Geomechanics and Engineering

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Empirical correlation for in-situ deformation modulus of sedimentary rock slope mass and support system recommendation using the Qslope method

  • Yimin Mao (School of Information and Engineering, Shaoguan University) ;
  • Mohammad Azarafza (Department of Civil Engineering, University of Tabriz) ;
  • Masoud Hajialilue Bonab (Department of Civil Engineering, University of Tabriz) ;
  • Marc Bascompta (Department of Mining Engineering, Polytechnic University of Catalonia) ;
  • Yaser A. Nanehkaran (School of Information Engineering, Yancheng Teachers University)
  • Received : 2022.05.13
  • Accepted : 2023.11.17
  • Published : 2023.12.10
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Abstract

This article is dedicated to the pursuit of establishing a robust empirical relationship that allows for the estimation of in-situ modulus of deformations (Em and Gm) within sedimentary rock slope masses through the utilization of Qslope values. To achieve this significant objective, an expansive and thorough methodology is employed, encompassing a comprehensive field survey, meticulous sample collection, and rigorous laboratory testing. The study sources a total of 26 specimens from five distinct locations within the South Pars (known as Assalouyeh) region, ensuring a representative dataset for robust correlations. The results of this extensive analysis reveal compelling empirical connections between Em, geomechanical characteristics of the rock mass, and the calculated Qslope values. Specifically, these relationships are expressed as follows: Em = 2.859 Qslope + 4.628 (R2 = 0.554), and Gm = 1.856 Qslope + 3.008 (R2 = 0.524). Moreover, the study unravels intriguing insights into the interplay between in-situ deformation moduli and the widely utilized Rock Mass Rating (RMR) computations, leading to the formulation of equations that facilitate predictions: RMR = 18.12 Em0.460 (R2 = 0.798) and RMR = 22.09 Gm0.460 (R2 = 0.766). Beyond these correlations, the study delves into the intricate relationship between RMR and Rock Quality Designation (RQD) with Qslope values. The findings elucidate the following relationships: RMR = 34.05e0.33Qslope (R2 = 0.712) and RQD = 31.42e0.549Qslope (R2 = 0.902). Furthermore, leveraging the insights garnered from this comprehensive analysis, the study offers an empirically derived support system tailored to the distinct characteristics of discontinuous rock slopes, grounded firmly within the framework of the Qslope methodology. This holistic approach contributes significantly to advancing the understanding of sedimentary rock slope stability and provides valuable tools for informed engineering decisions.

Keywords

Acknowledgement

The authors would like to thank the anonymous reviewers for providing invaluable review comments and recommendations for improving the scientific level of the article. This work is supported by the Key Improvement Projects of Guangdong Province with Grant Number 2022ZDJS048, the Shaoguan Science and Technology Plan Projects with Grant Number 220607154531533, and the National Nature Sciences Foundation of China with Grant Number 42250410321.

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