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24-MMP-A5 Surface Mining Methods and Design · December 2018

Question 7 of 27

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper
Paper: Surface Mining Methods and Design (09-MMP-A5), National Exam, December 2018 — 20 pages, compulsory Question 1 (40 marks, parts 1.1–1.8) plus THREE of five optional Questions 2–6 (20 marks each) normally constitute a complete paper. As a study resource, this solution answers Question 1 in full AND all five optional Questions 2–6.

Reference texts: Hustrulid, Kuchta & Martin, Open Pit Mine Planning and Design (3rd ed.) — truck-shovel match factor, dragline stripping geometry, capital cost indexes, open-pit scheduling; SME Mining Engineering Handbook (3rd ed.) — equipment costing, mine dewatering, cost-index escalation.

Question 1.7 (5 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

1.7.1 — why monitor even after good design. Slope DESIGN uses average, sampled rock-mass properties (RMR/Q, joint sets, strength) that can never fully capture every local structural anomaly, blast-damage zone, or pore-pressure change encountered as mining actually advances; groundwater, blast vibration, and progressive stress redistribution as the pit deepens all continue to change conditions AFTER design is finalised. Displacement monitoring (prisms, radar, InSAR, extensometers) is the only way to detect the onset of movement in real time, giving early warning of a developing failure BEFORE it becomes catastrophic — design reduces the probability of failure, monitoring manages the consequence of a failure the design could not fully anticipate.

1.7.2 — Bieniawski. Z.T. Bieniawski developed the Rock Mass Rating (RMR) system (1970s–80s), a practical empirical classification combining intact rock strength, RQD, discontinuity spacing/condition, and groundwater into a single 0–100 score used worldwide to guide slope angle, support design and excavation method selection. Achievements: simple, field-repeatable, requires no advanced numerical modelling, and correlates reasonably well with rock-mass deformation modulus and stand-up time, making it hugely influential across mining and civil rock engineering. Shortcomings: RMR is empirical, not mechanistic — it does not directly model the actual failure mechanism, can be subjective between raters classifying the same face, and was calibrated primarily on TUNNELLING case histories, so its direct application to open-pit slope stability (very different stress path and much larger scale) requires caution and is usually supplemented by kinematic and limit-equilibrium analysis rather than used alone.

ItemAnswer
Why monitordesign uses averaged properties; monitoring catches real-time deviations design cannot predict
Bieniawski’s systemRock Mass Rating (RMR), 0–100 empirical classification
Achievementssimple, field-repeatable, links to support design and stand-up time
Shortcomingsempirical not mechanistic, rater subjectivity, tunnelling-calibrated