Roof fall hazard assessment with the use of artificial neural network

Małkowski, Piotr; Juszyński, D.

doi:10.1016/j.ijrmms.2021.104701

Cited by 26 publications

(8 citation statements)

References 8 publications

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“…Thirdly, depending on the level of geomechanical indexes Н and R influence, these functions U(t) can be divided into two types: first typethe displacements U increase in time t, but with its course there is some stabilization of the process of adjacent mass displacement, at which further growth of U either stops or has very low values (Fig. 3) and the deformation process is caused by the change of geomechanical situation in the rock mass [38], [39]; second typethe displacements U do not stop in time t and later on, some fairly constant growth gradient of U is settled down [31], [40]- [42] (Fig. 4).…”

Section: Basic Research Materialsmentioning

confidence: 99%

“…Alongside with it, the state of the fastening structure elements is assessed in terms of the possibility of further performing their functions to ensure the proper mine working stability [39], [46]. It is appropriate to note here that the main difficulty in solving this task is the need to conduct mine observations over a very long period, often calculated in decades [38]. To solve this issue, an original methodology has been developed, based on an integrated study and analysis of the various information sources and discreteness (in time) of mine measurements with their subsequent extrapolation to a longer time frame.…”

Section: Figure 3 Stabilization Of the Displacement Process In The Mine Working Figure 4 Settling A Constant Gradient Of Displacement Gromentioning

confidence: 99%

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Technical and technological aspects of the coal mine closure based on the geomechanical component assessment

Barabash¹,

Salieiev²,

Symanovych³

2021

Min. miner. depos.

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Purpose.Development of a comprehensive methodology for assessing the state of mine workings based on the analysis of their contour displacement patterns when solving the problem of minimizing the risks during the closure of coal mines in Ukraine. Methods. Based on an integrated analysis of international and domestic trends when assessing the consequences of mine closure, the main provisions of using the method of instrumental mine observations have been substantiated. When solving the problem, the approaches of regulatory documents are taken into account to identify the geomechanical situation according to two conditions: the structure and strength properties of the lithotypes in the adjacent coal-bearing stratum and the peculiarities of the rheological processes manifestation during the development of its displacements. Findings. The geomechanical, technological and hydrogeological factors have been distinguished that are required to take into account when closing the coal mines. Fundamental methodological provisions have been substantiated for the most reliable assessment of the mine workings state, taking into account the long period of their operation. A criterion for making a decision on the decommissioning of mine workings or their further maintenance is presented. Originality.A series of generalizing dependences of the mine working contour displacement development has been obtained, which can be divided into four main groups according to the criteria of the structural and strength properties of lithotypes in the adjacent mass, as well as the type of their rheological manifestations: decaying and persistent deformation creep. For each group, using the methods of correlation-dispersive analysis, empirical formulas have been determined for calculating the convergence of the roof and bottom of mine workings, as well as their sides, depending on the geomechanical criterion H/R of the maintenance conditions and the duration t of this period. Practical implications.The obtained correlation ratios make it possible to predict the residual section of mine working at any time of its maintenance. They are a geomechanical component of its operational state assessment. The result of this research is the development of a new methodology for assessing the mine working state according to the patterns for predicting its contour displacement.

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Section: Basic Research Materialsmentioning

confidence: 99%

Section: Figure 3 Stabilization Of the Displacement Process In The Mine Working Figure 4 Settling A Constant Gradient Of Displacement Gromentioning

confidence: 99%

Technical and technological aspects of the coal mine closure based on the geomechanical component assessment

Barabash¹,

Salieiev²,

Symanovych³

2021

Min. miner. depos.

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“…In this process, the dynamic disturbance suffered by the coal and rock is not negligible [6][7][8]. The dynamic disturbance, such as mining-induced seismicity, blasting, and hydraulic fracturing, propagates outwards in the form of vibrational waves and continuously acts on the coal rock mass and causes damage, especially in areas with high static stresses [9,10]. Therefore, it is of great significance to understand the mechanism of rock burst triggering by understanding the evolution characteristics of rock force and energy and the progressive damage mechanism of rock burst.…”

Section: Introductionmentioning

confidence: 99%

Evolution Laws of Stress–Energy and Progressive Damage Mechanisms of Surrounding Rock Induced by Mining Disturbance

Bai

et al. 2023

Applied Sciences

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The rock burst induced by the mutual disturbance of mining and excavation is significantly influenced by high static load stress and external dynamic load disturbance. In this paper, the evolution characteristics and progressive damage mechanism of surrounding rock in the process of mutual disturbance of mining and excavation are systematically studied. The results show that the evolution of surrounding rock stress can be roughly divided into three stages: rapid rise in the early stage, continuous rise and step-like decline in the middle stage, and slow rise in the late stage. In the process of parallel mining, the overlying rock movement above the goaf shows the sequence of horizontal penetration of tiny fissures—fracture intensification transition to stratification—non-coordinated caving of middle–low overlying rock—obvious horizontal cracks in the upper key layer. Only under the quasi-static loading mining action does the upper key layer not reach the breaking condition. The wave side of the heading face which is close to the focal point is affected by the dynamic load disturbance, the acceleration duration is short, and the attenuation is relatively fast, so it is the area prone to the earliest impact failure in the face of mining disturbance. The conclusion is helpful to deepen the understanding of the coal burst mechanism of mutual disturbance of mining and excavation.

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“…Before rock mechan-ics advancement in India, experienced mining personnel used to predict roof fall when strata started talking to them with admissible accuracy and saved many valuable lives. Artificial Neural Network (ANN) has been used for roof fall hazard assessment (Malkowski and Juszynski, 2021), roof fall hazard detection (Isleyen et al, 2021), predicting roof fall rate by novel fuzzy interface system (Razani et al, 2013), forecasting shield pressures (Deb et al, 2006), pillar stress prediction (Monjezi et al, 2009) and also being used for weather forecasting, voice and image recognition, stock market prediction, health care, driverless vehicle etc.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Model for Prediction of Local and Main FALL in caving Panel of Bord and Pillar Method of Mining

Prajapati

Sinha

Gupta³

et al. 2022

jmmf

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Depillaring with caving method of mining is a common practice in Indian coalfields and so is the occurrence of fall in goaf area, which can be considered as a boon in disguise as it allows wining of coal from large reserves but this becomes a curse just because of its unpredicted occurrence. Various empirical and statistical models are developed after idealization of several complicated mechanisms but they are not able to predict roof fall accurately especially in caving panels. Therefore, a new approach based on Artificial Intelligence is used to predict the sequence of local and main fall in caving panel taking into account a host of geotechnical and mining parameters of the mine. Mathematical equations and hidden calculations of artificial neural networks are known to have the capability of learning and analyzing records endlessly. Two different models have been deployed after optimal hyper parameter optimization to predict the occurrence of fall and to characterize the nature of fall (local or main) with considerable and reliable accuracy.

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Roof fall hazard assessment with the use of artificial neural network

Cited by 26 publications

References 8 publications

Technical and technological aspects of the coal mine closure based on the geomechanical component assessment

Technical and technological aspects of the coal mine closure based on the geomechanical component assessment

Evolution Laws of Stress–Energy and Progressive Damage Mechanisms of Surrounding Rock Induced by Mining Disturbance

Artificial Intelligence Model for Prediction of Local and Main FALL in caving Panel of Bord and Pillar Method of Mining

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