Cave fragmentation in a cave-to-mill context at the New Afton Mine part I: fragmentation and hang-up frequency prediction

Abstract

Block and panel caving methods are increasingly being proposed as an economical means for the excavation of ore deposits. The development of methods for predicting cave fragment size holds significant potential for reducing risk associated with cave mining projects. A fragmentation study was carried out for the New Afton B1 and B2 caves to generate fragmentation models that could be applied to future lifts. In part 1 of this paper, implications of fragmentation size for the mine are considered, whereas the effects on mill performance are addressed in part 2. Fragmentation measurements, from sieving and image-based methods, as well as historical logs of hang-up events are presented. Measurements showed that for the B1 and B2 caves, secondary fragmentation size, representing the size of material at drawpoints, is strongly related to faulting, height of draw and effects of the cave boundary.

Cave propagation factor for caving rate and drawpoint productivity forecasting at PTFI

“…The methodology shares some features with other recently developed approaches to fragmentation and productivity forecasting that recognize the importance of considering heterogeneity in cave back stress, intact/vein strength and discontinuity intensity. For example, cave back stress block models, point load index block models and flow mixing models have been coupled to aid in primary and secondary fragmentation forecasting at Niobec Mine Fuenzalida et al 2014) while fracture intensity block models have been developed and applied to similar forecasting at both Cadia Mine (Rogers et al 2010;Brunton et al 2016) and New Afton Mine (Munkhchuluun et al 2017;Nadolski et al 2018). New Afton Mine has also coupled primary fragmentation block models with flow mixing models to develop drawpoint-based forecasts (Munkhchuluun et al 2018) and Castro & Cuello (2018) provide an example of how drawpoint monitoring data can be used to enhance productivity forecasting through the development of site specific hangup frequency relations.…”