Stability Analysis of Underground Mine Excavations2014Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    The creation of underground mine excavation disturbs the original state of the rock mass surrounding the excavation which often leads to instability of the excavation. This poses a threat to the safety of personnel and equipment in and around such excavations. Therefore the stability of underground mine excavations has always been a major concern to geotechnical engineers. The stability of the excavations depends on physical and mechanical properties of the rock masses as well as the in situ stress condition. For stability analyses, these parameters are determined either by in situ investigations or laboratory tests. Because of the inherent uncertainties associated with natural materials such as rock masses, the precise values of the properties are never known. The sources of these uncertainties could be inherent variability caused by random process (aleatory uncertainty) or it could be a knowledge-based uncertainty (epistemic uncertainty) such as measurement error or model transformation uncertainty. Traditional deterministic methods, which use mean or single characteristics value of the input parameter for stability analyses, do not consider the inherent uncertainties in the rock mass properties hence the underlying effects of the uncertainties become obscure. Depending on the distributive character of these uncertainties, the deterministic methods may lead to results which are not representative of real behaviour. Therefore, for a realistic stability analysis of an underground excavation the uncertainties must be adequately considered in the analysis using probabilistic methods. With probabilistic methods, the likelihood of occurrence of unsatisfactory performance or failure of the underground excavation can be estimated with respect to a predefined tolerable limit. Even though probabilistic methods have been increasingly used in slope stability analyses, the application of probabilistic methods has not received considerable attention in the stability analyses of underground mine excavations for instance. Therefore, there is need for an increased understanding of the effect of uncertainty in the rock mass properties on the stability of underground mine excavations so as to facilitate the application of the probabilistic methods in the stability analysis of the underground excavation. This thesis is therefore aiming in that direction and thus the objective. To achieve this aim, the uncertainties in rock mass properties were quantified so as to determine the statistical parameters and the probability density functions for the random rock mass parameters. Different probabilistic methods, each with different sampling techniques and assumptions, were incorporated with commercial finite difference numerical code to analyse the stability of underground mine excavations for different case studies. The probabilistic methods considered were Point Estimate Methods (PEM), Artificial Neural Network (ANN), Response Surface Method (RSM), Monte Carlos Simulation (MCS) and Strength Classification Method (SCM). The results of these analyses were reported in a series of papers which make up this thesis. The methodology, results and conclusions from this thesis will increase the understanding of the effects of uncertainty in rock mass properties and facilitate the application of probabilistic methods to the analyses of underground excavation stability.

  • 2.
    Idris, Musa Adebayo
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Basarir, Hakan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Nordlund, Erling
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Wettainen, Thomas
    Luossavaara-Kiirunavaara AB. SE-98381, Malmberget.
    The probabilistic estimation of rock masses properties in Malmberget mine, Sweden2013Inngår i: The Electronic journal of geotechnical engineering, ISSN 1089-3032, E-ISSN 1089-3032, Vol. 18, nr B, s. 269-287Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Numerical modeling techniques have been applied in many mining and civil engineering projects. Traditionally, deterministic methods have been used frequently for the estimation of design or input parameters for numerical modeling. Whereas, it is known that the effect of variability and uncertainty sourced from the complex and variable nature of rock cannot be considered by deterministic approaches using single or mean value. In this paper, the authors tried to apply a probabilistic approach to consider the uncertainties and variability in rock properties. This is to make more a realistic assessment of design parameters of rock masses around an instrumented test drift in Malmberget Mine within the content of the “Rock mass - Rock support interaction project” conducted at the Division of Mining and Geotechnical Engineering, Lulea University of Technology. To calculate the design parameters GSI of rock mass, UCS and mi constant of the intact rock are considered as random variables. For each of these random variables ranges were specified depending on the laboratory and field information. Using Monte Carlo simulation method a possible range of each of necessary strength and deformability properties were obtained and presented. The assessed values can be used as preliminary input parameters and considered as basis for further numerical modeling calibration studies.

  • 3.
    Idris, Musa Adebayo
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Nordlund, Erling
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Saiang, David
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Comparison of different probabilistic methods for analyzing stability of underground rock excavations2016Inngår i: The Electronic journal of geotechnical engineering, ISSN 1089-3032, E-ISSN 1089-3032, Vol. 21, nr 21, s. 6555-6585Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Stability analyses of underground rock excavations are often performed using traditional deterministic methods. In deterministic methods the mean or characteristics values of the input parameters are used for the analyses. These method neglect the inherent variability of the rock mass properties in the analyses and the results could be misleading. Therefore, for a realistic stability analyses probabilistic methods, which consider the inherent variability of the rock mass properties, are considered appropriate. A number of probabilistic methods, each based on different theories and assumptions have been developed for the analysis of geotechnical problems. Geotechnical engineers must therefore choose appropriate probabilistic method to achieve a specific objective while taking into account simplicity, accuracy and time efficiency. In this study finite difference method was combined with five different probabilistic methods to analyze the stability of an underground rock excavation. The probabilistic methods considered were the Point Estimate Method (PEM), the Response Surface Method (RSM), the Artificial Neural Network (ANN), the Monte Carlos Simulation (MCS), and the Strength Classification Method (SCM). The results and the relative merits of the methods were compared. Also the general advantages of the probabilistic method over the deterministic method were discussed. Though the methods presented in this study are not exhaustive, the results of this study will assist in the choice of appropriate probabilistic methods for the analysis of underground rock excavations. 

  • 4.
    Idris, Musa Adebayo
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Saiang, David
    Nordlund, Erling
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Consideration of the rock mass property variability in numerical modelling of open stope stability2012Inngår i: Föredrag vid Bergmekanikdag i Stockholm, 12 mars 2012, Stockholm: Stiftelsen bergteknisk forskning - Befo , 2012, s. 111-123Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    This paper presents a probabilistic approach for modelling complex rock masses wherethe intrinsic properties are highly variable. For this study a complex orebody in aCanadian mine is used. The mechanical properties of the host rock and the ore in thismine are found to be intrinsically variable with high contrast between their mechanicalproperties. It is apparent that the use of traditional deterministic methods to study thebehaviour of the open stopes is not appropriate for this mine. Hence, in this study aprobabilistic approach is adopted which allows the propagation of the variability of theinput parameters in the numerical modelling. Three different approaches were used toanalyze the stability of the open stopes based on the distribution of the different materialproperties of the rock mass. The results of the analysis using the three methods werecompared and the limitations and the potentials of each of the methods were discussed.The study provides insight into the significance of the rock mass property variability inthe numerical modelling of open stope stability and different ways that it could beincorporated into the modelling.

  • 5.
    Idris, Musa Adebayo
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Saiang, David
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Nordlund, Erling
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Numerical analyses of the effects of rock Mass property variability on open stope stability2011Inngår i: 45th US Rock Mechanics /Geomechanics Symposium, San Francisco, CA, USA: ARMA, American Rock Mechanics Association , 2011Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The rock mass is intrinsically variable in its physical and mechanical properties which makes it complex. This complexity is evident from the spatial random distribution of the properties from any site characterization program. The precise values for these properties are never known in most cases hence most geotechnical mine designs are based on fixed or discrete values of rock mass properties for stability analysis. This traditional deterministic approach neither reflects the inherent variability nor the uncertainty in the rock mass properties. Therefore, it is desirable to utilize a probabilistic approach which provides a range of possible results based on the variability in the rock mass properties. Understanding the effect of this random distribution and variability of the properties on stope stability is essential for more realistic mine design. In this study, a series of numerical analyses using the explicit finite difference element code FLAC, have been conducted to study the effect of the random distribution and variability of rock mass properties on the stope stability. The rock mass in the FLAC model is represented by different material properties randomly distributed to each zone. In order to compare the results, fixed average values of the material properties were also used for the FLAC model in another simulation. The results clearly indicate that rock mass property variability does affect the stope stability and that a deterministic approach to stope stability analysis could lead to conservative results.

  • 6.
    Idris, Musa Adebayo
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Saiang, David
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Nordlund, Erling
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Probabilistic analysis of open stope stability using numerical modelling2011Inngår i: International Journal of Mining and Mineral Engineering, ISSN 1754-890X, E-ISSN 1754-8918, Vol. 3, nr 3, s. 194-219Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A probabilistic approach is presented for the analysis of open stopestability. The approach considers the inherent variability and uncertainty whichare typical of rock mass properties. In this study, a series of numerical analyseswere performed using FLAC to study the stability of open stopes while takinginto account the variability in the rock mass properties. The rock mass wasdivided into six strength classes: three classes for the host rock and threeclasses for the massive sulphide ore. Each class was randomly distributed to theelements in the FLAC model. The host rock-to-massive sulphide ore ratio isenvisaged to have a strong influence on the stope. To verify this, three casesof different ore percentages were considered and the results compared.The results, which were presented as Probability Density Functions (PDFs),indicate that the zones of low stiffness show high range of displacements andthat the increase in the percentage of the ore significantly affects the stability ofthe stopes.

  • 7.
    Idris, Musa Adebayo
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Saiang, David
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Nordlund, Erling
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Stochastic assessment of pillar stability at Laisvall mine using Artificial Neural Network2015Inngår i: Tunnelling and Underground Space Technology, ISSN 0886-7798, E-ISSN 1878-4364, Vol. 49, s. 307-319Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Stability analyses of any excavations within the rock mass require reliable geotechnical input parameters such as in situ stress field, rock mass strength and deformation modulus. These parameters are intrinsically uncertain and their precise values are never known, hence, their variability must be properly accounted for in the stability analyses. Traditional deterministic approaches do not quantitatively consider these uncertainties and variability in the input parameters. To incorporate these variability and uncertainties stochastic approaches are generally used. In this study, a stochastic assessment of pillar stability using Artificial Neural Network (ANN) is presented. The variability and uncertainty in the rock mass properties at the Laisvall mine were quantified and the probability density function of the deformation modulus of the rock mass was determined using probabilistic approach. The variability of the in situ stress was also considered. The random values of the deformation modulus and the horizontal in situ stresses were used as input parameters in the FLAC3D numerical simulations to determine the axial strain in the pillar. ANN model was developed to approximate an implicit relationship between the deformation modulus, horizontal in situ stresses and the axial strain occurring in pillar due to mining activities. The closed-form relationship generated from the trained ANN model, together with the maximum strain that the pillar can withstand was used to assess the stability of the pillar in terms of reliability index and probability of failure. The results from this study indicate that, the thickness of the overburden and pillar dimension have a substantial effect on the probability of failure and reliability index. Also shown is the significant influence of coefficient of variation (COV) of the random variables on the pillar stability. The approach presented in this study can be used to determine the optimal pillar dimensions based on the minimum acceptable risk of pillar failure

  • 8.
    Lawal, Abiodun Ismail
    et al.
    Department of Mining Engineering, Federal University of Technology, Akure, Nigeria.
    Idris, Musa Adebayo
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi. Department of Mining Engineering, Federal University of Technology, Akure, Nigeria.
    An artificial neural network-based mathematical model for the prediction of blast-induced ground vibrations2019Inngår i: International Journal of Environmental Studies, ISSN 0020-7233, E-ISSN 1029-0400Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents an artificial neural network (ANN) based mathematical model for the prediction of blast-induced ground vibrations using the data obtained from the literature. A feed-forward back-propagation multi-layer perceptron (MLP) was adopted, and the Levenberg–Marquardt algorithm was used in training the network. The powder factor, the maximum charge per delay, and distance from blasting face to monitoring point are the input variables. The peak particle velocity (PPV) is the targeted output variable. The model was then formulated using the weights and biases output from the ANN simulation. Multilinear regression (MLR) analysis was also performed using the same number of datasets, as in the case of ANN. The quality of the proposed ANN-based model was also tested with another 14 datasets outside the one used in developing the models and compared with more classical models. The coefficient of the determination (R2) of the proposed ANN-based model was the highest.

  • 9.
    Onifade, Moshood
    et al.
    Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam. Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
    Lawa, Abiodun Ismail
    Department of Mining Engineering, Federal University of Technology, Akure, Nigeri.
    Aladejare, Adeyemi Emman
    Oulu Mining School, University of Oulu, Oulu, Finland.
    Bada, Samson
    Clean Coal and Sustainable Energy Research Group, University of the Witwatersrand, Johannesburg, South Africa.
    Idris, Musa Adebayo
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Prediction of gross calorific value of solid fuels from their proximate analysis using soft computing and regression analysis2019Inngår i: International Journal of Coal Preparation and Utilization, ISSN 1939-2699Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The determination of gross calorific value (GCV) of solid fuel is important because GCV is frequently required in the design of most combustion and other thermal systems. However, experimental determination of GCV is time-consuming, which necessitated the development of different empirical equations to estimate GCV using the elemental composition of the solid fuels. With the growing popularity of empirical equations for estimation of GCV of solid fuels, there is a need to develop reliable and suitable models for the prediction of GCV of coal from the South African coalfields (SAC). In this study, empirical models were developed to determine the relationship between the proximate analysis of coal with its GCV, using soft computing and regression analyses. A total of 32 coal samples were used to develop three empirical models based on soft computing techniques, namely; adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN), and regression analysis using multilinear regression (MLR). The performances of the proposed models were evaluated using coefficient of determination (R2), mean absolute percentage error (MAPE), mean squared error (MSE) and variance accounted for (VAF). The R2, MAPE, MSE and VAF for the ANFIS are 99.92%, 2.0395%, 0.0778 and 99.918% while for the ANN, they are 99.71%, 2.863%, 0.2834 and 99.703%. The R2, MAPE, MSE and VAF for the MLR are 99.46%, 3.551%, 0.5127 and 99.460%. From the soft computing and regression analysis studies conducted, the ANFIS was found as the most suitable model for predicting the GCV for these coal samples.

  • 10.
    Oniyide, G.O.
    et al.
    University of the Witwatersrand, Johannesburg, South Africa. Federal University of Technology Akure, Akure, Nigeria.
    Idris, Musa Adebayo
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi. Federal University of Technology Akure, Akure, Nigeria.
    Numerical Modelling of the Effect of Temperature Variation on Stope Stability in Bushveld Igneous Complex2019Inngår i: Mining of Mineral Deposits, E-ISSN 2415-3443, Vol. 13, nr 2, s. 121-131Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Purpose. This paper presents the result of the research carried out on the effect of increasing temperature and stres-ses with depth of mining on the stability of stope within the Bushveld Igneous Complex (BIC), where the South African Platinum mines are located.

    Methods. The stability of stope at the platinum mine was analysed using numerical modelling. A commercial geotechnical software, FLAC (Fast Lagrangian Analysis of Continua), was used for the numerical modelling to study and to understand the behaviour of the rock in the deep and hot underground excavations. The modelling is hypothe-tical in the sense that there are no direct field measurements of failure or displacements. However, some field data received from the mines include virgin rock temperature, in-situ stress data.

    Findings. The plots of the yielded zones of the model for excavations at the depths of 1073, 2835 and 5038 m re-vealed that there would be shear and tensile failures at 2835 and 5038 m, however, these failures will be higher at 5038 m than what will be witnessed at shallow depths. This observation could be attributed to higher in-situ stresses and virgin rock temperatures.

    Originality. Major researches on the platinum mine have not extensively consider the influence of the increased temperature at the ultra-depth level hence this study aims to fill the gap by studying the effect of the increased tem-perature and stresses on the stability of stopes at the ultra-depth levels within the BIC.

    Practical implications. This research showed that mining at ultra-deep levels would pose a challenge of an increase in horizontal and vertical displacements with increasing depth. It is recommended that horseshoe-shaped stopes could be preferred in such conditions to avoid high-stress concentration at the corners of the roof of the stopes, which may reduce failures from shallow-depth to ultra-depth levels. Also, based on the magnitude of convergence that will be experienced at ultra-deep mining levels (3500 to 5000 m), it is recommended that access development is located in the more competent strata, such as in mottled anorthosite with an average UCS of 82 MPa.

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