Synthetic Rock Mass Modelling and Geotechnical Mapping: An Open Pit Mine Case Study in Anisotropic Rock. Issue 5 (28th May 2021)

• Record Type: Journal Article
• Authors: Bester, M.; Stacey, T.R.; Russell, T.
• Is Part Of: International journal of mining, reclamation and environment. Volume 35:Issue 5(2021)
• Page Start: 356
• Page End: 378
• Publication Date: 2021-05-28
• Subjects: Geotechnical Engineering -- synthetic Rock Mass Modelling -- geotechnical mapping -- open pit mining; Mining engineering -- Periodicals; Mineral industries -- Environmental aspects -- Periodicals; Abandoned mined lands reclamation -- Periodicals; 622.292
• DOI: 10.1080/17480930.2020.1834177
• Languages: English
• ISSNs: 1748-0930

Abstract

ABSTRACT: Most pit boundaries at Sishen Mine in South Africa consist of Banded Iron Formation (BIF), which exhibits anisotropic behaviour on a rock mass scale. A generally applicable approach is to apply Synthetic Rock Mass (SRM) modelling to characterise rock mass anisotropy. To characterise the rock mass for slope stability analysis, the persistence of bedding planes is very important. Subsequently, a sensitivity analysis on the effect that bedding persistence has on rock mass strength, was performed. Results indicate that bedding plane sizes less than the sample dimensions, produce higher strengths due to the influence of rock bridges. SRM modelling therefore demonstrates that persistence is a critical factor in rock mass strength analysis and subsequent slope stability analyses. The definition of SRMs is completely reliant on data provided by high quality, bench-scale structural mapping. The importance of geotechnical mapping is discussed, as it is currently the only way to accurately determine persistence. The Sishen study is a case in point that geotechnical mapping remains an essential function to obtain the appropriate rock mass characteristics for slope design. Routine mapping exercises, performed by well-trained geotechnical engineers, will therefore remain critical to acquire the necessary input parameters to advance the cutting edge SRM approach.