Geophysical Monitoring of Underground Constructions and its Theoretical Basis

Ezersky, M.; Eppelbaum, Lev

doi:10.15273/ijge.2017.03.007

Cited by 7 publications

(5 citation statements)

References 14 publications

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“…The project consists of eight hydroelectric generators with a total capacity of 1920 MW, and they were located in the underground of an effusive rock hill, which can suffer from seismic and earthquakes up to Level 8 (Ezersky & Eppelbaum, 2017; Ezerskii et al., 1990). In the first period of the operation, the electricity production accounted for about 40% of the total production in Vietnam, and during the last 26 years, this project has produced about 230 billion kWh.…”

Section: Case Studymentioning

confidence: 99%

Deformation forecasting of a hydropower dam by hybridizing a long short‐term memory deep learning network with the coronavirus optimization algorithm

Bui

Torres

Gutiérrez‐Avilés

et al. 2022

Computer aided Civil Eng

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The safety operation and management of hydropower dam play a critical role in social-economic development and ensure people's safety in many countries; therefore, modeling and forecasting the hydropower dam's deformations with high accuracy is crucial. This research aims to propose and validate a new model based on deep learning long short-term memory (LSTM) and the coronavirus optimization algorithm (CVOA), named CVOA-LSTM, for forecasting the deformations of the hydropower dam. The second-largest hydropower dam of Vietnam, located in the Hoa Binh province, is focused. Herein, we used the LSTM to establish the deformation model, whereas the CVOA was utilized to optimize the three parameters of the LSTM, the number of hidden layers, the learning rate, and the dropout. The efficacy of the proposed CVOA-LSTM model is assessed by comparing its forecasting performance with state-of-the-art benchmarks, sequential minimal optimization for support vector regression, Gaussian process, M5' model tree, multilayer perceptron neural network, reduced error pruning tree, random tree, random forest, and radial basis function neural network. The result shows that the proposed CVOA-LSTM model has high forecasting capability (R 2 = 0.874, root mean square error = 0.34, mean absolute error = 0.23) and outperforms the benchmarks. We conclude that CVOA-LSTM is a new tool that can be considered to forecast the hydropower dam's deformations.

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Section: Case Studymentioning

confidence: 99%

Deformation forecasting of a hydropower dam by hybridizing a long short‐term memory deep learning network with the coronavirus optimization algorithm

Bui

Torres

Gutiérrez‐Avilés

et al. 2022

Computer aided Civil Eng

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“…A feature of the EMR field recorded in underground workings using the Angel equipment is that in most cases the registration is carried out under conditions of natural and man-made interference and in the so-called nearest zone of the radiation source, which extends from the source to a distance of up to three wavelengths. A direct analogy here is acoustic emission (AE) technology, a method that has long been used for geophysical monitoring of underground structures [30], as well as sound metering in the form of seismic tomography when monitoring underground structures with a signal generated by a tunnel boring machine [31].…”

Section: Other Possible Causes Of Emr Cyclingmentioning

confidence: 99%

Integrated Interpretation of the Results of Long-Term Geotechnical Monitoring in Underground Tunnels Using the Electromagnetic Radiation Method

et al. 2022

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Electromagnetic radiation (EMR) technology makes it possible to evaluate changes in the stress-strain state (SSS) in the “tunnel lining-enclosing rock mass” system at a high level of interference, and to create schemes of long-term EMR control in tunnels (geotechnical monitoring systems). The issues of the variations in EMR signals are extremely important for monitoring systems: based on anomalous deviations from the normal regime one can draw conclusions about changes in the SSS, leading to geodynamic phenomena (e.g., rock bursts). This article presents data obtained during laboratory studies on samples and field studies in transport tunnels. Also, some results of long-term geotechnical monitoring by a set of methods is presented: EMR and tensometry of the tunnel lining, both methods are in the automatic mode. The ability of an EMR control system to respond to earthquakes affecting tunnel structures is shown. An analysis of long-term EMR studies was conducted, which showed the periodic oscillation of the “tunnel lining-enclosing rock mass” system. In a stable compressed state, minima of EMR pulses are recorded; when the rock mass and lining material are stretched, charges are separated on the edges of micro-defects and EMR increases; complete separation of the edges of micro-defects leads to the termination of intense EMR. The same occurs in the opposite direction during the compression of micro-defects and micro-fractures in the rock mass and concrete lining. The periods of compression and expansion are closely related to temperature fluctuations. The results differ in detail and, therefore, in to be more confident, additional studies are needed in various host rock massifs and types of tunnel lining.

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“…In June 2017, two multipoint extensometers were installed in a chain pillar (one from the entry and one from the cross-cut) and the deformations were subsequently monitored as the longwall face approached and crossed the instrumented location. Extensometers were specifically chosen over other monitoring approaches/equipment, like stress cells (e.g., [42]), tomography (e.g., [43]), and acoustic emissions (e.g., [44]), because extensometers can directly measure ground deformations that are comparable with the model results and are also low-cost and relatively simple to install. Based on a borehole log from the site, a FLAC3D model was developed and calibrated to match the extensometer measurements.…”

Section: Introductionmentioning

confidence: 99%

Application of an Integrated 3D–2D Modeling Approach for Pillar Support Design in a Western US Underground Coal Mine

Sinha,

Walton

2023

Geosciences

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Discontinuum Bonded Block Modeling (BBM) represents a potential tool for support design, as these models can reproduce both the rock fracturing process and the influence of reinforcement on unsupported ground. Despite their strengths, discontinuum models are seldom used for mining design due to their computationally intensive nature. This study is an application of an integrated 3D continuum–2D discontinuum approach, in which the mine-wide stress distribution process is modeled using a continuum software, and the local deformation behavior in response to a strain path from the continuum model is simulated with a 2D discontinuum software. In June 2017, two multi-point borehole extensometers were installed in a longwall chain pillar to record ground displacements as a function of the longwall face position. The data from one of the extensometers were employed to calibrate a panel-scale FLAC3D model. The boundary conditions along the pillar slice containing the extensometer were extracted from the FLAC3D model and applied to a 2D BBM, and the input parameters were modified to match the extensometer data. The calibrated BBM was able to reproduce the unsupported rib deformation and depth of the fracturing well. Subsequently, a few support schemes were tested to demonstrate how the incorporation of support might affect rib deformation.

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Geophysical Monitoring of Underground Constructions and its Theoretical Basis

Cited by 7 publications

References 14 publications

Deformation forecasting of a hydropower dam by hybridizing a long short‐term memory deep learning network with the coronavirus optimization algorithm

Deformation forecasting of a hydropower dam by hybridizing a long short‐term memory deep learning network with the coronavirus optimization algorithm

Integrated Interpretation of the Results of Long-Term Geotechnical Monitoring in Underground Tunnels Using the Electromagnetic Radiation Method

Application of an Integrated 3D–2D Modeling Approach for Pillar Support Design in a Western US Underground Coal Mine

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