Prediction of Longwall Progressive Subsidence Basin Using the Gompertz Time Function

Wang, Jian; Yang, Keming; Wei, Xiangping; Shi, Xiaoyu; Yao, Shuyi

doi:10.1007/s00603-021-02664-z

Cited by 10 publications

(10 citation statements)

References 20 publications

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“…When b is taken as 2, with the increase of a , the slope of the time function curve in the initial period is faster, the time taken for the function value to reach the convergence value 1 is shorter, and when combined with the theory of mining subsidence, it can be seen that the ground point ends the moment of mobile deformation earlier . When a takes 0.05, it is found that the parameter b only controls the path of movement of the function curve and the time used for the function value to reach the final convergence value is basically unchanged, and the larger the parameter b , the later the deformation point reaches the maximum sinking speed …”

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

“…The time function is time as the independent variable of the dimensionless function; the value of the domain can traverse the [0,1] interval, and it controls the function of the curve shape and change characteristics through the relevant parameters . If the time function is used, φ( t ), the maximum deformation value at a point of the pit is S max , the settlement at that point at a certain time is the product of and, obviously, determines the convergence value of the settlement curve but cannot affect the trend of the settlement curve . In this paper, the Adjusted-Logistic time function model is established on the basis of the two parameters of the Logistic time function model, and the parameter a, which adjusts the symmetry of the function curve, is introduced, and the model expression is where S max is the maximum settlement value of the surface; a , b , and c denote the time influence parameters related to the overburden lithology; and t is the time parameter in days.…”

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

“…27 If the time function is used, φ(t), the maximum deformation value at a point of the pit is S max , the settlement at that point at a certain time is the product of and, obviously, determines the convergence value of the settlement curve but cannot affect the trend of the settlement curve. 28 In this paper, the Adjusted-Logistic time function model is established on the basis of the two parameters of the Logistic time function model, and the parameter a, which adjusts the symmetry of the function curve, is introduced, and the model expression is…”

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

“… 33 When a takes 0.05, it is found that the parameter b only controls the path of movement of the function curve and the time used for the function value to reach the final convergence value is basically unchanged, and the larger the parameter b , the later the deformation point reaches the maximum sinking speed. 34 …”

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

See 3 more Smart Citations

Monitoring and Prediction of Horizontal Displacement of Underground Enclosure Piles in Subway Foundation Pits

et al. 2023

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Urban rail transportation and underground space development and utilization are initiatives to solve urban traffic congestion. The monitoring and prediction of the stability of underground enclosure piles in foundation pits is a key index for the dynamic evaluation of the stability of underground space engineering. In this paper, we focused on the problem that the dynamic prediction accuracy and stability of foundation pit retaining piles in the Qingdao area are not high. Based on the analysis of various time function curves and the physical meaning of the parameters, we proposed the Adjusted-Logistic time function model, which introduces three physical parameters to adjust the deformation velocity and deformation acceleration in different stages for better accuracy. It could predict the deformation process of underground enclosure piles under different geological engineering conditions. It was verified in the field that the root-mean-square error (RMSE) of the Adjusted-Logistic function was 0.5316, MAE was 0.3752, and R 2 was 0.9937, which were better than those of Gompertz, Weibull, and Knothe time function models. Meanwhile, it showed that with the increase of excavation depth, the maximum horizontal displacement of the underground enclosure piles gradually decreased and finally stabilized at 0.62−0.71 H. We established a catastrophe model of the horizontal displacement cusp at the observation point of the underground enclosure piles by using the time series of the measured data. It could determine the weak location of the underground enclosure pile stability and realize the multipoint warning of the foundation pit stability, which would ensure safe construction.

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Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

Section: Improved Dynamic Prediction Functionmentioning

confidence: 99%

See 2 more Smart Citations

Monitoring and Prediction of Horizontal Displacement of Underground Enclosure Piles in Subway Foundation Pits

et al. 2023

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“…Zhang et al established an improved Knothe time function model, which accurately predicted surface subsidence caused by underground mining [12] . Wang et al identified the defects in the improved Knothe time function and provided a more accurate dynamic prediction model of mining surface deformation [13] . Marian et al used the influence function method to predict the degree of mining-induced subsidence [14] .…”

Section: Introductionmentioning

confidence: 99%

Prediction of surface subsidence in Gequan coal mine based on probability integral and numerical simulation

2024

AJETS

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The goaf produced by underground mining will produce subsidence on the surface, which will threat to the overlying buildings. In order to study surface subsidence, probability integral method and FLAC3D numerical simulation method were adopted to simulate and predict the coal seam mining in Gequan Mine. The results showed that the subsidence decreased gradually from the center of the goaf to both ends, from the underlying strata to the surface, and the result of probability integral calculation was slightly larger than that of numerical simulation. However, in the case of fully considering complex strata and insufficient mining, numerical simulation can better reflect the real situation in the mining surface subsidence of Gequan Mine, which has good reference significance.

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Evaluation of Surface Subsidence Due to Inclined Coal Seam Mining: a Case Study in the 1930 Coal Mine, China

et al. 2022

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Prediction of Longwall Progressive Subsidence Basin Using the Gompertz Time Function

Cited by 10 publications

References 20 publications

Monitoring and Prediction of Horizontal Displacement of Underground Enclosure Piles in Subway Foundation Pits

Monitoring and Prediction of Horizontal Displacement of Underground Enclosure Piles in Subway Foundation Pits

Prediction of surface subsidence in Gequan coal mine based on probability integral and numerical simulation

Evaluation of Surface Subsidence Due to Inclined Coal Seam Mining: a Case Study in the 1930 Coal Mine, China

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