Based on reported statistics, rockburst phenomenon is the main cause of many casualties and accidents occurred during the construction of deep underground structures. Therefore, its prediction in ...initial stages of design has a remarkable role on enhancement of safety. In this paper, two models have been developed for rockburst evaluation using the C5.0 decision tree classifier. The first model has been applied for prediction of rockburst occurrence and the second model for prediction of rockburst intensity. These models have been developed based on a database including 174 rockburst case histories. In both models, stress coefficient, rock brittleness coefficient, and the elastic strain energy index are the predictive variables. These models are easy to use and do not require extensive knowledge. Based on decision rules derived from these models, the rockburst occurrence and intensity can be evaluated easily. The results revealed that the proposed approach is a useful and robust technique for long-term prediction of rockburst.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Estimating the field penetration index (FPI) is an essential task in tunneling as the FPI is used to determine the tunnel boring machine (TBM) performance. In this study, fuzzy inference system (FIS) ...modelling is implemented to predict the FPI. Several models including fuzzy clustering and knowledge-based models were proposed. Data from the Queens Water Tunnel underneath Brooklyn and Queens were used to establish and validate the models. The input parameters include the rock type, uniaxial compressive strength, Brazilian tensile strength, rock brittleness (BI) of the intact rock, the angle between the plane of weakness and the TBM driven direction (Alpha), the distance between planes of weakness (FS), and the TBM cutter load. In order to evaluate the effect of the characteristics of the fractures on the FPI prediction, several models with different inputs and dataset structures were explored. The models were tested with independent datasets and performance indices used included the coefficient of determination R2, values account for (VAF), root-mean square error (RMSE) and mean absolute percentage error (MAPE). Overall, the model performance results were satisfactory with R2, VAF, RMSE and MAPE ranging between 0.79–0.92; 79.42–92.06%; 6.66–11.05; and 5.68–8.96%, respectively indicating good predictability capability. The models based on fuzzy clustering yielded higher accuracy. It was established that BI, Alpha and CL were the parameters controlling mostly the FPI. Based on that, the knowledge-based model was developed and satisfactory results were achieved as well. It was concluded that the FISs could be used to estimate the FPI values with a reliable accuracy.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The wear of cutting tools is critical for any engineering applications dealing with mechanical rock excavations, as it directly affects the cost and time of project completion as well as the ...utilization rate of excavators in various rock masses. The cutting tool wear could be expressed in terms of the life of the tool used to excavate rocks in hours or cutter per unit volume of excavated materials. The aim of this study is to estimate disc cutter wear as a function of common mechanical rock properties including uniaxial compressive strength, Brazilian tensile strength, brittleness, and density. To achieve this goal, a database of cutter life was established by analyzing data from 80 tunneling projects. The data were then utilized for evaluating the relationship between rock properties and cutter consumption by means of cutter life index. The analysis was based on artificial intelligence techniques, namely artificial neural networks (ANN) and fuzzy logic (FL). Furthermore, linear and non-linear regression methods were also used to investigate the relationship between these parameters using a statistical software package. Several alternative models are introduced with different input variables for each model, to identify the best model with the highest accuracy. To develop these models, 70% of the dataset was used for training and the rest, for testing. The estimated cutter life by various models was compared with each other to identify the most reliable model. It appears that the ANN and FL techniques are superior to standard linear and non-linear multiple regression analysis, based on the higher correlation coefficient (R2) and lower Mean square error (MSE).
The rock quality designation is an important input for the analysis and design of rock structures as reliable spatial modeling of the rock quality designation (RQD) can assist in designing and ...planning mines more efficiently. The aim of this paper is to model the spatial distribution of the RQD using the multi-Gaussian kriging approach as an alternative to the non-linear geostatistical technique which has shown some limitations. To this end, 470 RQD datasets were collected from 9 boreholes pertaining to the Gazestan ore deposit in Iran. The datasets were declustered then transformed into Gaussian distribution. To ensure the model spatial continuity, variogram analysis was first performed. The elevation 150 m with a grid of 5 m × 5 m × 5 m was selected to illustrate the methodology. Surface maps showing the RQD classes (very poor, poor, fair, good, and very good) with their associated probability were established. A cross-validation method was used to check the obtained model. The validation results indicated good prediction of the local variability. In addition, the associated uncertainty was quantified on the basis of the conditional distributions and the accuracy plot agreed with the overall results. It is concluded that the proposed model could be used to produce a reliable RQD map.
Full text
Available for:
CEKLJ, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The stability assessment of a potential tunnel, especially a tunnel excavated under complicated geological conditions, is an essential task in tunnel design because it helps to determine the most ...suitable support system. In this paper, the deformation and failure mechanism of the rock mass surrounding a tunnel driven in water-rich soft rock with a fault zone are investigated. The Youfangping Tunnel, which is located along the Changsha-Kunming section of the Shanghai-Kunming High-Speed Railway, China, is used as a case study. The two main factors influencing the mechanical response of the surrounding rock mass, namely, the existence of a fault (geological structure) and groundwater, are considered in the analysis. Three cases, namely, no fault or groundwater, only a fault, and both a fault and groundwater, are simulated to investigate the deformation and failure mechanism of the surrounding rock and the internal force of the primary support. The results show that the existence of the fault induces shear stress concentration near the fault plane, which causes shear failure of the surrounding rock and contributes to the reduction in the rock mass strength under the action of groundwater, resulting in a failure mode with plastic flow, squeeze-out and shear sliding. The obtained results could assist in the design and construction of tunnels in water-rich soft rock with faults.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Since rockburst is a violent expulsion of rock in high geostress condition, this causes considerable damages to underground structures, equipments and most importantly presents serious menaces to ...workers' safety. Rockburst has been associated with thousands of accidents and casualties recently in China. Due to this importance, this research was intended to predict rockburst intensity based on fuzzy inference system (FIS) and adaptive neuro-fuzzy inference systems (ANFIS), and field measurements data. A total of 174 rockburst events were compiled from various published research works. Five different models were investigated. The maximum tangential stress, the uniaxial compressive strength, the uniaxial tensile strength of the surrounding rock and the elastic strain energy index were considered as the inputs while the actual rockburst intensity was the output. In some models, the inputs were extended to the stress coefficient and the rock brittleness coefficient. The results obtained from the study conclude that the knowledge-based FIS model shows lowest performance with 45.8%, 13.2%, 16.5% and 66.52% of the variance account for (VAF), root-mean square error (RMSE), mean absolute percentage error (MAPE) and the percentage of the successful prediction (PSP) indices, while the ANFIS model indicates the best performance with 92%, 1.71%, 0.94% and 95.6% of VAR, RMSE, MAPE and PSP indices, respectively. These results suggest that the developed models in the present study can be used for the rockburst prediction, and this may help to reduce the casualties sourced from the rockbursts.
► Five different fuzzy inference systems were developed for rockburst prediction. ► The models were calibrated using field data selected from published works. ► The results indicated that the models can predict rockburst in a reliable manner. ► The knowledge-based model yielded the lowest performance. ► The ANFIS model showed the best performance.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Support failures in mine drifts represent potential hazards that threaten underground mine safety and productivity. The aim of this study is to determine the reliability index associated with the ...rock supporting elements used in Ridder-Sokolny mine, an underground mine located in East Kazakhstan. Numerical simulations of the drift support and the First Order Reliability Method (FORM) were employed to carry out the analysis. Several support cases were considered including: shotcrete, bolting, concrete, bolting combined with concrete and unsupported drift case. For each support case, the Factors of Safety (
FS
), the reliability index (
β
) and the Probability of Failure (
P
F
) were determined in accordance with the corresponding rock mass quality and the excavation geometry. The results indicate a slight variation of the average FS values for the different support cases (except for shotcrete) while
β
and
P
F
vary more significantly between 0.62–3.25 and 0.05–27 (× 10
3
%) factor depending on the rock conditions and the installed support. The probability of failure of the rock support increases with a decrease in the rock mass quality. Similar trends are observed with an increase of the width/height ratio of the excavations for the same rock domain. These results illustrate that a single FS value obtained from a deterministic method may not always provide a sufficient indication of safety. This is in agreement with the field observations which have indicated a poor performance of the supports. Hence, on the basis of the reliability index of the supports, the requirement in terms of coefficient of variability of the rock mass quality to meet the target performance level is proposed. It is concluded that the results of this study could help improving the drift support design in Ridder-Sokolny mine.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In 2005, when two main tunnels were excavated in Faer Coal Mine, Guizhou Province, China, an unknown ancient landslide, subsequently named Dazhai landslide, was encountered. Roof caving, large ...convergence and severe support damage in the tunnels, as well as several ground subsidence occurred. The two tunnels have been kept stable after an inner supporting treatment in 2008. However, since a heavy rainfall in July 2010, some transverse cracks were observed at the landslide toe, determining significant additional costs over the normal administration of the mine. Invited by the owner, we performed a comprehensive investigation to evaluate the stability of Dazhai landslide crossed by two main tunnels. Firstly, field surveys and mappings were completed to obtain a preliminary delineation of the landslide surface, and a geological drilling along the central landslide axis was accomplished to depict the sliding surface. After that, a monitoring system containing a GPS–RTK network and six observation sections in one tunnel were established and a 12-month monitoring was conducted. Moreover, to obtain an overall comprehension, numerical simulations were carried out by using GeoStudio and FLAC3D software. The results from site drilling, monitoring and simulations indicate that the Dazhai landslide is stable as a whole, and only local shallow landslides might occur. The local instability of Dazhai landslide has limited impact on the safety of the two main tunnels. This conclusion has led to a budget savings of over RMB 40million.
•Stability of an ancient landslide crossed by two coal tunnels was studied.•Field surveys, drillings, monitoring and numerical simulations were applied.•This landslide is stable as a whole, and only local shallow landslides might occur.•Local instability of the landslide has little impact on the shaft safety.•This study has led to a budget savings of over RMB 40million for the owner.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
In this work, three extensions to the traditional discontinuous deformation analysis (DDA) method are tested to simulate the entire process describing the behavior of landslides induced by reservoir ...impoundment. These extensions include the discretization of the area of interest, block gluing and the HM (hydro-mechanical) coupling approach. Several hydraulic boundary conditions are introduced based on the water level during the dry and rainfall seasons. As verification, the entire processes for two practical landslides, the Qianjiangping and the Majiagou landslides, which occurred in the Three Gorges Reservoir (TGR) of China, are simulated. The simulation results agree well with the observed failure modes, indicating that the proposed methodology can intuitively reproduce the entire reservoir impoundment induced landslide process.
•DDA method is extended to simulate reservoir impoundment induced landslides.•FE meshing technique, gluing algorithm and HM coupling are introduced.•Qianjiangping and Majiagou landslides in Three Gorges Reservoir are simulated.•The simulated results agree well with the late observations.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
With a mining-driven economy, Botswana has experienced increased geochemical exploration of minerals around existing mining towns. The mining and smelting of copper and nickel around Selibe-Phikwe in ...the Central Province are capable of releasing heavy metals including Pb, Fe, Mn, Co, Ni and Cu into the soil environments, thereby exposing humans, plants and animals to health risks. In this study, turning bands co-simulation, a multivariate geostatistical algorithm, was presented as a tool for spatial uncertainty quantification and probability mapping of cross-correlated heavy metals (Co, Mn, Fe and Pb) risk assessment in a semiarid Cu–Ni exploration field of Botswana. A total of 1050 soil samples were collected across the field at a depth of ~ 10 cm in a grid sampling design. Rapid elemental concentration analysis was done using an Olympus Delta Sigma portable X-ray fluorescence device. Enrichment factor, geoaccumulation index and pollution load index were used to assess the potential risk of heavy metals contamination in soils. The partially heterotopic nature of the dataset and strong correlations among the heavy metals favors the use of co-simulation instead of independent simulation in the probability mapping of heavy metal risks in the study area. The strong correlation of Co and Mn to iron infers they are of lithogenic origin, unlike Pb which had weak correlation pointing to its source in the area being of anthropogenic source. Manganese, Co and Fe show low enrichment, whereas Pb had high enrichment suggesting possible lead pollution. We, however, recommend that speciation of Pb in the soils rather than total concentration should be ascertained to infer chances of possible bioaccumulation, and subsequent health risk to human by chronic exposure.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
PDF
