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

This article is dedicated to the pursuit of establishing a robust empirical relationship that allows for the estimation of in-situ modulus of deformations (E-m and G(m)) within sedimentary rock slope masses through the utilization of Q(slope) 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 Q(slope) values. Specifically, these relationships are expressed as follows: E-m = 2.859 Q(slope) + 4.628 (R-2 = 0.554), and G(m) = 1.856 Q(slope) + 3.008 (R-2 = 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 E(m)0.460 (R-2 = 0.798) and RMR = 22.09 G(m)0.460 (R-2 = 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 = 34.05e(0.33Qslope) (R-2 = 0.712) and RQD = 31.42(e0.549Qslope) (R-2 = 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 Q(slope) methodology. This holistic approach contributes significantly to advancing the understanding of sedimentary rock slope stability and provides valuable tools for informed engineering decisions.