Interpretation of variability of rock mass rating by geostatistical analysis: a case study in Western Turkey

Ozturk, H.; Erkayaoğlu, Mustafa

doi:10.1007/s12517-018-3696-y

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…In the past, many rock mass classification systems have been proposed and used to evaluate and classify rock mass, such as the Q system, RQD index, rock mass rating (RMR) method, geological strength index (GSI) method, and R mi system. 30,31 The GSI could be estimated from rock mass descriptions by field observations and provides a complete set of mechanical properties using the generalized Hoek-Brown failure criterion. 32 The generalized Hoek-Brown failure criterion is expressed as:…”

Section: Rock Mass Materials Propertiesmentioning

confidence: 99%

A numerical study of the mining‐induced energy redistribution in a coal seam adjacent to an extracted coal panel during longwall face mining: A case study

Wang

Qiu

Ning

et al. 2019

Energy Science & Engineering

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Mining of the coal seam adjacent to the extracted coal panel is widely practiced in China to improve coal resource recovery rates, but the energy change associated with longwall mining may present a new risk to ground stability and gateroad failure. To understand the energy change effectively, a meticulously validated numerical model, built using FLAC3D software, incorporating a double‐yield model for the gob materials and a strain‐softening model for the coal/rock masses, was developed to investigate the energy redistribution in coal seams and barrier pillars during the process of mining the coal seam adjacent to the extracted coal panel. The model results showed that the closer the region was to the LW 5301 gob, the higher the location and magnitude of the peak strain energy density. Consequently, the risk of rockburst in coal seams was greater than that in barrier pillars. Along the coal seam strike, with increasing advancing distance from the setup room, the magnitude of the peak strain energy density gradually increased to 1.88‐2.78 times the premining energy level. In addition, along the coal seam dip, the maximum distance from the peak strain energy density to the edge of the coal seam was approximately 16‐28 m, which is greater than that in the barrier pillar. The proposed numerical simulation procedure and calibrated method could be a viable alternative approach to evaluate longwall mining‐induced energy changes.

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Section: Rock Mass Materials Propertiesmentioning

confidence: 99%

A numerical study of the mining‐induced energy redistribution in a coal seam adjacent to an extracted coal panel during longwall face mining: A case study

Wang

Qiu

Ning

et al. 2019

Energy Science & Engineering

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“…e methods include deterministic spatial interpolations (e.g., inverse distance weighting), geostatistical interpolations (e.g., ordinary kriging), and geostatistical simulations (e.g., sequential Gaussian simulation) [8,11]. e deterministic method is distance-based and an exact estimator unable to consider orientations, trends, and anisotropy in the dataset [12]. e weights selected for the deterministic spatial interpolation are local and arbitrary with the primary goal of interpolation (i.e., error minimization).…”

Section: Introductionmentioning

confidence: 99%

Geostatistics and Artificial Intelligence Applications for Spatial Evaluation of Bearing Capacity after Dynamic Compaction

Ewusi-Wilson

Park

Yoon

et al. 2022

Advances in Civil Engineering

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This study employs geostatistical and artificial intelligence (AI) methods to estimate the degree of ground improvement after dynamic compaction. We implement artificial neural network (ANN) and random forest (RF) for artificial intelligence spatial interpolation to investigate the efficiency of dynamic compaction considering the spatial distribution of the geotechnical parameters. Data used in this study involve averaged SPT N value before dynamic compaction (Nbefore), averaged SPT N value after dynamic compaction (Nafter), applied energy (AE), X- and Y-coordinates at each borehole location, and degree of ground improvement (DI). This study uses the data obtained from a total of 42 borehole logs with an average depth of 17 m and testing depth intervals of 1.5 m after dynamic compaction and 26 SPT-N log data before dynamic compaction. An optimal spatial interpolation tool selected in this study develops a bearing capacity map after dynamic compaction. The model performance is examined using the correlations between SPT-based and predicted bearing capacity in the context of mean absolute error (MAE), coefficient of determination (r2), and root mean square error (RMSE). The model with the least MAE and RMSE and the highest r2 is selected as optimal. The optimal RF (RFVD) model has an RMSE of 15.83 while out of the two geostatistical models considered OK recorded the lower RMSE of 22.62. Results show that RF spatial interpolation techniques outperform traditional geostatistical methods. The artificial neural network model shows good compatibility with physical and intuitive processes pertinent to dynamic compaction. The ANN resulted in a prediction RMSE of 0.11 for DI and an r2 of 0.97. This unique approach for evaluating the efficiency of dynamic compaction will be useful to geotechnical engineers when designing site improvement projects, especially dynamic compaction by employing easily obtainable field data for coarse-grained soils.

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Method for the Interpretation of RMR Variability Using Gaussian Simulation to Reduce the Uncertainty in Estimations of Geomechanical Models of Underground Mines

Rodriguez-Vilca¹,

Paucar-Vilcañaupa²,

Pehovaz-Alvarez³

et al. 2020

Advances in Intelligent Systems and Computing

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Interpretation of variability of rock mass rating by geostatistical analysis: a case study in Western Turkey

Cited by 5 publications

References 20 publications

A numerical study of the mining‐induced energy redistribution in a coal seam adjacent to an extracted coal panel during longwall face mining: A case study

A numerical study of the mining‐induced energy redistribution in a coal seam adjacent to an extracted coal panel during longwall face mining: A case study

Geostatistics and Artificial Intelligence Applications for Spatial Evaluation of Bearing Capacity after Dynamic Compaction

Method for the Interpretation of RMR Variability Using Gaussian Simulation to Reduce the Uncertainty in Estimations of Geomechanical Models of Underground Mines

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