Investigation for probabilistic prediction of shear strength properties of clay-rich fault gouge in the Austrian Alps

In this study, the K-means algorithm based on particle swarm optimization (K-PSO) and game theory are introduced to establish the quality evaluation model of a rock mass. Five evaluation factors were considered, i.e., uniaxial saturated compressive strength of rock, discontinuity spacing, acoustic velocity, rock quality designation (RQD), and integrity coefficient. The rock mass of an elevation adit at the abutment of Maji hydropower station was taken as a case study. The subjective weight of the evaluation factor was determined by the weighted least squares method, and the objective weight of the evaluation factor was determined by the entropy method. The combined weights of each influencing factor were determined by game theory to be 0.142, 0.179, 0.035, 0.116, and 0.108. The rock mass quality evaluation in the study area was analyzed by K-PSO algorithm. The results indicate that the K-PSO clustering results are almost the same as the evaluation results of the traditional basic quality (BQ) classification method and the widely used extension evaluation method and are consistent with the preliminary judgment of the expert field. The results are consistent with the field observation law. It is considered that the K-PSO clustering theory can reflect the engineering geological characteristics of the rock mass of the hydropower project in the rock mass quality evaluation.

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“…. ., P 15 , in order [38][39][40][41][42][43][44]. The rock mass parameters of each section are shown in Table 4.…”

Section: Selection Of Rock Mass Samplesmentioning

confidence: 99%

Application of K-PSO Clustering Algorithm and Game Theory in Rock Mass Quality Evaluation of Maji Hydropower Station

et al. 2023

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“…In recent years, some scholars used doubledirect shear tests to investigate the relationship between frictional strength and fabric characteristics of fault gouge, which indicated that the frictional strength showed a negative correlation with clay content and particle size [7,8]. Liu et al [9] divided the shear strength properties into four types according to their geotechnical parameters and established a probabilistic prediction method for shear strength. Li and Deng [10] studied the mechanical properties of an undisturbed fault gouge in the Longmenshan Fault zone.…”

Section: Introductionmentioning

confidence: 99%

Shear Mechanical Behaviours and Multistrength Parameter Characteristics of Fault Gouge

Bao

Lan

et al. 2019

Advances in Civil Engineering

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Fault gouge has special mechanical properties and remarkable engineering effects. Using a ring shear test, the strength properties of the differently colored remolded fault gouges of the Shendaogou Fault in Yan’an were studied by changing moisture contents and normal stresses. Chlorite and illite are the main clay minerals in fault gouges; differences in mineral composition make fault gouges appear in different colors. Besides clay minerals, the dried fault gouges disintegration in water is also due to the transformation of gypsum. The gradation of green fault gouge and multicolor fault gouge is better than that of the red fault gouge, while the fault gouges’ strain softening properties become weaker as the coarse grain content increases. Affected by water content and normal stress, the shear planes can be divided into three failure modes: peeling failure, grooved failure, and sliding failure. With the increase of water content, there will be a significant weakening on cohesion and friction angle. A new parameter, the “Normal Stress Threshold (NST),” is introduced as a critical value for the emergence of the strain hardening phenomenon, and the NSTs of different fault gouges are significantly different. The functions obtained from the relation of residual strength, peak strength, and normal stress can be used to calculate shear strength parameters under any normal stresses. In addition, the residual strength of fault gouge is obviously different from clay and loess, which can be qualitatively explained by clay particle contents.

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Prediction of the unconfined compressive strength of compacted granular soils by using inference systems

et al. 2008

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Investigation for probabilistic prediction of shear strength properties of clay-rich fault gouge in the Austrian Alps

Cited by 13 publications

References 11 publications

Application of K-PSO Clustering Algorithm and Game Theory in Rock Mass Quality Evaluation of Maji Hydropower Station

Application of K-PSO Clustering Algorithm and Game Theory in Rock Mass Quality Evaluation of Maji Hydropower Station

Shear Mechanical Behaviours and Multistrength Parameter Characteristics of Fault Gouge

Prediction of the unconfined compressive strength of compacted granular soils by using inference systems

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