A Generalized Stochastic Framework for Analyzing Rock Slopes Stability and Designing Reliable Remedial Measures with Limited Investigation Data: Theory and Field Implementation

Abstract

Availability of limited data for rock properties is a very frequently encountered issue for the rock slopes along Himalayan highways due to problems like high costs, manual efforts, geological complexities, difficult terrain etc. involved in rock testing and investigation. Under these conditions, support estimation for rock slides mitigation using traditional deterministic and reliability approaches becomes highly questionable due to inaccuracy in the estimated statistical parameters of rock properties. To resolve this issue, this article proposes a computationally efficient methodology which utilizes Advanced Re-Sampling Reliability Approach (ARRA) along with deterministic approach and Target Reliability Approach (TRA) to estimate required support for rock slides mitigation when limited field and laboratory investigation data is available, with acceptable accuracy and confidence. Proposed methodology was used to design the support measures to mitigate two massive rock slides along a rock-slide prone highway i.e. Rishikesh-Badrinath National Highway (NH-58) in India. It was observed from the analysis that availability of limited test data induces high uncertainty in the statistical parameters (mean and standard deviation) and probability distribution of rock properties. Support estimation carried out using traditional deterministic and reliability approaches with this inaccurate probabilistic characterization of rock properties, can lead to inaccurate support estimates for potential rock slides in the presence of limited data; however these methods when coupled with ARRA can lead to significant improvement in computational efficiency and the designer’s confidence for the estimated support.