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

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.

Study of Dynamic Coordinates Time Function in Mine Subsidence

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.

scholarly journals Time Function Model of Surface Subsidence Based on Inversion Analysis in Deep Soil Strata

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Jihuan Han ◽  
Chenchen Hu ◽  
Jiuqun Zou
Keyword(s):  
Soil Surface ◽  
Measured Data ◽  
Surface Subsidence ◽  
Time Function ◽  
Model Parameters ◽  
Deep Soil ◽  
Function Model ◽  
Composite Function ◽  
Inversion Analysis ◽  
Function Models

As a common geological disaster, surface subsidence caused by mining underground resources has always been a hot and difficult topic in the civil engineering field. Aimed at the shortcomings of existing time function models in predicting mining subsidence in deep soil strata, a more accurate and reasonable time function model, called the composite function model, was established based on an inverted analysis of measured data. The results showed that the composite function model could describe the whole subsidence process of a deep soil surface and agreed well with the measured data. The model parameters were calculated by specific formulas, which improved the reliability of the subsidence prediction results under different mining conditions. The new model provided important guiding significance for preventing subsidence geological disasters and determining the coal mining time under the buildings, the railways, and the water bodies in deep soil strata.

Three Dimensional Mapping of Ground Deformation Disasters Caused by Underground Coal Mining

2012 ◽  
Vol 524-527 ◽  
pp. 503-507
Author(s):  
Zhao Hui Liu ◽  
Li Cui ◽  
Tao Zhang ◽  
Qiang Liu ◽  
Er Yang Chen ◽  
...  
Keyword(s):  
Land Reclamation ◽  
Underground Mining ◽  
Ground Deformation ◽  
Three Dimensional ◽  
Google Earth ◽  
Surface Subsidence ◽  
Mining Subsidence ◽  
Ground Subsidence ◽  
Three Dimensional Mapping ◽  
Probability Integral Method

The ground subsidence and deformations caused by underground mining not only affect people’s life tremendously, but also ruin the local eco-environment. These phenomenons (disasters) should be controlled and rehabilitated. For this purpose, in this paper, the characteristic and values of surface subsidence, deformation and movements were evaluated and calculated using some kinds of technological theories and methodology such as probability integral method and so on. Based on the Google Earth image and digital relief maps as well as the predicted results and data, several types of 3D thematic maps of mining subsidence and deformation were designed and mapped in order to carry on the land reclamation or rehabilitation in the mining subsidence and deformation areas. The research results can be fitted well with the reality of surface subsidence and deformations.

Key Technology of Predicting Dynamic Surface Subsidence Based on Knothe Time Function

2011 ◽  
Vol 6 (7) ◽  
Author(s):  
Qing-Feng Hu ◽  
Xi-Min Cui ◽  
Guo Wang ◽  
Meng-Ru Wang ◽  
Yin-Xiao Ji ◽  
...  
Keyword(s):  
Surface Subsidence ◽  
Time Function ◽  
Dynamic Surface ◽  
Key Technology

scholarly journals A New Dynamic Prediction Model for Underground Mining Subsidence Based on Inverse Function of Unstable Creep

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hua Cheng ◽  
Liangliang Zhang ◽  
Longhui Guo ◽  
Xiaojian Wang ◽  
Shilong Peng
Keyword(s):  
Analogical Reasoning ◽  
Underground Mining ◽  
Inverse Function ◽  
Empirical Method ◽  
Creep Model ◽  
Model Parameters ◽  
Subsidence Basin ◽  
Fitting Method ◽  
Relative Standard ◽  
Improved Model

In this study, an improved Knothe time function model is established via analogical reasoning from a phenomenological perspective, based on an inverse “Hohai creep model” function, in accordance with the antisymmetric relationship between the unstable creep curve and surface dynamic subsidence curve. An empirical method and fitting method are proposed to determine the parameters of the improved model based on the availability of measured field data. The accuracies of the two models are compared with monitored data from eight monitoring points in the main strike profile of the Guotun coal mine subsidence basin. The results show that the improved model can more accurately reflect the dynamic process of surface subsidence. The average relative standard deviation of the improved model is only 4.9%, which is far lower than the 23.1% associated with the Knothe model. This verifies the improved model’s accuracy and reliability. The model parameters for different monitoring stations obtained using the fitting method are similar, which shows that the model parameters are regular and can be easily applied.

Modeling of Surface Subsidence Based on Time Function

2011 ◽  
Vol 422 ◽  
pp. 318-321 ◽  
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

Dynamic Modeling of Surface Subsidence Induced by Underground Mining

2011 ◽  
Vol 382 ◽  
pp. 323-327 ◽  
Author(s):  
Hao Liang Han ◽  
Nai Lian Hu ◽  
Bo Cui
Keyword(s):  
Dynamic Modeling ◽  
Underground Mining ◽  
Surface Subsidence ◽  
Time Function ◽  
Dynamic Mode ◽  
Subsidence Basin ◽  
Iron Mine ◽  
Section Function ◽  
New Time

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

scholarly journals Lidar arc scan uncertainty reduction through scanning geometry optimization

2016 ◽  
Vol 9 (4) ◽  
pp. 1653-1669 ◽  
Author(s):  
Hui Wang ◽  
Rebecca J. Barthelmie ◽  
Sara C. Pryor ◽  
Gareth. Brown
Keyword(s):  
Theoretical Model ◽  
Wind Speed ◽  
Wind Energy ◽  
Turbulence Intensity ◽  
Wind Direction ◽  
Energy Production ◽  
Elevation Angle ◽  
Relative Standard Error ◽  
Power Performance ◽  
Relative Standard

Abstract. Doppler lidars are frequently operated in a mode referred to as arc scans, wherein the lidar beam scans across a sector with a fixed elevation angle and the resulting measurements are used to derive an estimate of the n minute horizontal mean wind velocity (speed and direction). Previous studies have shown that the uncertainty in the measured wind speed originates from turbulent wind fluctuations and depends on the scan geometry (the arc span and the arc orientation). This paper is designed to provide guidance on optimal scan geometries for two key applications in the wind energy industry: wind turbine power performance analysis and annual energy production prediction. We present a quantitative analysis of the retrieved wind speed uncertainty derived using a theoretical model with the assumption of isotropic and frozen turbulence, and observations from three sites that are onshore with flat terrain, onshore with complex terrain and offshore, respectively. The results from both the theoretical model and observations show that the uncertainty is scaled with the turbulence intensity such that the relative standard error on the 10 min mean wind speed is about 30 % of the turbulence intensity. The uncertainty in both retrieved wind speeds and derived wind energy production estimates can be reduced by aligning lidar beams with the dominant wind direction, increasing the arc span and lowering the number of beams per arc scan. Large arc spans should be used at sites with high turbulence intensity and/or large wind direction variation.

scholarly journals Population Pharmacokinetics of Fluconazole in Young Infants

2008 ◽  
Vol 52 (11) ◽  
pp. 4043-4049 ◽  
Author(s):  
K. C. Wade ◽  
D. Wu ◽  
D. A. Kaufman ◽  
R. M. Ward ◽  
D. K. Benjamin ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Compartment Model ◽  
Volume Of Distribution ◽  
Relative Standard Error ◽  
Data Set ◽  
Mixed Effect ◽  
Young Infants ◽  
Relative Standard ◽  
Population Pk ◽  
The Impact

ABSTRACT Fluconazole is being increasingly used to prevent and treat invasive candidiasis in neonates, yet dosing is largely empirical due to the lack of adequate pharmacokinetic (PK) data. We performed a multicenter population PK study of fluconazole in 23- to 40-week-gestation infants less than 120 days of age. We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm. Covariate effects were predefined and evaluated based on estimation precision and clinical significance. We studied fluconazole PK in 55 infants who at enrollment had a median (range) weight of 1.02 (0.440 to 7.125) kg, a gestational age at birth (BGA) of 26 (23 to 40) weeks, and a postnatal age (PNA) of 2.3 (0.14 to 12.6) weeks. The final data set contained 357 samples; 217/357 (61%) were collected prospectively at prespecified time intervals, and 140/357 (39%) were scavenged from discarded clinical specimens. Fluconazole population PK was best described by a one-compartment model with covariates normalized to median values. The population mean clearance (CL) can be derived for this population by the equation CL (liter/h) equals 0.015 · (weight/1)0.75 · (BGA/26)1.739 · (PNA/2)0.237 · serum creatinine (SCRT)−4.896 (when SCRT is >1.0 mg/dl), and using a volume of distribution (V) (liter) of 1.024 · (weight/1). The relative standard error around the fixed effects point estimates ranged from 3 to 24%. CL doubles between birth and 28 days of age from 0.008 to 0.016 and from 0.010 to 0.022 liter/kg/h for typical 24- and 32-week-gestation infants, respectively. This population PK model of fluconazole discriminated the impact of BGA, PNA, and creatinine on drug CL. Our data suggest that dosing in young infants will require adjustment for BGA and PNA to achieve targeted systemic drug exposures.

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