An integrated approach to span design in open stope mining

In order to develop an appropriate mine design, a thorough understanding of the rock mass conditions and its potential response to mining is required. Rock mass characterisation is a key component in developing models of the rock mass and its engineering behaviour, and relies on disparate data collected by exploration geologists, mine geologists, rock mechanics engineers and technicians, in a variety of formats. Optimal rock mass model development requires the effective integration of all data sources, which currently requires considerable effort in collecting, managing, collating, validating and analysing this data.The importance of understanding the spatial variability of rock mass conditions has been highlighted as a major issue. The traditional approach of using simplistic models of “average” rock mass conditions can lead to sub-optimal designs, which may result in unplanned additional costs or economic implications of dilution and ore loss. The design of stope and pillars should be optimised for the prevailing rock mass conditions in the various regions of the mine.Some of the existing design tools used for open stope design have shown poor reliability in their performance predictions. Though some may have been originally developed to assist in initial stope size selection (i.e. pre-feasibility and feasibility levels), they are potentially being inappropriately relied upon for detailed design. Consideration of large scale structures on stability and their influence on local rock mass conditions are also important aspects of open stope design that are commonly over-looked. There is a need to select design methodologies that are optimised for the stage of project development. It is also important to emphasise the iterative, evolutionary and interdisciplinary nature of open stope design.This thesis proposes a framework that attempts to integrate different rock mass characterisation models, numerical modelling and stope performance data to assist in improving the overall excavation design process. The key philosophy behind design optimisation is the continual reduction in uncertainty in collected data, analysis and design methods used with a view to improving the overall reliability of the design. A stope span design optimisation approach is proposed which attempts to ensure that the appropriate methodologies in data collection, data analysis, rock mass model formulation and stope design are utilised at relevant project stages in order to minimise uncertainty and maximise design reliability. The design optimisation approach recognises that the appropriateness of a particular design methodology is highly dependant on the availability of an appropriate rock mass model, which is in turn dependant on the availability of quality rock mass data. With respect to the design of spans in open stope mining, the key aims of the proposed integrated approach are to; • Assess the suitability of data for analysis • If data is unsuitable, assess the most appropriate data collection strategy • Assess the most appropriate approach to rock mass modelling • Assess the most appropriate design methodologies • Assess the reliability of the design criteria and quantify the potential economic impact of the design on the projectOptimisation of the design process also requires integration of state-of-the-art techniques in data collection, analysis, modelling and engineering analysis and design at the appropriate stage of project development. During development of this thesis a number of improvements have been proposed in key areas in the rock engineering design process which can be incorporated into the integrated approach, including; • A rock mass data model has been developed that assists in facilitating the ongoing rock mass characterisation process. The data model is capable of integrating rock mass data from various sources, which promotes sharing of data and avoids duplication of data collection efforts. The data model is able to query rock mass data, define relationships between data types, apply bias corrections, and perform basic analysis for use in subsequent detailed analysis and rock mass modelling. • An implicit based approach to spatial rock mass and deterministic discontinuity modelling can be employed to improve understanding of the spatial variability of rock mass parameters, inter-relationships between rock mass characteristics on their role in design. For example, understanding the influence of large-scale structures on rock mass characteristics and excavation performance. • Improved scale independent geometrical assessments of stope performance have been proposed that maximise the use of stope performance data. • An integrated back analysis framework has been presented that is able to account for structural complexity, scale and features that cannot be directly incorporated into linear elastic numerical modelling codes. • With regard to linear elastic back analyses, an number of improvements have been proposed, as well as a suggested method to assess appropriateness of continuum models based on discontinuity intensity and critical span

An implicit function based approach to deterministic discontinuity modeling using trace data

A methodology has been described that is capable of generating realistic 3-dimensional models of large-scale structures from mapped discontinuity trace data. The technique incorporates a search algorithm to hierarchically select traces based on a variety of criteria, such as orientation, genetic type, and surface characteristics. Implicit functions (based on radial basis functions) are utilized to interpolate surfaces between selected trace data to provide validated realistic surface geometries. The implicit function based modeling approach also provides the rock engineer with an important tool in rock mass modeling and excavation design. The deterministic discontinuity models can be output as meshed surfaces as direct input into 3-dimensional discontinuum and continuum numerical modeling