Comprehensive study on identification of water inrush sources from deep mining roadway

2021 ◽  
Author(s):  
Yang Chen ◽  
Liansheng Tang ◽  
Shuyun Zhu
Keyword(s):  
Water Inrush ◽  
Deep Mining ◽  
Comprehensive Study

scholarly journals Analysis of Key Factors Affecting Water Disaster in Deep Mining and Establishment of a Water Disaster Evaluation Method Suitable for Different Mining Depths

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jianghui He ◽  
Wenping Li ◽  
Wei Qiao ◽  
Zhi Yang ◽  
Qiqing Wang
Keyword(s):  
Water Inrush ◽  
Assessment Method ◽  
New Method ◽  
Specific Yield ◽  
Water Yield ◽  
Deep Mining ◽  
Hydrogeological Characteristics ◽  
Formula Method ◽  
Water Disaster

Deep mining is the current and future mining focus in the coalfield of North China. Therefore, it is necessary to establish a water inrush assessment method suitable for deep mining. The conventional water inrush coefficient ( T ) method is simple to use, but its accuracy is low when the mining depth is very small or large because it neglects the role of the aquifer water yield. The main purpose of this paper is to introduce a simple water inrush risk assessment method that is more applicable in deep mining than the T method. In this study, the hydrogeological characteristics in deep mining were studied and the role of the aquifer water yield in water inrush was analyzed. Afterwards, an improved T method considering the aquifer specific yield ( q ) was established. In the new method, the critical water inrush coefficient changes with changing q following a negative correlation. The parameter thresholds were determined based on systematic data analyses of 186 mining cases. The results of the statistical analysis show that the accuracy of the new method at different mining depths is higher than that of the T method.

scholarly journals Gray Evaluation of Water Inrush Risk in Deep Mining Floor

ACS Omega ◽  
2021 ◽  
Author(s):  
Xingyue Qu ◽  
Xiaoge Yu ◽  
Xingwei Qu ◽  
Mei Qiu ◽  
Weifu Gao
Keyword(s):  
Water Inrush ◽  
Deep Mining

Comprehensive Assessment of Water Inrush Risk in Deep Mining of Beiminghe Iron Mine

2011 ◽  
Vol 261-263 ◽  
pp. 1348-1354
Author(s):  
Chang Hong Li ◽  
Li Xin Zhang
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Water Pressure ◽  
Water Inrush ◽  
Fuzzy Comprehensive Evaluation ◽  
Mathematic Model ◽  
Test Field ◽  
Deep Mining ◽  
Hydrogeological Characteristics ◽  
Iron Mine

In view of one-sidedness and the limitations in comprehensive evaluation index for water inrush risk, a variety of factors of water inrush induced by deep mining of Beiminghe iron mine are analyzed from hydrogeological characteristics, structural characteristics and mining. Faulted structure, water storage capacity, water pressure, water-resisting layer, miming effect and the change of stress in surrounding rock of two levels of deep mining in mine area are quantized by rock permeability test, field pumping test and finite element numerical analysis. Mathematic model of risk assessment of water inrush in deep mining of Beiminghe iron mine is established by using fuzzy comprehensive evaluation method. Quantitative assessment of water inrush risk is carried out to obtain the value of rank tendency for water inrush risk through that mathematic model.

Mechanical Model on Water Inrush Assessment Related to Deep Mining Above Multiple Aquifers

2019 ◽  
Vol 38 (4) ◽  
pp. 827-836 ◽  
Author(s):  
Liming Yin ◽  
Kai Ma ◽  
Juntao Chen ◽  
Yanchao Xue ◽  
Ziqi Wang ◽  
...  
Keyword(s):  
Mechanical Model ◽  
Water Inrush ◽  
Deep Mining ◽  
Multiple Aquifers

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Sign in / Sign up

Export Citation Format

Share Document