Vol. 7(4) April 2014
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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