Authors: Basson, FRP; Humphreys, R; Temmu, A


DOI https://doi.org/10.36487/ACG_rep/1308_82_Basson

Cite As:
Basson, FRP, Humphreys, R & Temmu, A 2013, 'Coefficient of restitution for rigid body dynamics modelling from onsite experimental data', in PM Dight (ed.), Proceedings of the 2013 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering, Australian Centre for Geomechanics, Perth, pp. 1161-1170, https://doi.org/10.36487/ACG_rep/1308_82_Basson

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Abstract:
Rigid body dynamics uses the Newtonian laws of motion to solve the physics behaviour of moving bodies as a function of time. This approach is fast enough for real time simulation of multiple fall bodies, and can simulate the trajectories of three-dimensional volumetric bodies during free fall, bouncing, sliding and rolling. An additional benefit of rigid body dynamics is that the input parameters required are few, measurable and intuitive, as only the coefficient of restitution (COR), and the static and dynamic friction angles are required. The Geotechnical Team at Newmont Boddington Gold (Boddington) undertook simple experiments to determine the ranges of COR values applicable to different surfaces for the Boddington pits. Ten rocks between 0.35 and 2.08 kg were collected, weighed, marked, and measured. Each rock was then dropped ten times from a height of 1.40 m onto the four different horizontal pit surfaces ‘pit floor’, ‘haul road’, ‘catch berm’, and ‘hard rock’. The rebound of each drop test was measured with a scaled white board behind the test area from video footage. A total of 400 data points were collected and the results analysed. It was found that the different rebound surfaces have different levels of predictability in rebound behaviour, and that some surfaces a more prone to occasional outlier results. The aim of these experiments was to obtain rebound information for use in the rigid body dynamics modelling software package Trajec3D. During a full scale rockfall experiment, and the accompanying threedimensional backanalysis with volumetric fall bodies, many factors determine the outcome that complicates the verification of the individual simulation components. The simple experiments discussed before were simulated in Trajec3D to determine if rigid body dynamics could simulate realistic rebound behaviour with different rock shapes, sizes, and physics material interaction properties. The combined outcomes from the rockfall experiments and rigid body dynamic simulations lead to the identification of the critical factors controlling fall body rebound behaviour at Boddington. Appropriate COR values will be selected and used in the analysis of larger scale rockfall experiments, the backanalyses of known rockfall events, and to identify and assess potential future rockfall areas.

References:
Basson, F.R.P. (2012) Rigid body dynamics for rock fall trajectory simulation, in Proceedings 46th US Rock Mechanics/Geomechanics Symposium 2012, A. Bobet, R. Ewy, M. Gadde, J. Labuz, L. Pyrak-Nolte, A. Tutuncu and E. Westman (eds), 24–27 June, Chicago, USA, Curran Associates Inc, New York, pp. 1438–1444.
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