Dynamic Modeling of Surface Subsidence Induced by Underground Mining

A new time function was proposed to cover the disadvantage of knothe time function in predicting surface subsidence by adding parameter k. The velocity and acceleration of the progressive surface subsidence obtained from this new time function were compared with actual subsidence data from an iron mine in China. Combining this new time function with section function of surface subsidence basin, a dynamic mode was proposed to predict surface subsidence induced by underground mining and a case study based on this model was carried out. It shows that this model accurately represents the actual subsidence pattern observed. Instruction

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Modeling of Surface Subsidence Based on Time Function

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.422.318 ◽

2011 ◽

Vol 422 ◽

pp. 318-321 ◽

Cited By ~ 1

Author(s):

Hao Liang Han ◽

Bo Cui

Keyword(s):

Dynamic Model ◽

Dynamic Process ◽

Underground Mining ◽

Surface Subsidence ◽

Time Function ◽

Subsidence Basin ◽

Section Function ◽

New Time

Base on Knothe time function, a new time function was proposed by adding parameter which is approved more accurate in predicting surface subsidence than Knothe funciton. Combing this new time function with section function of surface subsidence basin, a dynamic model is proposed to predict surface subsidence induced by underground mining and a case study based on this model was carried out. The results illustrates this model is more accurate to reflect the dynamic process of surface subsidence

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Study of Dynamic Coordinates Time Function in Mine Subsidence

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.594-597.56 ◽

2012 ◽

Vol 594-597 ◽

pp. 56-60

Author(s):

Ying Guo ◽

Guang Yi Zhu ◽

Xin Liang Jiang ◽

Ming Dou

Keyword(s):

Dynamic Process ◽

Underground Mining ◽

Surface Subsidence ◽

Time Function ◽

Calculation Methods ◽

Ground Displacement ◽

Mining Design ◽

Dynamic Time ◽

Reflecting Surface ◽

Surface Dynamic

According to hot research of subsidence time function at home and abroad in recent years that there are commonness of less parameters and difficult to extended reflecting surface subsidence characteristics in the dynamic process, the surface subsidence dynamic coordinates time function were proposed based on the probability integration principle, established the calculation methods of surface dynamic process, anal sized the applicability and limitations of the dynamic time function and verified some examples. The results show that the function is more accurate than the Knothe time function in analyzing the actual regularity of surface subsidence caused by underground mining, reflecting the dynamic characteristics of surface movement in real time, interoperating mining phenomenon, it is more accurate to predict dynamic ground displacement and deformation which has a certain significance value in mining design and subsidence disaster management.

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Numerical Modeling of Soil-Pipeline Interaction Mechanism Caused by Surface Subsidence due to Longwall Mining

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.838-841.2202 ◽

2013 ◽

Vol 838-841 ◽

pp. 2202-2207

Author(s):

Guo Ming Cheng ◽

Wen Jie Xu ◽

Hong Bin Chu

Keyword(s):

Numerical Modeling ◽

Cross Sections ◽

Longwall Mining ◽

Measurement Data ◽

Interaction Mechanism ◽

Surface Subsidence ◽

Face Advance ◽

Subsidence Basin ◽

The Face

In China, Surface subsidence caused by underground coal mining has affected the safe operation of pipelines in recent years. Take the coal mine in Shanxi section of the west-east gas pipeline as case study, numerical modeling was adopted to study the interaction mechanism of the soil-pipeline caused by longwall mining, and the numerical model was calibrated with the measurement data. The results reveal that the soil-pipeline interaction undergoes an evolution process from synchronization to separation during the subsidence process. The peak stresses on the pipeline at cross-sections occur generally above the centre of the corresponding subsidence basins at different stages of face advance, and the maximum stress on the pipeline appeared at about 150m above the centre of the subsidence basin as the face advances 300m.

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Application of the Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence: A Case Study from Heze City, Shandong Province, China

Applied Sciences ◽

10.3390/app10093147 ◽

2020 ◽

Vol 10 (9) ◽

pp. 3147

Author(s):

Liangliang Zhang ◽

Hua Cheng ◽

Zhishu Yao ◽

Xiaojian Wang

Keyword(s):

Underground Mining ◽

Shandong Province ◽

Surface Subsidence ◽

Time Function ◽

Relative Standard Error ◽

Function Model ◽

Dynamic Surface ◽

Probability Integral Method ◽

Relative Standard ◽

Improved Model

Taking into account the inadequacy of the Knothe time function model to predict the dynamic surface subsidence caused by underground mining, a new hypothesis is proposed, and the improved Knothe time function model is established. Theoretical analysis shows the improved model agrees well with surface subsidence dynamic change, velocity change, and acceleration change rules. Combined with field measured data, the probability integral method, dual-medium method, and least square method are adopted to determine the time influence parameter C and the model order n. Based on monitoring data from four monitoring stations in the Guotun coal mine subsidence basin strike main profile from Heze city, Shandong Province, China, the accuracies of the Knothe time function and improved model are compared and analyzed. Results show the improved model can accurately describe the dynamic surface subsidence process and subsidence velocity with mining time. The average relative standard error between the predicted and measured values is only 4.8%—far lower than the Knothe time function model is 23%, verifying the improved model’s accuracy and reliability.

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A Model to Predict Crosscut Stress Based on an Improved Extreme Learning Machine Algorithm

Energies ◽

10.3390/en12050896 ◽

2019 ◽

Vol 12 (5) ◽

pp. 896 ◽

Cited By ~ 2

Author(s):

Xiaobo Liu ◽

Lei Yang ◽

Xingfan Zhang ◽

Liancheng Wang

Keyword(s):

Extreme Learning Machine ◽

Underground Mining ◽

Liaoning Province ◽

Stress Monitoring ◽

Network Algorithms ◽

Iron Mine ◽

Time In Literature ◽

Learning Machine ◽

First Time

The analysis of crosscut stability is an indispensable task in underground mining activities. Crosscut instabilities usually cause geological disasters and delay of the project. On site, mining engineers analyze and predict the crosscut condition by monitoring its convergence and stress; however, stress monitoring is time-consuming and expensive. In this study, we propose an improved extreme learning machine (ELM) algorithm to predict crosscut’s stress based on convergence data, for the first time in literature. The performance of the proposed technique is validated using a crosscut response by means of the FLAC3D finite difference program. It is found that the improved ELM algorithm performs higher generalization performance compared to traditional ELM, as it eliminates the random selection for input weights. Furthermore, a crosscut construction project in an underground mine, Yanqianshan iron mine, located in Liaoning Province (China), is selected as the case study. The accuracy and efficiency of the improved ELM algorithm has been demonstrated by comparing predicted stress data to measured data on site. Additionally, a comparison is conducted between the improved ELM algorithm and other commonly used artificial neural network algorithms.

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Water inrush characteristics and hazard effects during the transition from open-pit to underground mining: a case study

Royal Society Open Science ◽

10.1098/rsos.181402 ◽

2019 ◽

Vol 6 (3) ◽

pp. 181402

Author(s):

Huijie Zhang ◽

Bin Zhang ◽

Nengxiong Xu ◽

Lei Shi ◽

Hanxun Wang ◽

...

Keyword(s):

Mine Water ◽

Underground Mining ◽

Water Inrush ◽

Mine Safety ◽

Liaoning Province ◽

Open Pit ◽

Comprehensive Method ◽

Iron Mine ◽

Mine Roadway

During the transition from open-pit to underground mining in iron ore mines, water inrush is a prominent problem for mine safety and production. In this paper, a comprehensive method that incorporates hydrochemical analysis and numerical simulation is proposed to analyse the characteristics of water inrush during the transition from open-pit to underground mining. The proposed method revealed the migration law of groundwater and analysed the source of mine water inrush in the Yanqianshan iron mine located in Liaoning province, China. The results show that the excavated mine roadway is the primary factor affecting groundwater migration and that the source of the mine water inrush is the groundwater in the aquifer around the mine roadway. Moreover, based on the results of the study, appropriate methods for prevention and treatment of mine water inrush were proposed. This approach provides a novel idea for the assessment of water inrush hazards and will serve as a valuable reference for analogous engineering cases.

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