Disaster Advances

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Disaster Advances





Prediction of Landslide Hazard Area using GIS and Probability Models

Park Jin-Woo and Lee Jung-Soo

Landslide hazard area was predicted using conditional probability models under climate change scenarios. The primary predictors for landslides were forest type, slope aspect, slope gradient and rainfall. By using these factors, a landslide area was predicted by both the Direct and Bayes models. We tested two partitioning approaches, half-portion partitioning and systematic grid partitioning, in constructing the prediction models. In each approach, the study area was partitioned into two groups for training and validation and then reversed to verify the partitioning approach. Bayes model had high accuracy and consistent results in both half-portion partitioning and systematic grid partitioning. Thus, the Bayes model was a better option for landslide hazard prediction of the study area. Considering the climate change scenario A1B, the landslide hazard map based on Bayes model estimated that the landslide occurrence rate remained high in the northern part of study area while that of the southern part decreased over time thereby creating a polarization between the two regions.

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Cracking of surrounding rocks induced by excavation unloading in deep tunnels

Zhang Wenju, Lu Wenbo and Yang Jianhua

Cracking of surrounding rocks induced by excavation unloading in deep tunnels is a typical cause for engineering disasters. Cracking mechanism in surrounding rocks of tunnels induced by excavation unloading is investigated via theoretical and numerical analyses. First, an initiation cracking model under the biaxial compression is adopted to simulate cracking induced by unloading. Second, crack mechanism in surrounding rocks of deep tunnels induced by excavation unloading is analyzed. Finally, the cracking influencing factors of quasi-static and effect of transient unloading on cracking zone distribution are discussed. The results indicate that the excavation unloading has a significant influence on cracking of surrounding rocks in deep tunnels and the compression-shear mode is the main failure mode of deep tunnels under quasi-static unloading. Moreover, the cracking condition of surrounding rocks is mainly determined by initial stress conditions and the crack parameters. Compared with the quasi-static loading condition, additional dynamic stress will be generated by the transient release of in-situ stress in surrounding rocks. This leads to the enlargement of the radial unloading and the circumferential loading effects which further aggravate the cracking effect and broaden the damaged zone. The cracking depth and range increase as lateral pressure coefficient increases and the cracking region is in the shape of ‘V’ notch. This study is of great significance for further understanding of the cracking failure mechanism of surrounding rocks.

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Causal Factor Analysis of Chinese Coal Mining Accident based on HFACS Frame

Yunxiao Fan and Yangke Guo

As the paramount energy source in China, the exploration for coal and development of coal mining has been important for the national economy. Coal mining has been viewed as an inherently high-risk industry in China and there is little doubt that human error contributes to the majority of the accidents. In order to find the hidden failures occurring at the blunt end of a system which leads to the sharp end of human error, 107 coal mining accidents spanning the year of 2007 to 2012 were reviewed and a theoretical framework (the Human Factors Analysis and Classification System, HFACS) was adopted as a means of identifying errors associated with accidents in China. Overall, HFACS proved useful in categorizing errors from existing accident reports and in capturing the full range of relevant human factors data. The study also showed that lack of tailored practice training and procedures for the job can easily trigger operators’ unsafe acts and if supervision ability was poor, these unsafe acts could not be identified and controlled. A poor technical environment and poor communication climate are other triggers of operators’ unsafe acts; they are further causal factors resulting from a poor organizational process.

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Mechanism of Intense Strata Behaviors at Working face influenced by Gob Pillars of Overlying Coal Seam

Yang J.X., Liu C.Y. and Yu B.

In this study, influences from stresses of gob pillars in Jurassic coal seam and roof caving range in the gob of Carboniferous seam are analyzed through theoretical analysis and field measurement. The mechanism of intense strata behaviors under combined effects of pillars and coal caving movements is revealed. The investigation showed that when the excavation of Carboniferous seam passes below gob pillars of Jurassic seam, intense strata behaviors occur at the working face and create severe impacts on working face and the two ends of the roadway. In the strata below gob pillars of Jurassic seam, both horizontal and vertical stresses reach 10.5MPa which is relatively high while depths of the stress concentration areas are only 50 to 70 meters. Elastic energy is relatively concentrated in the strata below gob pillars with maximum energy density of about 3.8kPa while the influencing depth is only 50 meters. Borehole televiewers and electromagnetic imaging show that after no.8105 working face of Carboniferous seam passed the pillars of Jurassic seam, effective height of the influenced area of roof caving zone in the gob is about 150 meters. Both theoretical analysis and field measurement show that the intense strata behaviors occur when the excavation of Carboniferous seam passes under pillars of Jurassic seam is mainly caused by combined effects of pillars and inter-strata roof caving movements.

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The effects of Different Prediction Parameters on the Mining Subsidence Forecast Result

Debao Yuan

Mining subsidence prediction is one of the main contents in mining subsidence science. With the prediction results, the quantitatively research can be done on the distribution law of strata and ground movement in time and space effected by the mining which is important to guide the mining practice under the buildings, railways and waters. This paper analyses and gets the reasons for deviation of the surface movement and deformation result by the mining subsidence theory and probability integral method. The effects on the prediction result of different parameters under same and different mining conditions are also analyzed using subsidence prediction and data processing integration system to draw the corresponding isolines. The preliminary assessment of the parameters effect is made. It is expected to have some guidance and reference for mining subsidence prediction.

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Comparison of Fuzzy Model and Frequency Ratio Model for the analysis of Kundha Landslides in Nilgiris District

Evany Nithya S., Rajesh Prasanna P. and Eswaramoorthi S.

Landslides pose a major threat in mountainous regions like Nilgiris. Although most of the landslides occur during rainy season, the geographic location of such landslides remains unpredictable, posing significant disaster management problems. Although a number of methods are available, fuzzy-logic provides an easy and intuitive way for assessment of landslide susceptibility. However, the validity of fuzzy-logic models with statistical methods viz., frequency-ratio method complemented with field observation shall provide a robust basis for application of these models for specific and adjoining geographical areas. Such a kind of comparison was made using the susceptibility index map developed by considering the causative factors such as slope, soil depth, geomorphology, geology, land use, drainage density, lineament density, runoff and proximity to the road. Using linear membership function, the susceptibility indices developed by both methods were rescaled between 0 and 1 for comparison. The results provide a reasonably accurate estimation for the landslide forecasting when compared with the frequency ratio method, indicating that fuzzy-logic methods have statistical validity.

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Evaluation of Highway Landslide Hazard based on Information Entropy and Uncertainty Measure Theory

He Hujun and Qu Cuixia

Analyzing on highway landslide hazard evaluation characteristics and existing problems of evaluation method, combining with information entropy theory and uncertainty measurement theory, highway landslide hazard evaluation model was put forward on the basis of information entropy and unascertained measure theory. Information entropy was used for the reduction of highway landslide hazard evaluation index system, the removal of redundant index; highway landslide hazard was carried through evaluation on the basis of uncertainty measure theory. At the same time, combined with 15 landslides in Yingxiu-Wolong of S303 line, the validity of the model was verified. Research results show that the method uses information entropy to reduce evaluation index, evaluation accuracy is not reduced but the amount of calculation is reduced. Landslide hazard evaluation provides significance for the future.

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Prediction of compressive strength from microfabrics properties of banded amphibolite rocks using artificial neural networks and multivariate regression techniques

Esamaldeen Ali, Guang Wu and Zhiming Zhao

In complex inherent characteristics of certain rocks, especially anisotropic rock, it may be difficult to measure the uniaxial compressive strength (UCS). However, the use of empirical relationships to estimate UCS of rocks can be more practical and economical. In this study, the prediction capability of the Artificial Neural Networks (ANNs) and multivariate regression methods has been carried out to predict UCS from microfabrics properties of banded amphibolite rocks. Based on statistical analysis, microfabrics parameters including grain Size, shape factor and quartz content that adequately affect the values of UCS have been adopted in this study. The ANNs model was performed using the same input variables as multivariate regression model. To assess the models performances, some performance indices such as correlation coefficient (R), variance account for (VAF) and root mean square error (RMSE) were calculated and compared for the two models. The results show that even though the developed two models are reliable to predict the UCS, the study clearly indicates the superiority of the ANN model based on the model performance indices. This approach can be easily extended to the modeling of rock strength and deformation parameters in the absence of adequate geological information or abundant data.

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Comparative study of infrared precursors from the excavation experiments on differently inclined stratified rocks

Weili Gong and Yanyan Peng

This paper presents an investigation of three infrared precursors including energy release, heterogeneity and thermography precursors from the excavation experiments on geological models with horizontally, 45 and vertically inclined rock strata. The energy release precursor reveals the overall behaviors of the three strata when undergoing full-face excavation (phase 1: excavating a passage with small face area) and staged excavation (phase 2: expanding the roadway face by removing rock blocks). Time-marching scheme for the horizontal strata exhibited a linear increase during phase 1 and plastic behavior over phase 2, for the vertical strata exhibited similar behavior over phase 1 and stick-slip oscillation in phase 2 and for 45 strata exhibited a piecewise linearity with sliding events in phase 1 and stick-slip behavior like the vertical strata. The heterogeneity precursors were obtained by performing the curve fitting on the energy release data based on Weibull distribution. The resultant Weibull modulus characterized the heterogeneity manifested by the three geological models under excavation. Thermography precursor is the image feature extracted by performing image processing procedures on the raw thermogram sequence. The most significant finding is the intense far-field stationary frictions along the bedding interfaces in the early period of the phase 1 excavation.

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The Distribution and Control Measures of PM2.5 in Coal Mine Workface

Baisheng Nie , Hongqi Lu , Xiangchun Li , Weina Yuan , Jianhua Guo, Li Li and Fei Xue

With the mechanization and modernization of coal mine, the dust concentration in coal mine workface is larger and larger and the number of pneumoconiosis in coal mine is more and more, so it is a big problem to impede coal mines’ smooth development. In order to analyze the distribution law of PM 2.5 in workface, the dust concentration of 2203 workface at Zhangcun coal mine is measured. The result shows that the dust concentration is becoming larger behind the coal-cutter at 10m along the wind direction and the dust concentration is largest behind the coal-cutter at 30m along the wind direction. The proportion of PM2.5 in every roadway is analyzed and the proportion of PM2.5 in the intake entry is highest. To get the dynamic distribution law, the numerical model which is similar to virtual condition is estab-lished and the results show that PM 2.5 is mainly fo-cused at the upper right area and the dust concentra-tion at machine area is larger than the sideway, so the key area of controlling PM 2.5 is gotten. At last, the controlling measures of PM 2.5 are gotten through analyzing the distribution law of PM 2.5in coal mine workface and provide basis and methods for reducing the concentration of PM 2.5.

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