Numerical Modelling Challenges in Rock Engineering with Special Consideration of Open Pit to Underground Mine Interaction
This paper raises important questions about the way we approach numerical analysis in rock engineering design. The application of advanced numerical models is essential to adequately analyze and design different geotechnical aspects of pit-to-cave transitions. We present a critical review of numerical methods centered around the hypothesis that a model is not, and cannot be, a perfect imitation of reality; therefore, numerical modelling of large-scale mining projects requires the real problem to be idealized and simplified. The discussion highlights the dichotomy of continuum vs. discontinuum modelling and the important question of whether continuum models can effectively capture dynamic continuum-to-discontinuum processes typical of cave mining. The discussion is complemented by examples of hybrid continuum-discontinuum models to analyze the important problem of transitioning from surface (open pit) mining to underground mass mining (caving). The results demonstrate the hypothesis that forward modelling should be performed in the context of a risk-based approach, with numerical models becoming investigative tools to assess risk and evaluate the impact of different unknowns, thus classifying modelling outputs in terms of expected consequences.
Examining Rock Engineering Knowledge through a Philosophical Lens
This paper presents a philosophical examination of classical rock engineering problems as the basis to move from traditional knowledge to radical (innovative) knowledge. While this paper may appear abstract to engineers and geoscientists more accustomed to case studies and practical design methods, the aim is to demonstrate how the analysis of what constitutes engineering knowledge (what rock engineers know and how they know it) should always precede the integration of new technologies into empirical disciplines such as rock engineering. We propose a new conceptual model of engineering knowledge that combines experience (practical knowledge) and a priori knowledge (knowledge that is not based on experience). Our arguments are not a critique of actual engineering systems, but rather a critique of the (subjective) reasons that are invoked when using those systems, or to defend conclusions achieved using those systems. Our analysis identifies that rock engineering knowledge is shaped by cognitive biases, which over the years have created a sort of dogmatic barrier to innovation. It therefore becomes vital to initiate a discussion on the subject of engineering knowledge that can explain the challenges we face in rock engineering design at a time when digitalisation includes the introduction of machine algorithms that are supposed to learn from conditions of limited information.
Why the future of rock mass classification systems requires revisiting their empirical past
Despite recent efforts, digitization in rock engineering still suffers from the difficulty in standardizing and statistically analysing databases that are created by a process of quantification of qualitative assessments. Indeed, neither digitization nor digitalization have to date been used to drive changes to the principles upon which, for example, the geotechnical data-collection process is founded, some of which have not changed in several decades. There is an empirical knowledge gap that cannot be bridged by the use of technology alone. In this context, this paper presents the results of what the authors call a rediscovery of rock mass classification systems, and a critical review of their definitions and limitations in helping engineers to integrate these methods and digital acquisition systems. This discussion has significant implications for the use of technology as a tool to directly determine rock mass classification ratings and for the application of machine learning to address rock engineering problems.
The Role of Behavioural Factors and Cognitive Biases in Rock Engineering
In this paper, the authors investigate the role that behavioural factors and cognitive biases play in rock engineering. The concept of behavioural rock engineering is herein introduced as the study of rock engineering as it pertains to design decisionmaking processes made by individuals. The objectives of this paper are twofold: (i) to provide a better understanding how knowledge is used (or not used) in rock engineering to achieve conclusions based on an individual’s experience; and (ii) to offer a critical discussion on the resistance to changing methods that were first developed in the 1960s and 1970s. Accordingly, the paper presents a critical review of what engineers and professional refer to as industry standards in rock engineering; the discussion is centred around the concepts of uncertainty and variability, which form our aggregate knowledge of a problem, and the distinction between knowledge, experience and engineering judgement. The objective of this paper is not to discourage the use of rock mass classification/characterisation systems; rather, to encourage a more careful, considerate and reflective use of those varied systems. Ultimately, preferential engineering attachment biases should not be allowed to become a hindrance to the proposal and adoption of improved versions and alternatives to current empirical methods.
The concept of representative elementary length (REL) as an effective tool to study scale effects in rock engineering problems
In this paper, a discrete fracture network approach (DFN) is used to study scale effects on rock quality designation (RQD) measurements. RQD is a parameter that describes rock mass quality and represents a fundamental component of several rock mass classification systems. The results demonstrate that it is possible to define a representative elementary length (REL), above which RQD measurements represent an average indicator of rock mass quality. However, the directional bias of RQD measurements is such that the choice of REL is itself a function of the orientation of the sampling line used to estimate RQD. By considering multiple sampling directions, this paper introduces the concept of a REL Ellipsoid, whereby the normalized value of the REL along three sampling directions indicates the degree of homogeneity and isotropy of the rock mass with increase in problem scale. In the authors’ opinion, the REL Ellipsoid concept allows to better capture the nature of the 3D representative elementary volume (REV) for both isotropic and anisotropic rock masses Mapping data from a room-and-pillar mine are used in the initial validation of the proposed REL Ellipsoid concept.
Procedure for estimating broken ore density distribution within a draw column during block caving
Broken ore density (BOD) is an important parameter in planning a block cave mine. However, its assessment is complicated by the heterogeneous nature of its distribution within a draw column, varying from a denser central plug-flow zone and decreasing outwards towards outer perimeter shear bands. The BOD further decreases immediately above the drawpoint due to the development of a loosening zone that develops in response to mucking. This makes determining BOD a challenging task, hindered by the inability to measure it in situ. To address this, several key factors influencing BOD are investigated including the influence of primary and secondary fragmentation, air gap thickness, draw rate and column height. Data is used to link primary and secondary fragmentation to broken ore size distributions. From these, a conceptual framework and empirical procedures are presented for evaluating BOD within draw columns during block caving for feasibility and early stage mine planning and design.
A Numerical Based Approach to Calculate Ore Dilution Rates Using Rolling Resistance Model and Upside-Down Drop Shape Theory
The chief characteristic of the caving mining method is that caved ores, surrounded by overlying rocks, are drawn from the drawpoint. And the ultimate objective of investigating the draw problems is to forecast the ore loss and dilution. In this paper, the rolling resistance model in the Particle Flow Code was used to simulate the effect of actual shape of different materials flowing towards a drawpoint under the near-field condition and improve the computational efficiency at the same time. The reliability of the rolling resistance model was validated against experimental results, and the new empirical equations were deduced for calculation of the ore dilution rates based on the upside-down drop shape theory (UDDS theory). Within the precision and range of values considered in this paper, the results show that when the height of IEZ is in the range of 30–80 m, the particle size, the drawpoint size and the column height have no significant influence on the (isolated extraction zone) IEZ’s shape and maximal width. And regardless of near-field gravity flow with one or two granular materials, the shape of IEZ was coincident with the upside-down drop shape.
A Study of Gravity Flow Based on the Upside-Down Drop Shape Theory and Considering Rock Shape and Breakage
The cave mining method relies on gravity to fragment the rock mass into blocks that can be extracted out of drawpoints. Several discrete element method (DEM) models on gravity flow are presented in the literature; however, only a few of those consider rock shape and secondary fragmentation. In this paper, the reliability of the particle flow code (PFC) to model gravity flow of fragmented rock is validated against known experimental results. A new method to create complex shape clusters is proposed and then used to investigate the mechanisms of gravity flow and the influence of particle bond strength on the secondary fragmentation, and the evolutions of the movement zone and extraction zone. The model results are validated against the upside-down drop shape theory for two cases: (1) constant size of fragmented rock blocks and (2) changing size due to breakage of the fragmented rock blocks. For the latter case, the results show that secondary fragmentation of weaker rocks would result in a wider movement zone and extraction zone than that of stronger rocks.
Influence of data analysis when exploiting DFN model representation in the application of rock mass classification systems
Discrete fracture network (DFN) models have been proved to be effective tools for the characterisation of rock masses by using statistical distributions to generate realistic three-dimensional (3D) representations of a natural fracture network. The quality of DFN modelling relies on the quality of the field data and their interpretation. In this context, advancements in remote data acquisition have now made it possible to acquire high-quality data potentially not accessible by conventional scanline and window mapping. This paper presents a comparison between aggregate and disaggregate approaches to define fracture sets, and their role with respect to the definition of key input parameters required to generate DFN models. The focal point of the discussion is the characterisation of in situ block size distribution (IBSD) using DFN methods. An application of IBSD is the assessment of rock mass quality through rock mass classification systems such as geological strength index (GSI). As DFN models are becoming an almost integral part of many geotechnical and mining engineering problems, the authors present a method whereby realistic representation of 3D fracture networks and block size analysis are used to estimate GSI ratings, with emphasis on the limitations that exist in rock engineering design when assigning a unique GSI value to spatially variable rock masses
Cave fragmentation in a cave-to-mill context at the New Afton Mine part I: fragmentation and hang-up frequency prediction
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
Volumetric Fracture Intensity Measurement for Improved Rock Mass Characterisation and Fragmentation Assessment in Block Caving Operations
Recent discrete fracture network (DFN) related analysis of a number of block caving projects has demonstrated the role that the 3D volumetric fracture intensity measure (P32) plays on controlling a number of rock mass properties critical to caving operations. P32 represents the fracture area per unit volume and as such represents a nondirectional intrinsic measure of the degree of rock mass fracturing, incorporating both a frequency measure and a fracture size component. Preliminary results suggest that the P32 intensity of a DFN model would strongly control the overall fragmentation of the rock mass. The implication would be that by taking the overall distribution of P32, the in situ fragmentation of a large rock mass volume could be determined in a computationally efficient way. With P32 also being shown to be one of the dominant controls on DFN derived directional stiffness measures, increasingly these DFN related work flows are being shown to be central to an improved rock mass characterisation process and ultimately the more accurate capturing of the caving process.
Discrete Fracture Network approach to characterise rock mass fragmentation and implications for geomechanical upscaling
Natural fragmentation is a function of the fracture length and connectivity of naturally occurring rock discontinuities. This study reviews the use of a Discrete Fracture Network (DFN) method as an effective tool to assist with fragmentation assessment, primarily by providing a better description of the natural fragmentation distribution. This approach has at its core the development of a full-scale DFN model description of fracture orientation, size and intensity built up from all available geotechnical data. The model fully accounts for a spatially variable description of the fracture intensity distribution. The results suggest that DFN models could effectively be used to define equivalent rock mass parameters to improve the predictability achieved by current geomechanical simulations and empirical rock mass classification schemes. As shown in this study, a mine-scale DFN model could be converted to equivalent directional rock mass properties using a rapid analytical approach, allowing the creation of a rock mass model that incorporates the influence of a local variable structure with continuous spatial variability. When coupled with more detailed numerical synthetic rock mass simulations for calibration and validation, a balanced and representative approach could be established that puts more equal emphasis on data collection, local- and large-scale characterisation, conceptualisation and geomechanical simulation.
Integrated mining and mineral processing for more advanced mining system
The integration of mining and mineral processing technologies into new advanced mining systems is considered to offer several benefits, including selective mining, reduction in waste, increased productivity, flexibility, and improved resource utilization. This paper focuses on underground hardrock mining and the integration of pre-concentration technologies into future mining systems as representing realistic, shorter-term integration options. Control of fragmentation to optimize grinding, pre-concentration of ores, in situ leaching, and modular mining/mineral processing systems are possible with existing technology. Current research is directed toward development of integrated underground systems that minimize surface activity and minimize or eliminate surface waste disposal. Results from a simulation model of an integrated underground pre-concentration system are presented.
Insight in ore grade heterogeneity and potential of bulk ore sorting for block cave mining
A block cave mine operation was investigated in terms of ore grade heterogeneity and the potential of bulk ore sorting application. The grade heterogeneity within the caved material was measured for different draw points and mining zones, in terms of Distribution Heterogeneity and Fractal Dimension. The potential of bulk ore sorting was assessed by comparing the Net Smelter Return before and after a hypothetical bulk ore sorting system was implemented. Results showed that the potential of applying bulk ore sorting was influenced greatly by the heterogeneity within the mined material. A certain level of heterogeneity was necessary in considering the mine production as ‘sortable’. The sortability would also vary for different mining areas depending on heterogeneity level of the production. Peripheral zones of the orebody were considered with the highest level of heterogeneity and the most significant potential of bulk ore sorting application.
Cave to Mill a Mine to Mill approach for block cave mines
A refinement of the traditional Mine-to-Mill integration opportunity for copper block cave mines is introduced here as a Cave-to-Mill production management concept. This is essentially the integration of underground mine production scheduling and monitoring with surface mineral processing management based upon fragment size and geometallurgical ore characteristics. Cave-to-Mill defines ore block models with respect to both mine and mill performance. Linkages between key cave and mill parameters have been established so that coordinated efforts towards maximizing net present value (NPV) can be made. Discrete fracture network (DFN) based methods were found to hold significant value within the Cave-to-Mill approach. The variable and relatively uncontrollable nature of cave fragmentation is considered to be a key distinguishing feature of Cave-to-Mill when compared with typical Mine-to-Mill strategies established for open-pit mines. It is envisioned that Cave-to-Mill will be an important design and operational strategy for block cave mines.
Evaluation of bulk and particle sensor-based sorting systems for the New Afton
Block and panel caving mines are increasingly being proposed for the excavation of massive ore-bodies located at depth. The lack of selectivity associated with the mining methods results in both ore and waste being caved and transported through material handling systems to the surface for processing and waste rock disposal. Sensor based sorting systems provide an opportunity to automate the discrimination between ore grades and rock types, providing an enhanced level of selectivity for ore control and thereby improving mine productivity. To evaluate the potential to add value to a caving operation, a sensor-based ore sorting study, incorporating bulk and particle sorting systems, was carried out for the New Afton block cave mine. Results showed that rock from the copper-gold porphyry deposit is amenable to prompt gamma neutron activation analysis, and to X-ray fluorescence sensors. A conceptual flowsheet, where both technologies are used as separate unit operations, was evaluated. Test samples of varying copper head grades allowed an ore value calculation method to be developed based on the integration of continuous bulk sorting and particle sorting. The calculation method can be applied to block models of a future cave at New Afton and used to evaluate the change in the economic footprint. It was found that the concept demonstrated an improvement in the net smelter return of excavated material.