Mining exploitation influence range

Kwinta, Andrzej; Gradka, Robert

doi:10.1007/s11069-018-3450-5

Cited by 9 publications

(4 citation statements)

References 12 publications

(11 reference statements)

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“…He proved this hypothesis through the physical model of dry sand medium displacement. Similar but more simple version of the solution presented by Knothe (1953) based on coal mine observations in Poland, the solution is accepted by mining companies and different software applications this method (Sroka 2001;Kratzsch 1983;Kwinta, Gradka 2018). Knothe's influence function (Kratzsch 1983):…”

Section: Existing Prediction Methods and Its Limitsmentioning

confidence: 99%

Investigation about the contribution of tectonic conditions to mining subsidence parameters

Babaryka¹,

Benndorf²

2022

Mining Science

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Underground infrastructure of any kind can affect the surface by inducing ground movements. The ability of precise subsidence prediction is crucial for environmental management. Prediction methods in practice are mainly based on influence functions that are symmetrical and provide comparably smooth profiles. In the past, deviations from the predictions have been detected. The ability of modern geomonitoring data makes the deviation even more obvious today. One of the reasons for the deviations are the regional tectonic stress conditions. To justify further investigation into the impact of tectonic conditions on the subsidence parameters, numerical experiments were conducted based on a hypothetical case of a homogenous sedimentary rock under different stress conditions. As a result, deviation of up to 7% of the subsidence profile parameters was detected. The results can be considered significant and encourage researchers to investigate the topic further to extend the currently used prediction methods to take into count the tectonic conditions. The research is based on numerical simulation and provides only theoretical result, implementation and validation of the theory in the field are left for further investigation.

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Section: Existing Prediction Methods and Its Limitsmentioning

confidence: 99%

Investigation about the contribution of tectonic conditions to mining subsidence parameters

Babaryka¹,

Benndorf²

2022

Mining Science

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“…However, there are some types of rocks and industrial minerals that are found in nature with a more abundant distribution. In these cases, the study and analysis of alternative locations for the mining activity within the regional scope can be proposed, according to all the factors of the social, physical, economic, environmental and geographical contexts, to those that are intrinsic to the resource to be exploited, and considering the degree of compatibility of its location with other uses of the natural resources and the existing legislation [21].…”

Section: Methodological Proposal To Redefine the Environmental Criterionmentioning

confidence: 99%

Determination of Environmental Factors for the Implementation of the Exploitability Index in Industrial Aggregate Mining Using Multi-Criteria Analysis

Luis-Ruiz

Salas-Menocal

Fernández-Maroto

et al. 2021

IJGI

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The quality of human life is linked to the exploitation of mining resources. The Exploitability Index (EI) assesses the actual possibilities to enable a mine according to several factors. The environment is one of the most constraining ones, but its analysis is made in a shallow way. This research is focused on its determination, according to a new preliminary methodology that sets the main components of the environmental impact related to the development of an exploitation of industrial minerals and its weighting according to the Analytic Hierarchy Process (AHP). It is applied to the case of the ophitic outcrops in Cantabria (Spain). Twelve components are proposed and weighted with the AHP and an algorithm that allows for assigning a normalized value for the environmental factor to each deposit. Geographic Information Systems (GISs) are applied, allowing us to map a large number of components of the environmental factors. This provides a much more accurate estimation of the environmental factor, with respect to reality, and improves the traditional methodology in a substantial way. It can be established as a methodology for mining spaces planning, but it is suitable for other contexts, and it raises developing the environmental analysis before selecting the outcrop to be exploited.

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“…The Probability Integration Method (PIM), the theory of which was developed by Knothe and functions via Knothe's theory, is one of the influential function methods [27][28][29][30]. The method makes use of the probability integration function as its main function.…”

Section: Introductionmentioning

confidence: 99%

Extraction of Irregularly Shaped Coal Mining Area Induced Ground Subsidence Prediction Based on Probability Integral Method

Tan

Song

et al. 2020

Applied Sciences

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Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation.

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Mining exploitation influence range

Cited by 9 publications

References 12 publications

Investigation about the contribution of tectonic conditions to mining subsidence parameters

Investigation about the contribution of tectonic conditions to mining subsidence parameters

Determination of Environmental Factors for the Implementation of the Exploitability Index in Industrial Aggregate Mining Using Multi-Criteria Analysis

Extraction of Irregularly Shaped Coal Mining Area Induced Ground Subsidence Prediction Based on Probability Integral Method

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