A Qslope-based empirical method to stability assessment of mountain rock slopes in multiple faults zone: A case for North of Tabriz

Kouhdaragh, Mehdi; Azarafza, Mohammad; Derakhshani, Reza

doi:10.1016/j.mex.2022.101718

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Q slope is an empirical method developed for analyzing slope stability based on the Q method [39,40]. The method employs a stability chart, as depicted in Figure 1, which was modified in 2020 by Azarafza et al [43].…”

Section: Q Slope Classification Systemmentioning

confidence: 99%

“…According to Bar and Barton [39], the Qslope number relationship, expressed in Equation (1), encompasses key elements such as the shear force element (Jr/Ja), block size (RQD/Jn), and external loading/stress factor (Jwice/SRFslope). In this equation, RQD represents the "rock quality designation", J n corresponds to the "discontinuity set number", J r denotes the "discontinuity roughness number", J a signifies the "discontinuity alteration number", J wice stands for "environmental and geological condition number", and SRF slope represents the "strength reduction factor" [39][40][41][42][43]. RQD, commonly used worldwide by geoengineers, serves as an indicator of rock mass quality and can be estimated through direct or indirect procedures [1].…”

Section: Qslope Classification Systemmentioning

confidence: 99%

“…Q slope was initially developed based on Barton's Q system, which is widely used to assess the quality of rock mass [40]. While the main Q method is primarily employed for underground structures, Q slope is specifically designed for evaluating slope stability through an engineering discussion-making procedure.…”

Section: Qslope Classification Systemmentioning

confidence: 99%

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Fuzzy-Based Intelligent Model for Rapid Rock Slope Stability Analysis Using Qslope

Mao

Chen²,

Nanehkaran

et al. 2023

Water

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Artificial intelligence (AI) applications have introduced transformative possibilities within geohazard analysis, particularly concerning the assessment of rock slope instabilities. This study delves into the amalgamation of AI and empirical techniques to attain highly precise outcomes in the evaluation of slope stability. Specifically, our primary objective is to propose innovative and efficient methods by investigating the integration of AI within the well-regarded Qslope system, renowned for its efficacy in analyzing rock slope stability. Given the complexities inherent in rock characteristics, particularly in coastal regions, the Qslope system necessitates adjustments and harmonization with other geomechanical methodologies. Uncertainties prevalent in rock engineering, compounded by water-related factors, warrant meticulous consideration during all calculations. To address these complexities, we present a novel approach through the infusion of fuzzy set theory into the Qslope classification, leveraging fuzziness to effectively quantify and accommodate uncertainties. Our approach employs a sophisticated fuzzy algorithm encompassing six inputs, three outputs, and 756 fuzzy rules, thereby enabling a robust assessment of rock slope stability in coastal regions. The implementation of this method capitalizes on the high-level programming language Python, enhancing computational efficiency. To validate the potency of our AI-based approach, we conducted preliminary tests on slope instabilities within coastal zones, indicating a promising initial direction. The results underwent thorough evaluation, affirming the precision and dependability of the proposed method. However, it is crucial to emphasize that this work represents a first attempt to apply AI to the evaluation of rock slope stability. Our findings underscore a high degree of concurrence and expeditious stability assessment, vital for timely and effective hazard mitigation. Nonetheless, we acknowledge that the reliability of this innovative method must be established through broader applications across diverse scenarios. The proposed AI-based approach’s effectiveness is validated through a preliminary survey on a slope instability case within a coastal region, and its potential merits must be substantiated through broader validation efforts.

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Section: Q Slope Classification Systemmentioning

confidence: 99%

Section: Qslope Classification Systemmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy-Based Intelligent Model for Rapid Rock Slope Stability Analysis Using Qslope

Mao

Chen²,

Nanehkaran

et al. 2023

Water

Self Cite

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“…Liu et al studied the instability mechanism of composite strata slopes with faults and weak layers and analyzed the stress field and damage zone evolution using the finite element strength reduction method [23]. Mehdi provided an empirical relationship for rock slope stability assessment with numerous micro-faults and fracture development [24]. Kumar collected and tested undisturbed soil samples from landslide areas with fracture zones developed and used different methods to conduct dynamic and static analysis of the slope stability [25].…”

Section: Introductionmentioning

confidence: 99%

A Case Study for Stability Analysis of a Toppling Bank Slope with Fault Fracture Zones Developed under the Action of Bridge Loads and Reservoir Water

Li,

Zhang,

Zhang

et al. 2024

Water

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The mountainous areas of Southwest China have the characteristics of valley deep-cutting, a large topographic gradient, complex geological structures, etc. With the development of infrastructure construction in the area, the construction of bridges across valleys has gradually increased, and the phenomenon of slope failure occurs more and more frequently. As the weak interlayer, the fault fracture zones have a significant influence on the geological structure and stability of slopes, while the complexity of the mechanism of the deformation and failure of slopes increases with the combination of the development of the fracture zones and toppling deformation. This paper took the toppling bank slope of bridge foundations developed with fault fracture zones in Lancang River as the research object. Through an on-site field survey and geological survey technologies, it identified the distribution range of the fracture zones on the bank slope and determined the characteristics of the rock mass in the fracture zones. A stability evaluation model for the bank slope of the bridge foundations was established using the limit equilibrium method and discrete element method. Based on the two-dimensional limit equilibrium analysis, the potential failure modes of the bank slope were explored, and the stability of the bank slope under bridge loads was calculated. Through the three-dimensional geological model of the bank slope, including the fracture zones and toppling bodies, the three-dimensional discrete element numerical simulation method was adopted to simulate and calculate the deformation and failure process of the bank slope under different bridge loads and working conditions. According to the calculation results, the influence of bridge loads and reservoir water on the stability of the bank slope was analyzed from the perspectives of displacement, plastic zone, stability coefficient, and other factors. The formation process of the plastic zone and the development of the sliding surface were revealed, the incentive mechanism of bridge loads and reservoir water on the deformation and failure of the bank slope was analyzed, and the influence of fault fracture zones on the stability of the bank slope and the development of toppling deformation was determined. The results indicate that the fault fracture zones are important geological structures that affect the deformation and failure of the bank slope as a weak interlayer. Under the influence of bridge loads and reservoir water, the stability of the bank slope is affected by the quality of the rock mass and the development of the fault fracture zones, resulting in the unmet need for safety requirements and maybe leading to instability. Based on the calculation results of the stability evaluation prediction model for the bridge foundation bank slope and the engineering geological conditions, the bridge scheme has been selected.

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Development of a computer program from photogrammetry for assisting Q-system rating

Chiu

Liu²

2023

International Journal of Rock Mechanics and Mining Sciences

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A Qslope-based empirical method to stability assessment of mountain rock slopes in multiple faults zone: A case for North of Tabriz

Cited by 4 publications

References 9 publications

Fuzzy-Based Intelligent Model for Rapid Rock Slope Stability Analysis Using Qslope

Fuzzy-Based Intelligent Model for Rapid Rock Slope Stability Analysis Using Qslope

A Case Study for Stability Analysis of a Toppling Bank Slope with Fault Fracture Zones Developed under the Action of Bridge Loads and Reservoir Water

Development of a computer program from photogrammetry for assisting Q-system rating

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