ISSN: 1402-1536 ISBN 978-91-7439-465-8 Validation of...

TECHNICAL REPORT

Validation of numerical analysisA feasibility study

Catrin Edelbro

ISSN: 1402-1536 ISBN 978-91-7439-465-8

Luleå University of Technology 2012

Department of Civil, Environmental and Natural Resources EngineeringDivision of Mining and Geotechnical Engineering

Validation of numerical analysis

A feasibility study

Catrin Edelbro

Luleå University of TechnologyDepartment of Civil, Environmental and Natural Resources Engineering

Division of Mining and Geotechnical Engineering

ISSN: 1402-1536ISBN 978-91-7439-465-8

Luleå 2012

www.ltu.se

PREFACE

This feasibility study has been carried out at the Division of Mining and Geotechnical Engineering at the Luleå University of Technology with support from Jonny Sjöberg at Itasca Consultants AB. It has been a 12 week project performed during autumn 2011 and spring 2012. The financial support for the project is being provided by Hjalmar Lundbohm Research Centre (HLRC). First of all I would like to thank Jonny Sjöberg for his FLAC-guidance as well as for performing proof-readings of this report. I would also like to thank my contact persons at LKAB, Britt-Marie Stöckel and Lars Malmgren for help in finding relevant information at LKAB, for proof-reading of this report and for helpful and supportive discussions when I presented my work at LKAB in December 2011. At LKAB I would also like to thank Jimmy Töyrä for proof-reading of this report. Luleå, June 2012 Catrin Edelbro

ABSTRACT The main objective of this feasibility study was to increase the understanding of where, what, when and how measurements should be performed in order to validate the numerical analysis. This work has focused on validation of existing material models and softwares used by LKAB for rock mechanical numerical analysis. The mining-induced stress, deformation and yielding of footwall drifts in the Kiirunavaara Mine has been studied.

Based on this study it was concluded that it is preferable to conduct measurements in drifts close to the ore. The strength of the rock mass had a large influence on the calculated stress and displacement values, as well as on the amount of yielding. The Young's modulus had a large influence on the displacements, especially for low stiffness values. The best position to measure stresses in the footwall drift were in the roof and it is necessary to install the monitoring equipment in the roof when the production is (or opening has started) two levels above the studied drift. However for other directions to measure stresses it is important to install the monitoring equipment when the production is three levels above the studied drift in order to study all important variations caused by mining. The lower right-hand corner (opposite the direction to the ore-contact) is the most suitable location for monitoring both the x- and y-displacement. The displacement monitoring equipment should be installed in the studied drift when the production has started one to two levels above. The best positions to measure the Excavation Damage Zone are in the walls. In general, whether it is stress, deformation or EDZ monitoring, the installation of such equipment needs to be “marked” in the mine map already at the planning stage of the drifts. The suggestion for future work is to start a validation project.

SAMMANFATTNING Syftet med denna förstudie var att öka förståelsen för var, vad, när och hur mätningarna bör utföras för att kunna validera numeriska analyser. Detta arbete har fokuserat på validering av befintliga materialmodeller och programvaror som används av LKAB för bergmekaniska analyser. Sekundära spänningar orsakade av gruvdriften, deformationer och plasticering runt fältorter i liggväggen i Kiirunavaara gruva har studerats. Baserat på denna förstudie kan man dra slutsatsen att det är fördelaktigt att utföra mätningar i orter som ligger nära malmkontakten. Bergmassans hållfasthet hade en stor påverkan på resultatet av de beräknade spänningarna, deformationerna och storleken på den plasticerade zonen. Young's modul hade en stor påverkan på deformationerna, särskilt för låga värden på styvheten. Den bästa positionen att mäta spänningar på i fältorter visade sig vara i taket och det är nödvändigt att installera utrustningen i taket när produktionen är (eller öppningen har börjat) två nivåer ovanför den studerade orten. Om spänningarna ska mätas i andra riktningar är det viktigt att installera utrustningen när produktionen ska börja tre nivåer ovanför den studerade orten för att kunna studera alla stora förändringar som sker orsakade av gruvdriften. Det nedre högra hörnet (i motsatt riktning till malmkontakten) är den lämpligaste platsen för övervakning både x-och y-förskjutningen. Utrustningen för att mäta deformationer/förskjutningar bör installeras i den studerade orten när produktionen har påbörjats en till två nivåer ovanför. De bästa positionerna att mäta skadezonen (EDZ) är i väggarna. Hur än om det är spänning, deformation eller EDZ som ska övervakas så behöver installation av sådan utrustning finnas med i gruvkartan redan då orten planeras. Förslaget på framtida arbete är att starta ett valideringsprojekt.

Table of Contents Page

1 Introduction ..................................................................................................... 1 1.1 Problem statement ................................................................................. 1 1.2 Aim and objective .................................................................................. 4 1.3 Limitations ............................................................................................. 4 1.4 Outline of report ................................................................................... 5

2 Review of Case studies ..................................................................................... 7 2.1 Introduction .......................................................................................... 7 2.2 The Mine-by Experiment ...................................................................... 7 2.3 Palabora mine ........................................................................................ 8 2.4 Northparkes mine ................................................................................ 10 2.5 Kidd Creek .......................................................................................... 11 2.6 Continuous monitoring in a mining panel in Colonsay ........................ 11 2.7 Experiments at the Stripa Mine ............................................................ 12 2.8 The Äspö Pillar Stability Experiment ................................................... 15 2.9 Monitoring and measurements at Boliden ............................................ 17 2.10 Monitoring and measurements at LKAB .............................................. 18

2.10.1 Kiirunavaara .............................................................................. 18 2.10.2 Malmberget ............................................................................... 21

2.11 Summary of case studies ....................................................................... 21

3 Case Study – The Kiirunavaara mine .............................................................. 23 3.1 Model setup and input data .................................................................. 23 3.2 Parametric study .................................................................................. 28

4 Modelling results ............................................................................................ 31 4.1 Drifts at different distance from the ore contact .................................... 31 4.2 Evaluation of best positions to measure in a drift .................................. 39 4.3 Significance of strength and stiffness variation ....................................... 50

5 Discussion ....................................................................................................... 61

6 Conclusions and suggestions for future work .................................................. 65

References ................................................................................................................ 67

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1 INTRODUCTION

1.1 Problem statement

Numerical modelling may be used to simulate rock mass behaviour and mining-induced rock mass response However, a major problem is to know how well the results from numerical modelling correspond to what is happening in the field and the actual rock mass behaviour. In sublevel caving the ore is fragmented using blast holes drilled upwards in fans from the roof of the cross cut and extracted at drawpoints. As a result of the mining, excavations near the orebody will be subjected to changing stresses as mining progresses downward, see Figure 1. Generally when an underground opening is subjected to a change in stress condition the stability is affected. However the effect on the stability varies depending on the in-situ stress, excavation induced stress and other mining related stress changes. The first development on a new sublevel is the footwall drifts, oriented parallel to the orebody. The next steps are the cross-cut drifting, production drilling, and mucking. In sublevel cave mining, the footwall access drifts have a long required life while being exposed to changing stress condition. The footwall drifts needs to remain functional during the entire production cycle, from the first drifting to the final mucking. For the LKAB underground mines most rock mechanics problems occur in drifts in and near the orebody. Being able to provide a representation of the reality in computational form and obtain reliable results of numerical analysis would thus be of great benefit for such excavations.

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Figure 1 Stress redistribution caused by progressive sublevel caving (from Sjöberg et al., 2001).

To be able to assess whether a numerical model is acceptable, it must be verified and validated. The terms verification and validation can be defined as follows (Wikipedia, 2011), see also Figure 2: Verification is defined as the process of determining that a computer model correctly represent the conceptual description and specification, e.g., ensuring that the computer model is an accurate implementation of an underlying mathematical model. In other words, verification is to certify that the computer model has been developed correctly ("that you built it right"). Validation is the process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended use(s). In other words, validation is to ensure that the model fulfill its use ("that you built the right thing"). Model validation is often more difficult and time-consuming then verification as it requires comparison of model output with the observed real behaviour of a system. Calibration is a comparison between measurements – one of known magnitude or correctness made or set with one device and another measurement made in as similar a way as possible with a second device (Wikipedia, 2012).

Major principal stress

Orebody

Footwall Hangingwall

Ground surface

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Figure 2 The verification and validation process (modified from Horrigmoe, 2011).

In order to validate results from numerical analysis, it is important to know where to measure. Should the monitoring equipment be installed in an access drift, a footwall drift or a shaft near the production area? Should measurements be performed at a short distance from the ore contact or at longer distance? The installations of the monitoring equipment could be done in many different ways, see example in Figure 3.

Figure 3 Schematic picture of a footwall drift near the ore body where measurements will be performed.

Mined area

Access drift

Measure ?

Measure ?

Measure ?

Assessment activities

Modeling, Simulation and experimental activities

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The stability of an excavation must be studied versus the progress of mining. The stresses will increase as mining goes deeper but also for excavations at a shorter distance to the production. Hence, it is important to know when in relation to the mining that the measurement should be performed. Should the monitoring equipment be installed directly after drifting with a continuous update of data until the final mucking has been performed or is it enough to start measure when the mucking starts at one level above the studied excavation? With the help of numerical modelling the most appropriate parameter to monitor can be identified together with suggestions on when and how to measure that parameter in relation to the mining progress.

1.2 Aim and objective

The objective of the feasibility study is to:

Achieve a better understanding of where, what, when and how measurements should be performed in order to validate the numerical analysis.

Develop a comprehensive plan for how and what to measure in order to validate numerical models.

The aim, which primarily will be applicable to the production areas in LKAB's mines) is to provide answers to:

Where the monitoring equipment should be installed in order to be able to validate numerical models (roof, wall, long or short distance from the ore contact etc.)?

What should be measured in order to validate (stresses, deformations, other parameter)?

When should the measuring be performed in relation to the mining (immediately after operation/drifting or later of transition)?

How should the measuring be performed in order validate (e.g. convergence measurement, extensometers)?

The measurements should be performed in regions/sections where the studied parameter exhibit large gradients/variations.

1.3 Limitations

Footwall drifts in the Kiirunavaara mine have been used as case studies in this work. The distance between the drift and the ore contact has been 10-80 m. The footwall drifts on level 1165 were analysed with respect to the virgin stresses and changes in

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stresses when opening has started five levels above (level 1050) to the opening of the level under (level 1194). In the parametric study, the influence of the possible variation of the virgin stress state has not been studied. This work focuses on validation of existing material models and softwares used by LKAB for rock mechanical numerical analysis. Three parameters are evaluated in this work, namely the stress, deformation and yielding.

1.4 Outline of report

This feasibility study comprise four tasks, with intermediate goals and reporting as described in Figure 4.

Figure 4 Overview of the different tasks in this feasibility study.

The case study review is presented in Chapter 2 of this report. The methodology for numerical modelling and the Kiirunavaara case is presented in Chapter 3. In Chapter 4 the results from the numerical modelling are presented. Discussions of the results are given in Chapter 5. Finally, Chapter 6 deals with conclusions, suggestions and a plan for a future validation project.

Plan for validation

Numerical modelling

Case study review

Literature study focused on cases in which measurements with the aim to calibrate, validate and verify the numerical analysis has been performed.

Study of where to measure and at what stage in relation to mining

Results and summary of above are the background for making a plan for validation of numerical analysis

Parametric study in which a parameter value is varied while the other parameter value are held constant

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2 REVIEW OF CASE STUDIES

2.1 Introduction

This Chapter presents a review of underground cases where calibration, verification or validation of numerical modelling and/or an evaluation of the rock behaviour or rock characteristic has been performed. Where possible, the planning of monitoring and modelling has also been described.

2.2 The Mine-by Experiment

The Mine-by Experiment was located at level 420 in the Underground Research Laboratory (URL) in Canada. The premise for the Mine-by experiment was to characterize a volume of rock and instrument it with the latest technology (1989-1995) in displacement monitoring and acoustic emission. The objective was to measure the excavation induced response by excavating a test tunnel through the instrumented volume (see i.e., Read, 1994). The test tunnel was located at 420 m below surface and had a diameter of 3.5 meter, see Figure 5. The uniaxial compressive strength of the intact massive grey granite was 147-198 MPa (Martin, 1997). The monitoring instrumentation used in the Mine-by experiment was: displacement monitoring (extensometers and convergence arrays), triaxial strain cells and thermistors (to measure temperatur) and acoustic emission/microseismic. The complete excavation-induced response of the rock mass was possible to monitor by pre-installing the instruments. However, the plan (why and where the equipment should be installed) for instrumentation and monitoring has not been published in any paper (to the author's knowledge).

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Figure 5 Arrangement of the tests tunnel at level 420 of the URL (Read et al., 1998)

A number of different stress determination techniques (overcoring, hydraulic fracturing, back analysis and acoustic emission monitoring) were tried at the same depth as the Mine-by experiment, but none of them produced a satisfactory estimate of the complete in situ stress tensor (Read, 2004). Individual components of the tensor were estimated and used to perform numerical modelling of the Mine-by Experiment. Numerical modelling was used to explain the in situ failure process (Martin et al., 1999). However none of the material models (used at that time) was capable of simulating the complex processes involved in the progressive failure (Read, 2004). Linear elastic continuum models were shown to be useful for rock mass modelling (with the exception of regions of failed rock near the surface of the tunnel). However, after the test had been completed attempts have been made to validate material models. For simulation of failure and fallouts in hard rock masses, the results of a Cohesion Softening Friction Hardening (CSFH) material model, in form of shear bands and yielded elements failed in shear, have shown good agreement with observations of spalling failure in field (in e.g. Hajiabdolmajid et al. 2002; Diederichs 2007).

2.3 Palabora mine

In the transition from open pit mining to underground mining for the Palabora mine in South Africa, numerical models (using the programs FLAC3D, PFC3D and 3DEC) were used for simulation of the caving process (Board and Pierce, 2009). The rock mass behaviour was described by the Mohr-Coulomb failure criteria (strength represented by

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cohesion and angle of friction) and by simulating strain-softening material. The strain-dependent strength properties were estimated through (i) GSI and Hoek-Brown strength envelope and also by (ii) simulating a synthetic rock mass (SRM). In an SRM model the intact rock is represented by bonded spheres in the Particle Flow Code (PFC3D). To reproduce the intact rock stress-strain response a calibration of the inter-particle bonds was performed. This was done by calibrating the modulus and peak strength parameters with laboratory data for uniaxial and triaxial loading conditions. For the studied case four networks of fractures (representing four major geotechnical domains) was “mapped” on top of the bonded spheres. The fracture network was constructed based on underground line mapping as well as open pit bench mapping. As a validation of the SRM methodology a back-analysis of the caving behaviour was conducted for the Palabora mine in order to validate the methodology. A large scale FLAC3D model of the open pit and the underground was developed. The strength and modulus anisotropy determined from SRM was included in the FLAC3D model. The mobilized and yield zones as a function of an undercut was studied and a verification of the model’s ability to simulate the vertical advance and shape of the cave was obtained by comparing the predicted results with results from acoustic emission measurements. The results from both modelling and measurements indicated a similar region of yielding in advance of the cave, see Figure 6. The yielded zone was predicted 50-80 m in extent beyond the mobilized zone. The results from the model showed comparable timing to the failure of the crown pillar (Sainsbury et al., 2008).

Figure 6 Predicted and measured progression of caving in the Palabora mine (from Sainsbury et al., 2008).

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2.4 Northparkes mine

As for the Palabora case (see Chapter 2.3), the Synthetic Rock Mass approach (SRM), was used for the Northparkes mine in Australia (Mas Ivars et al., 2011). In this case the SRM methodology was used to characterize the caving behaviour of different rock domains for a block caving area, see Figure 7. The undercut level in the area was at a depth of 830 m below surface and with a diameter of 200 m. The rock domains were defined according to location relative the caving zone and lithology. The intact rock properties for the four domains were obtained from standard uniaxial compression tests on 5 cm diameter core samples and then scaled to account for the average in situ rock block size.

Figure 7 FLAC3D simulation of the mobilized cave zone, for the Northparkes block caving area, showing the predicted yielded zone (from Board and Pierce, 2009).

The calibrated strength used for the SRM samples were 80% of the mean laboratory-measured intact rock strength (to represent a sample of size 20-100 cm). The discrete fracture networks were developed from tunnel and borehole scanline mapping. The joint frequency measures from the mapping were used to calibrate the discrete fracture network. The SRM method has been validated through comparison of the rock mass

Yield zone (in blue)

Caved (mobilized) zone

Undercut

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response for cave mining operation with microseismicity, yielding and fragmentation in the SRM samples. The properties obtained from the SRM tests/samples were used directly in the cave-scale production simulation. The stress changes caused by the mining were predicted using a mine-scale continuum model in FLAC3D. The jointed synthetic rock mass samples were subjected to the stress paths. It was found that significant effects on the cave shape and the rate of propagation could be obtained by variations in the rock mass joint orientation and persistence (Sainsbury et al., 2008).

2.5 Kidd Creek

The Kidd Creek mine site is located in Canada. It is owned and operated by Xstrata Copper (http://www.mining-technology.com/projects/kidd_creek). For stability analysis, in-situ measurements of in-situ stress, induced stress, deformation, blasting effects characteristics of rock masses and micro seismicity has been carried out already from the early stages at Kidd Creek (Yu and Croxall, 1985). In the 1980:s Finite Element Modelling (both 2D and 3D) and Boundary Element programs was used to predict the stress concentration in some of the more critical parts of the mine. The validation of the modelling was through comparing predicted results with underground observations (Yu and Croxall, 1985). The behaviour of a fault and the rock mass was examined by numerical modelling using a boundary element code (Fotoohi, 1993). The validation of the software was through comparing predicted results with results from numerical calculations. The modeling results showed good agreement with both observations and the seismic events in the field. However there are few data published concerning the validation and its process, which makes it difficult to judge whether this is a comprehensive and well performed case for validation.

2.6 Continuous monitoring in a mining panel in Colonsay

No numerical modelling was performed for the Colonsay case. However, this case has been included in this work since they performed a carefully planned and performed instrumentation of the mine with continuous monitoring over a long period. As a result of the instrumentation program a long term data base was established which in turn lead to rational decisions and considerable operational cost savings. Due to brine leakage in a mining panel at IMC Kalium operation in Colonsay, in 1978, stringent controls started to control the inflow (Souza et al., 1997). A geotechnical investigation program concerning exploration drilling, analysis of core logs, mapping of fractures etc. was initiated. To get information of the long term behaviour, of the grout

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and backfill system that was used to prevent brine leakage, an extensive instrumentation program was designed and installed. The instruments installed included extensometers in the roof, floor and pillar, stress meters, strain gauges, convergence meters, borehole pressure cells, earth pressure cells and piezometers. In Souza et al. (1997) the planning and design of the instrumentation program in Colonsay is described. The design of the instrumentation was based on information from previous studies undertaken in the area of the brine leakage.

2.7 Experiments at the Stripa Mine

The goals of the Stripa Project (1980-1992) were to develop techniques to characterise a granitic rock mass with regards to its hydrological and geochemical properties and to study its behaviour under heating conditions and to develop techniques. A site characterisation and validation project was set up aimed at studying the ability to characterise the structures and to quantify the groundwater flow through the site (Olsson, 1992). The investigated site (validation drift) was located at 380 m below ground. A conceptual model of the site was used as input to different numerical models. By comparing the model predictions and measured results a validation process was set up. The following definition of validation was adopted (Gustafson, 1992): “A model is considered to be validated for use in a given application when a model has been determined by appropriate measures to provide a representation of the process or system that is acceptable to an assembled group of knowledgeable experts for purposes of the application.” The application for this case was ground-water flow and transport in the site and comparison of model calculations and results from field observations and/or experimental tests was the appropriate measure. The distribution of water flow through a volume of granitic rock was predicted before and after excavation of a validation drift. The preliminary data gathering were performed through drilling and investigation of 5 boreholes from existing drifts in the mine (N2-N4 and W1-W2 in Figure 8).

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Figure 8 Overview of the validation drift and the different boreholes for data gathering.

A conceptual model of the site was set up and four preliminary numerical predictions of groundwater inflow started for the non-excavated validation drift. The next step was to drill five boreholes (C1-C5 in Figure 8) in order to provide data for more detailed predictions of the inflow to the validation drift. Six 100 meter long parallel boreholes (D-holes in Figure 8 and Figure 9) were drilled and outlined a 2.4 m cylinder in the site and the inflow was measured. The conceptual model was continuously updated based on the additional data and in turn, used as input to the numerical models. At the latest stage the validation drift was excavated for the first 50 m of the cylinder outlined by the D-boreholes (Figure 9).

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Figure 9 The 100 m long D-boreholes and the excavated validation drift.

Four different research groups worked with the numerical modelling. All models included the data from structures and fractures, investigated/characterized at site. Based on the field experiment, the flow of the drift was 1/8th of the flow corresponding to the flow in the D-boreholes. The main cause for this was a two-phase flow condition due to degassing of the groundwater together with drying. The modelling of the inflow were not successful due to inadequate understanding of the hydrology of the disturbed

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zone around drifts. As a summary result from the Stripa project, the predicted values of the inflow were in general larger than the measured. However this test drift offered a great opportunity for long-term recording, observation and a possibility for evaluating the process for validation of results from numerical analysis.

2.8 The Äspö Pillar Stability Experiment

The Äspö Pillar Stability Experiment (APSE) was carried out during 2002 to 2006 to examine the failure process in the rock mass when subjected to coupled excavation-induced and thermal-induced stresses (Andersson, 2007b). The findings from the URL in Canada were used as guides for the planning and design of the pillar stability experiment. In APSE the rock mass was heated by electrical heaters and acoustic emission, displacement and thermal monitoring systems were installed to follow the yielding of pillar caused by the temperature rise. The pillar was created by excavating two large deposition holes (1.75 m diameter and 6.5 m deep) with a spacing of 1 m, see Figure 10. The holes were excavated at 450 m level of the Äspö Hard Rock Laboratory. The intact diorite had a mean value of the uniaxial compressive strength of 211 MPa. The state of stress was determined from overcoring and hydraulic fracturing results.

Figure 10 Layout of the ASPE at 450 m level (modified from Andersson, 2007a).

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One of the first steps in the experiment was to perform calculations of the required stress magnitude to induce damage in the pillar and designing the holes and the nearby region to achieve these target stress magnitudes. This was followed by predictive models to select where and what monitoring technique should be installed, but also to be able to compare preliminary predictions with the observed response of the rock mass. Rocscience software (Phase2, Examine3D) was used to establish the geometry of the pillar, while JobFem (Stille et al., 1982), FLAC3D and FRACOD (Shen et al., 2005) were used in the predictive modelling. The thermal induced stresses were back-calculated using the finite element program CODE_BRIGHT (CIMNE 2000). Acoustic emission events were recorded in the second excavated hole and the propagation of spalling could be monitored. Displacement was monitored on the wall of the second hole, using Linear Variable Differential Transformer (LVDT). Hence, based on the measured results, a comparison of the calculations and predictions could be performed (verification according to Andersson, 2007b). In Figure 11 the determined maximum principal stresses using Examine3D is presented for two different stress directions. The location of acoustic emission events and the observed failed region is also hatched in Figure 11. Based on the determined, observed and monitored data, it can be seen that the predictions were useful in order to understand and give an indication of where and how much the rock should fail. The main aim of this project was not to validate numerical analysis, rather the models were used to understand how and where to install the monitoring equipment. The amount of data made in possible to compare observed behaviour of the rock mass with calculations. However the process of determining the degree to which this model was an accurate representation of the real world is not complete and a correct validation of numerical models was not performed.

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Figure 11 Calculated maximum principal stress together with the observed geometry of the failed region (v-notch) and the location of all acoustic emission event located at the curtain depths (from Andersson, 2007a).

2.9 Monitoring and measurements at Boliden

According to the Boliden rock mechanics staff, numerical analysis has never been used, with the purpose to validate a model, before monitoring (Sandström et al., 2011). However, conducting monitoring followed by calibrating the numerical model with the measured results has been applied in several cases. This has for instance been the case for Boliden projects such as G2000 (in e.g. Nyström, 1991 and Nyström and Rådberg, 1991) and the Näsliden project (Stephansson, 1981). The calibration of models in the G2000 and the Näsliden project has been used for future prognoses of the effect of mining. In the Lasivall pillar test, stress measurements were performed and evaluated during excavation of the pillars. In an ongoing rock reinforcement project, the rock mass and its interaction with rock support has been studied in the Kristinebergs mine in 2010 (Nordlund et al., 2011). Also for this case the results from the measurements were used to calibrate numerical models.

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2.10 Monitoring and measurements at LKAB

2.10.1 Kiirunavaara

In the Kiirunavaara mine both deformation and stress measurements have been performed and compiled (see e.g., Björnfot, 1983a and 1983b; Jacobsson, 2005; Lundman, 1998; Sandström, 2003). Grouted rock bolts and their interaction with the surrounding rock were studied in a field test performed between 1980-1982 at 514 m level (285 m below the horizontal ground surface). A 20 m long section in a test drift in the foot-wall was instrumented with 20 bolts mounted with strain gauges and 50 bolts combined with single-anchor extensometer (Björnfot and Stephansson, 1984). The rock movements were measured with 23 borehole extensometers and 45 convergence measurement stations while 14 stress monitors recorded the changes in stresses. The mining activity during the 20 month long field study is shown in Figure 12.

Figure 12 The mining activity during the time of the field test (1980-1982) in the Kiirunavaara mine (from Björnfot and Stephansson, 1984).

The data recorded were compared with the results from a linear elastic finite element model. A global-local model was used (see Figure 13) where the input data for the local model (vicinity of the test are) was from a global model of the entire mine area (Larsson, 1983). The mining and the global-local model was simulated in five steps.

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Figure 13 The Global-local approach used for the test in 1980-1982 in the Kiirunavaara mine (Björnfot and Stephansson, 1984).

Based on the comparison between calculated and measured stresses in the roof of the test drift (see Figure 14), a fairly good agreement was found if the effect of creeping of the gauges was ignored (Björnfot, 1983b). However a good agreement was not found between results from calculations and recordings for the tangential stress in the wall. For the calculated and measured deformations in the rock mass, the recorded displacements were much larger than the calculated values. However this test drift offered a great opportunity for long-term recording, observation and a possibility for evaluation of the calculated results from numerical analysis.

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Figure 14 Measured changes in tangential stresses for three points in the roof of the test drift together with calculated results from the Finite Element Model (Björnfot and Stephansson, 1984).

In the Oscar project (performed in the end of 1980’s and beginning of 1990’s) a 3D numerical modelling was conducted of a test mining method (Jing and Stephansson, 1990). The results from the numerical model were validated either quantitatively by comparison with the in-situ measurements of qualitatively by comparison with underground observations. Based on a representative model that agreed well with measured displacements and stresses a new stope lay-out and mining sequences could be studied and evaluated.

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In order to examine the change of a new mining layout in 2005 a field test was performed. For the new mining layout a thin pillar was left between two access drifts. Extensometers and convergence measurements were used to record the movements of the pillar (Jacobsson, 2005). Examine2D was used to predict the pillar stresses. A global-local model was used where the access drifts represented the local area. Based on the predicted results, the stresses should increase in the middle of the pillar when the mucking started at one level above the studied level. The selection of place to perform deformation measurements was based on the results from the numerical modelling (Jacobsson, 2005). Hence, for this case, numerical analysis was used to select the best place for monitoring. As a result from the comparison between recorded data and calculated values, a 3D-model seemed to be necessary to use in order to capture the rock mass behaviour. The calculated results were not validated in Jacobsson (2005).

2.10.2 Malmberget

Different studies concerning failure and structure mapping, fallouts and the rock reinforcement have been performed in Malmberget during the last years (in e.g. Ersholm and Öberg, 2008 and Sundström, 2010). The propagation of the caving, caused by high stresses in a hard rock, has been studied recently for the Printzsköld ore body (Wettainen, 2010). Instruments will be installed during 2011 in the Malmberget mine in order to study the behaviour of the rock and support when subjected to dynamic changes and to build and calibrate numerical models (Nordlund et al., 2011). However, in these cases, validation of numerical models has not been performed. To the author's knowledge there are no cases where validation has been attempted for the Malmberget mine.

2.11 Summary of case studies

In many of the cases presented, calculated values have been compared with observations or measured data. Often this has been (incorrectly) named validation or verification by the authors. The process of determining the degree to which the different models has an accurate representation of the real world is only complete for the Stripa case and a stringent validation of numerical analysis has not been performed for the others. However the focus of the Stripa case was on hydrological and geochemical properties of the rock mass, which was not the primary scope of the present study.

22

The most comprehensive works performed in the field of rock mechanics, monitoring and numerical analysis were the Mine-by Experiment and the Äspö pillar stability experiment. Also the tests performed in the Kiirunavaara mine in the 1980s are good examples of comparisons between actual behaviour and calculations. However, none of these can be considered "validations" with the definitions employed in this study. The cave modeling for the Palabora and Northparkes mines were denoted validation cases according to the respective authors, and are probably the best candidates for this, of those cases presented in this report. The Palabora and Northparkes cases constituted validation of a caving algorithm developed for a continuum modeling approach, with input data derived from SRM (Synthetic Rock Mass) modeling. Thus, the discontinuum character of caving was not explicitly modeled and thus not validated. Clearly, there is a need for a systematic validation study also for the more conventional stress modeling conducted at LKAB.

23

3 CASE STUDY – THE KIIRUNAVAARA MINE

3.1 Model setup and input data

The numerical code used in the numerical study was FLAC (Itasca, 2008). Since the width of the excavations in the local model are relatively small compared to the length of the opening (assuming plane strain condition) a 2D-model has been used.

A global-local modelling approach was used, in which the boundary stress conditions for the footwall drifts were extracted from a global model (Sjöberg and Malmgren, 2008), see Figure 15. This approach was necessary to take into account stresses induced by sublevel caving, while keeping the overall model size reasonable. The calculated stresses from the global model were then used as boundary conditions for the local model and the footwall drifts.

Boundary stresses fromglobal model

H H

Global model

Local model of access drift

Local model

Drift

Figure 15 Global-local modelling approach for the Kiirunavaara sublevel caving mine (after Sjöberg and Malmgren, 2008)

24

In the global model, single drifts, ore passes etc were not included and only the effect of stress redistribution caused by the sublevel cave mining front was studied. The virgin rock stresses were determined based on the compilation and interpretation of all conducted measurements in the mine by Sandström (2003) as y =0.029y + 2.9 [MPa], x =0.037y + 3.7 [MPa], and z =0.028y + 2.8 [MPa] where y is the depth below 100 m ("zero level" of the surface is taken to be at the 100m depth). The width of the ore has been approximated as 160 meter. The rock strength parameters were based on internal reports from LKAB (Sjöberg, 2007), and are shown in Table 1.

Table 1 Input parameters for the global model

Parameter Hangingwall Ore Footwall

Young’s modulus [GPa] 70 65 70

Poisson's ratio 0.22 0.25 0.27

Cohesion [MPa] 5.18 4.81 6.67

Friction angle [degrees] 50.7 50.7 52.9

Tensile strength [MPa] 0.71 0.48 1.30

The drifts on level 1165 were analysed with respect to the virgin stresses and changes in stresses when production is (or the opening of a level has started) five levels above (1050 m) to one level below (1194 m) see Figure 16.

25

Figure 16 Schematic picture of the studied footwall drift at level 1165 for different level of production. The studied drift is marked with a dotted line/square.

Since the stresses and their orientations around the footwall drifts are a function (in addition to the location of the active mining level) of the distance between the footwall and the footwall drifts, different locations (distances from the footwall contact) of the footwall drifts were studied. Figure 17 shows an example of the predicted stresses at level 1165 m plotted for different level of production. Consequently, the stresses shown in Figure 17 can be used as boundary stresses in the local model of a footwall drift.

1165 1137

1108 1079

1050

1194

Level 1050 open Level 1079 open Level 1108 open

Level 1137 open Level 1194 open Level 1165 open

26

Figure 17 Calculated stress (xx) at the location of the footwall drift on level 1165 m, and for different distance from the footwall contact, and for different mining steps.

In the local model, only single drifts with a planned and analysed cross section as in Figure 18 were simulated.

Figure 18 Planned cross-section of footwall drifts.

Based on the results from the global model and also on the most common used distance in reality of drifts situated in the footwall, two distances from the ore boundary were

7.00

6.00

1.00

[m]

0.50

R=4.55

3.50 3.48

45º

27

studied, namely 20 m and 60 m. The input stress data from the global model are shown in Figure 19 and the strength and elastic parameters of the local model are given in Table 2.

-10

0

10

20

30

40

50

60

70

80

sigma xx 20

sigma yy 20

tau xy 20

1050 1079 11371108InsituOpened level

[MPa]

xx

xy

yy

Distance from ore contact = 20 m

1165 1194

-10

0

10

20

30

40

50

60

70

80

sigma xx 60

sigma yy 60

tau xy 60

1050 1079 11371108InsituOpened level

[MPa]

xx

xy

yy

Distance from ore contact = 60 m

1165 1194

Figure 19 Input stress data for drifts at level 1165 at a distance of 20 m and 60 m from

the ore contact.

28

Table 2 Input parameters for the local model (Malmgren and Sjöberg, 2006)

Parameter Footwall (Base case)

Young’s modulus [GPa] 70

Poisson's ratio 0.27

Cohesion [MPa] 10.2

Friction angle [degrees] 58.2

Tensile strength [MPa] 2.23

3.2 Parametric study

In the Kiirunavaara mine, there can be large variations in the stress-, strength- and stiffness parameters. Based on Sandström (2003) the variations in stiffness and the strength of the rock mass influence the development of failure at least to the same extent as the variation of the virgin stress state. Hence, in this study the influence of the stress variation has not been studied. In order to evaluate the relative importance of different strength and stiffness parameters a parametric study was performed. Also a comparison between results using large strains or no large strains in the FLAC code was performed. The strength parameters used for the footwall drifts in the Kiirunavaara mine case are presented in Table 3. In this case, the rock mass strength is the uniaxial compressive strength in large scale for the linear Mohr-Coulomb strength envelope. Table 3 Applied strength parameters for the footwall drifts in the Kiirunavaara mine

(Perman and Sjöberg, 2011).

Strength parameter Low 1 Low 2 Base case High 1 High 2

Cohesion [MPa] 4.90 6.67 10.2 12.8 19.9

Friction angle [degrees] 49.5 52.9 58.2 58.9 60.2

Tensile strength [MPa] 0.66 1.30 2.23 3.32 6.02

Rock mass strength [MPa]

26.6 39.8 71.6 92.0 149.6

The significance of Young's modulus was examined by varying the stiffness parameter according to Table 4, while keeping the Poisson’s ratio constant (ν=0.27).

29

Table 4 Input stiffness parameter used for the footwall drifts in the Kiirunavaara mine.

Young's modulus [GPa]

Low 1 10

Low 2 30

Low 3 50

Base case 70

High 80

30

31

4 MODELLING RESULTS

In this work the stress, displacement and yielding has been calculated and evaluated. The yielding around the drifts was calculated in order to study the excavation damage zone (EDZ). All parameters have been calculated around the drifts for different distance from the ore contact. In order to evaluate the best position to measure on the drift boundary, seven different directions were selected for which more detailed data of the stress and displacements were calculated.

4.1 Drifts at different distance from the ore contact

Drifts at a distance of 20 m and 60 m from the ore contact were studied. In Figure 20 the contour of determined maximum principal stresses for the footwall drifts, at distance 20 m and 60 m from the ore contact, are presented. When the opening of level is three levels above the studied drift the highest stress concentration is in the roof. Then, for every continued mining step, the highest stress concentration is towards the ore direction. A more detailed comparison of stress results for three different directions (upper left and upper right corner and roof) in drifts at 20 m distance and 60 m distance from the ore contact is shown in Figure 21. The trend in the result is almost the same for the studied drifts despite the different distances from the ore contact (except for level 1194). However the calculated stress values are higher for drifts closer to the ore. In Figure 22 the maximum principal stress in the roof for three different production levels and drifts at 20 m and 60 m distance from the ore contact is presented. Based on the results presented in the Figures described above it seems to be easier to capture the largest variations and larger values for drifts closer to the ore contact. The results of calculated x- and y-displacements also indicated higher predicted values for drifts closer to the ore compared to those located farther from the ore contact. The higher predicted displacement values were more obvious in later production stages compared to earlier stages, as can be seen in Figure 23.

32

Drifts at closer distance to the ore contact had a larger zone of yielding in the nearby region compared to drifts at a longer distance from the ore contact, see example in Figure 24. The yield in shear or volume and the yield in tension are shown together in Figure 24. A shorter distance between the ore contact and the drift also results in more yielding in tension. Hence based on the result of stress, displacement and yielding, in the continued work drifts at 20 m distance from the ore contact will be studied.

33

Level

open

20 m from ore contact 60 m from ore contact

1050

1079

Figure 20 Calculated maximum principal stresses for the footwall drifts, at distance 20 m and 60 m from the ore contact, when the

production is at different level.

34

Level

open


1108

1137

Figure 20 (continued).

35

Level

open


1165

1194


36

20 m distance from ore contact 60 m distance from ore contact

Base case 20 m from ore contact

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5

Distance from tunnel boundary

Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[m]

[MPa]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imum

prin

cipa

l str

ess

1050

1079

1108

1137

1165

1194

Level open

[m]

[MPa]

Figure 21 Calculated maximum principal stress for drifts at 20 m and 60 m distances from the ore contact.

37


-20

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tre

ss 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


-20

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


38

Base case

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s

1050_20m

1050_60m

1108_20m

1108_60m

1194_20m

1194_60m

Level open

[m]

[MPa]

Figure 22 Calculated maximum principal stress for three different production levels and for two different distances to the ore contact.

Base case

-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Y-d

isp

lace

me

nt

1050_20m

1050_60m

1108_20m

1108_60m

1194_20m

1194_60m

Level open

[m]

[m]

Figure 23 Calculated y-displacements in the roof in drifts at distance 20 and 60 m from the ore contact for three different production steps.

39

Opened level 1165

20 m from ore

contact

(Base case cm = 71.6, Em=70)

60 m from ore

contact

(Base case cm = 71.6, Em=70)

Figure 24 Yielding around the footwall drifts at level 1165, at distance 20 m and 60 m from the ore contact, when the production has started at the same level.

4.2 Evaluation of best positions to measure in a drift

For the drift at 20 m distance from the ore contact, seven different directions (see Figure 25) were selected for which stress data and displacements were calculated. The red lines in Figure 25 represent a depth of 3.6 m from the tunnel boundary. The chosen length of the red lines was based on results in Figure 20, for which the distance from the boundary should be longer than the distance (from the boundary) to the

40

location of the largest stress concentration in that direction. The four lines in the corners have an angle of 45 degrees from the horizontal. The results of the calculated maximum principal stress for the different directions are presented in Figure 26.

Figure 25 Directions for which stresses and displacements are calculated in the footwall drift.

Based on the maximum principal stress in Figure 26 the largest difference of highest and lowest values was found for the lower left corner, the roof and the upper right corner. In the roof, the maximum principal stress increases from opening of level 1050 to opening of 1108 and then it decreases with a large drop when opening of level 1137 starts. In the upper right corner, the stress decreases for every mining step and for opening of level 1165, tensile stresses develop closest to the boundary. Also for the lower left corner, the highest calculated value is for the opening of Level 1050 and then the stresses decrease with the mining. For the lower left corner and the upper right corner the highest values are close to the tunnel boundary. At a distance of 1-1.5 m from the boundary the stress curves tend to flatten. However there is a larger zone with higher values in the roof (curves flatten out at a distance of 2.5-3 m from the boundary). A summary of the highest and lowest values of the maximum principal stress together with the largest difference between two consecutive levels of production are presented in Table 5. The largest difference between two production levels was calculated for the lower left corner, the upper left corner, the roof and the upper right corner.

5.46 1.63

[m]

2.3 3.5

3.6

45º

41


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al str

ess 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[m]

[MPa]

Figure 26 Calculated maximum principal stress for the different directions in Figure 25.

42


-20

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s 1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Maxi

mu

m p

rin

cip

al s

tres

s

1050

1079

1108

1137

1165

1194

Level open

[MPa]

[m]

Figure 26 (Continue)

43

Table 5 The calculated highest and lowest values of the maximum principal stress and the largest difference between two consecutive levels of production (drifts at 20 m distance from ore contact).

Direction Highest value [MPa] Lowest value

[MPa]

Largest difference*

[MPa]

183 (Level 1050, close to

the boundary)

0.6 (Level 1194, 1-2.5 m

from boundary)

69 (between Level 1108

and 1137)

70 (Level 1165, 2 m from

boundary)

0.4 (Level 1194, close to

the boundary)

18.5 (between Level

1194 and 1165)


the boundary)

76 (Level 1050, 3.6 m

from boundary)


and 1165)

180 (Level 1108, 0.4 m

from boundary)


boundary)


and 1137)

120 (Level 1050, 0.4 m

from boundary)

-6 (Level 1165, close to

boundary)

60.5 (between Level

1137 and 1108)

66 (Level 1165, 2.5 m from

boundary)

0.6 (Level 1194 close and

near the boundary)


and 1050)

145 (Level 1108, 0.2 m

from boundary)

66.5 (Level 1050, 3.6 m

from boundary)


and 1050)

* Largest difference between the maximum principal stresses for two consecutive levels of production.

The displacement vectors for drifts at 20 m distance from the ore and for the different production steps are shown in Figure 27. Based on the vectors, the drift seems to increase in size in the lower right corner and decrease in size in the upper right corner.

44

Level open

20 m from ore contact Level Open

20 m from ore contact

1050

1137

1079

1165

1108

1194

Figure 27 Calculated displacements vectors for drifts at distance 20 m from the ore contact.

As for the stresses, the displacements were calculated in the seven positions shown (in Figure 25). The calculated vertical (y) displacements for the seven directions can be seen in Figure 28. The highest y-displacements were predicted for the upper right corner, the right wall and the lower right corner. For all positions/directions the y-displacements increased for every production step. The largest difference between two consecutive levels of production was calculated for the upper right corner, the right wall and the lower right corner. This largest difference was predicted for when production started at level 1194 compared to level 1165, see Table 6.

45


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]

Figure 28 Calculated vertical (y)-displacements at distance 20 m from the ore contact.

46


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


y-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


47

Table 6 Calculated highest and lowest values of the vertical (y) displacements and the largest difference between two consecutive levels of production (drifts at 20 m distance from ore contact).

Direction Highest value

[mm]

Lowest Value

[mm]

Largest difference*

[mm]

-68 (Level 1194) -14 (Level 1050) 16 (Between Level 1165 and

Level 1137)


Level 1137)


Level 1108)


Level 1165)


Level 1165)


Level 1165)


Level 1165)

* Largest difference of calculated vertical (y) displacement between two consecutive levels of

production.

The calculated horizontal (x) displacements for the seven directions can be seen in Figure 29. The highest values were predicted in the lower left corner, the left wall and the lower right corner when Level 1194 had opened. All directions resulted in the same largest difference of x-displacements (10-13 mm) between Level 1137 and Level 1165 except for the right wall (4 mm). A summary of the highest and lowest values of the x-displacement together with the largest difference between two consecutive production levels are presented in Table 7.

48


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


x-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


x-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


x-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


X-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]

Figure 29 Calculated horizontal (x) displacements at distance 20 m from the ore contact.

49


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


x-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


x-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


-0,02

-0,01

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


x-d

isp

lace

men

t

1050

1079

1108

1137

1165

1194

Level open

[m]

[m]


50

Table 7 The calculated highest and lowest values of the horizontal(x) displacements and the largest difference between two consecutive production levels (drifts at 20 m distance from ore contact).

Direction Highest value

[mm]

Lowest Value

[mm]

Largest difference*

[mm]

52 (Level 1194) 13 (Level 1050) 11 (Between Level 1165 and

Level 1137)


Level 1137)


Level 1137)

29 (Level 1108) -3 (level 1194) 10 ( Between Level 1165

and Level 1137)

23 (Level 1108) -7 (Level 1194) 10 ( Between Level 1165

and Level 1137)

11 (Level 1108) -14 (Level 1194) 4 (Between Level 1165 and

Level 1137)


Level 1137)

* Largest difference of the calculated horizontal (x) displacement between two consecutive levels of

production.

4.3 Significance of strength and stiffness variation

The input data for the parametric study has been according to Table 3 and Table 4 in Chapter 3. Since the cases with low strength values required that large strains should be allowed in the FLAC code, a comparison of the analysis result for the base case was performed, see example in Figure 30 and Figure 31. The differences between using large strain mode or not was small for both displacement and stresses; hence, relevant comparisons can be made between the models with different strength parameters.

51


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s

1050

1050 (large def)

1108

1108 (large def)

1194

1194 (large def)

Level open

[m]

[MPa]

Figure 30 Calculated maximum principal stress for three levels for calculations with and without large strain model in FLAC.


-0,15

-0,12

-0,09

-0,06

-0,03

0,00

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Y-d

isp

lac

em

ent

1050

1050 (large def)

1108

1108 (large def)

1165

1165 (large def)

Level open

[m]

[m]

Figure 31 Calculated vertical (y) displacements for three sublevels for calculations with and without large strain model in FLAC.

To study the significance of variation of different strength and stiffness parameters of the rock mass, the maximum principal stress was calculated for three positions (the upper left corner, the roof and the upper right corner), see Figure 32 - Figure 34. Based on the result presented in these Figures the stiffness parameter had no or little significant influence on the result for the calculated maximum principal stress, whereas the strength of the rock mass had a large influence on the result. The effect of the stiffness increased when the mining approached the studied level of the drift (level 1165) and with lower values of the stiffness parameter (e.g. E=10GPa).

52

Level open Calculated stress in upper left corner

1108

20 m from ore contact, Level open 1108

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[MPa]

[m]

1137


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Ma

xim

um

pri

nc

ipal

str

es

s

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[MPa]

[m]

1165


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[MPa]

[m]

Figure 32 Calculated maximum principal stress in the upper left corner for the base case and for cases with high and low strength value and a high and low stiffness value.

53

Level open Calculated stress in the roof

1108


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al st

ress

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[m]

[MPa]

1137


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Maxi

mu

m p

rin

cip

al s

tres

s

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[m]

[MPa]

1165


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al

stre

ss

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[m]

[MPa]

Figure 33 Calculated maximum principal stress in the roof for the base case and for cases with high and low strength value and a high and low stiffness value.

54

Level open Calculated stress in upper right corner

1108

20 m from ore contact, Level 1108 open

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Maxi

mu

m p

rin

cip

al s

tress

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[MPa]

[m]

1137


0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tres

s

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[MPa]

[m]

1165


-20

0

20

40

60

80

100

120

140

160

180

200

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


Max

imu

m p

rin

cip

al s

tre

ss

Base case

sigmacm 40

sigmacm 92

E 50

E 80

Strength

[MPa]

[m]

Figure 34 Maximum principal stress in the upper right corner for the base case and for cases with high and low strength- and high and low stiffness value.

The significance of variation in parameters was also studied for the vertical displacements in the roof for four different levels of production, see Figure 35. Using cm = 40 MPa and E = 80 GPa resulted in almost the same result as the base case.

55

Level open Calculated vertical (y) displacements in the roof

1108

1137

1165

1194

Figure 35 Calculated y-displacements in the roof for the base case and for cases with high and low strength value and a high and low stiffness value.

In Figure 35, the lower Young’s modulus (E=50 GPa) had the largest effect on the y-displacements for all studied levels. A lower stiffness parameter results in larger

56

calculated displacements compared to higher stiffness values. For opening of level 1165 and level 1194, also the highest strength value (cm = 92 MPa) showed effect on the result. For deeper production levels the effect of both stiffness and strength parameters increases. The calculated horizontal (x) displacements in the roof for four different levels of production and the different strength and stiffness parameters are presented in Figure 36. The lowest strength value of the rock mass (cm = 40) showed the greatest effect on the x-displacements. For deeper production levels the effect increases. A summary of the maximum displacement vectors and yielding at Level 1165 for the different strength parameters and stiffness parameters used in this study are presented in Figure 37 and in Figure 38. Changing the stiffness had no significant influence on the amount of yielding around the footwall drift, but affected, to a large extent, the maximum displacements around the drift.

57

Level open Calculated x-displacements in the roof

1108

1137

1165

1194

Figure 36 Calculated horizontal (x) displacements in the roof for the base case and for cases with high and low strength value and a high and low stiffness value.

58

Level open 1165

Yielding (plasticity) Maximum displacement vectors

Low stiffness cm = 71.6 MPa, Em=10 GPa

653 mm


248 mm


148 mm

Base case cm = 71.6 MPa, Em=70 GPa

104 mm

High Stiffness cm = 71.6 MPa, Em=80 GPa

91 mm

Figure 37 Yielding and the calculated maximum displacement vector of the footwall drifts at level 1165, at distance 20 m from the ore contact, for different stiffness parameters.

59

The strength of the rock mass had great influence on the both yielding and maximum displacement and lower strength results in larger region of plasticity and large displacements see Figure 38. When the strength of the rock mass is very high (cm = 150MPa) the yielding still exist in the left and right wall. Hence it is preferable to measure the yielding in the walls of the drifts. This is also the case for drifts at a longer distance from the ore contact (see Figure 24).

60

Level open 1137

Yielding Maximum displacement vectors

Low strength cm = 26.6 MPa, Em=70 GPa

868 mm

Low strength cm = 39.8 MPa, Em=70 GPa

1700 m

Base case cm = 71.6 MPa, Em=70 GPa

72 mm

High Strength cm = 92 MPa, Em=70 GPa

61 mm

High Strength cm = 149.6 MPa, Em=70 GPa

59 mm

Figure 38 Yielding of the footwall drifts at level 1165, at distance 20 m from the ore contact, for different strength of the rock mass.

61

5 DISCUSSION

In this feasibility study the mining-induced stress, deformation and yielding around footwall drifts in the Kiirunavaara Mine has been studied through numerical modelling. The hypothesis concerning how and when measurements should be performed to be able to validate numerical models, is that the measurements should be performed in regions/sections where the studied parameter exhibit large gradients/variations. Based on this study it was concluded that the shorter the distance between the drift and the ore contact, the higher the values of the calculated stress and deformation and the larger amount of yielding could be expected. Hence, it is preferable to measure in drifts located close to the ore. Of the seven studied directions to measure stresses, the best positions are marked in Figure 39. In the roof high values were predicted as well as large difference in values between two consecutive mining stages. Also, the roof had a larger zone/deeper depth of high values and variation (3 m). Since the highest stress value was found for the opening of level 1108, it is necessary to install the monitoring equipment in the roof when the production is (or opening has started) two production levels above the studied drift.

Figure 39 Best positions to measure stresses.

5.46 1.63

[m]

3.5

3

45º 1.5

Best position

Second best position

62

For both the upper right corner and the lower left corner the highest stress values were calculated for the opening of level 1050. The largest difference between two consecutive levels of production was predicted for level 1108 and level 1137. Hence for these two directions it is important to install the monitoring equipment when the production is three mining levels above the studied drift in order to capture all significant variations. In the upper left corner the largest difference in stress between two consecutive sublevels could be expected for opening of level 1194 compared to level 1165. Also the highest value was expected for level 1194. The installation of stress monitoring equipment could be performed one level above the studied drift. However the upper left corner shows the lowest stress value of the four positions in Figure 39 and also less difference between the sublevels. Hence, the upper left corner is the least recommended position of these four. Stresses are measured indirectly through strain measurements while displacement is a quantity that can be directly measured and compared with the results from a numerical analysis. Stresses play an important role as boundary conditions (loading situation) in existing numerical modelling. There are also more experience in comparing stress with strength in different failure criteria and analysis. Based on this study high values and large variation was predicted for the stress and hence it is still an important parameter to measure. By measuring both stresses and deformations more data can be collected that in turn will contribute to a better validation of numerical models. This study recommends that the stress should be measured during some years in order to capture the influence of mining. The LKAB-investigation concerning methods and preliminary costs for rock stress monitoring over time (Andersson, 2011) could be studied as a complementary information concerning the selection of method for continuous (and automatic/on-line) monitoring. Also the first results from the HLRC-project: “ANALYSIS OF THE MINING INDUCED SEISMICITY AT KIIRUNAVAARA MINE” could be used as complementary information. This project is currently being started, and will comprise stress measurements at several locations in block 33. In order to follow the change in the stress field over time stress monitoring equipment will be installed. Since, the instruments will be used for at least the same time it takes for one production level to be mined out, an evaluation of continuous stress monitoring can be performed. This in turn can be relevant information in order to be able to validate results based on continuous monitoring.

63

Displacement is a quantity that can be directly measured and compared with the results from a numerical analysis. The best positions for determining the x- and y-displacements are shown in Figure 40. The smallest displacement values were found for opening of level 1050 while the largest displacements were predicted for level 1194. The lower right-hand corner is the best choice for monitoring both the x- and y-displacement. The highest values of the y-displacements are larger (124-138 mm) than the x-displacement (48-57 mm). Also the difference in value between two constitutive levels of production is larger for the y-displacements (31-37 mm compared to 11-13 mm for the x-displacement). Hence it could be easier to study high deformations and displacements and their variation in the positions which are best for the y-displacements in Figure 40. Based on this study it seems that the values of the displacements do not change from the boundary and farther into the rock mass, implying that convergence measurements could be preferable. However the measuring points should be anchored deeper in the rock, in a borehole, in order to ensure that the rock mass response is measured. Short extensometers in the rock mass could also be used. Complements to traditional deformation measurement are laser scanning and digital stereo-photogrammetry which are available or existing equipment at LKAB. The largest change in displacements between two sublevels was for level 1137-1165 and 1165-1194. Hence the displacement monitoring equipment should be installed in the studied drift when the production has started one to two levels above.

Figure 40 Best positions to measure displacements.

Despite a long distance between the drift and the ore contact and despite a very high simulated rock mass strength (150 MPa), yielding could be predicted in the walls of the drifts. From these results it is concluded that the best positions to measure EDZ are in

5.46 1.63

[m]

2.3

45º

b) y-displacement

[m]

2.3

a) x-displacement

Best position

Second best position

Ore

64

the walls, as seen in Figure 41. If the drift is close to the ore, the upper right-hand corner also seems to be a good position to measure yielding. The EDZ could be observed by visual observations in boreholes, by drill cores and measured by more sophisticated methods such as vibration and ultrasonic monitoring or the ground penetrating radar method (Silvast and Wiljanen, 2008).

Figure 41 Best positions to measure yielding (or EDZ).

In general, whether it is stress, deformation or EDZ monitoring, the installation of such equipment needs to be “marked” in the mine map already at the planning stage of the drifts. Based on “practical” experience from both Malmberget and Kiirunavaara mine, the equipment can be (accidently) removed if the workers do not know about the continuous performed monitoring or the purpose of the measurements. Information about the measuring campaign, to those who work underground, is important in order to obtain reliable (or any) results. Other things to consider when planning the measuring campaign are that the complete monitoring system should contain some extra monitoring points to ensure redundancy, e.g., in the case that the equipment gets damaged through for example environmental causes such as corrosion, temperature, blasting and/or traffic. The production at one level starts with an "opening-phase" where the blasts starts at the hangingwall and progresses towards the footwall. The "opening-phase" is finished when connection has been established with the cave and the ore and the hangingwall are cut off. The most significant stress redistribution occurs for the opening of a new level. The installation of monitoring equipment needs to be performed when the production is (or opening has started) two-three levels above the studied drift in order to study the variations in results when a new level is opened. Therefore, the monitoring needs to be continuous, but the frequency of taking readings after opening of a new level needs to be about once a week in order to see that the equipment behaves as expected.

5.46

[m]

2.3

45º Best position Second best position

Ore

65

6 CONCLUSIONS AND SUGGESTIONS FOR FUTURE WORK

Based on this feasibility study it is more preferable to measure in footwall drifts close to the ore compared to drifts located farther from the footwall contact. The best position for measuring the stress with time is in the roof of the footwall drift. The displacements are preferably measured in the upper corner, the wall and the lower corner opposite to the direction of the ore. The EDZ should be measured in the walls of the drift. The strength of the rock mass had a large influence on the calculated stress and displacement values, as well as on the amount of yielding. The Young´s modulus had a large effect on the displacements, especially for low stiffness values. The suggestion for future work is to start a validation project of existing material models and softwares used by LKAB for rock mechanical numerical analysis. This may be conducted as a cooperation-project between the Luleå University of Technology and LKAB. The continued planning could be performed by the senior researcher Catrin Edelbro at LTU. Since this feasibility study recommends monitoring over time, the results from other near related projects at LKAB could be used as complementary information when planning the equipment and tools. The monitoring equipment needs to be included already in the design of the drifts and be “marked” on the mine map. Before starting the measuring campaign it is important to inform those who will work in the area. Therefore the validation project requires one responsible person of the monitoring equipment and measuring campaign and the dissemination of information at LKAB. Currently (beginning of 2012) the access drifting of level 1079 is ongoing. Concerning the production planning at LKAB, it could be possible to install monitoring equipment at level 1108 during the summer of 2013. After that it could be possible to follow the stress field changes during three to four years. A suggested schedule for the validation project is presented in Table 8.

66

Table 8 Suggestion of project plan for the validation project

Activity April -Dec 2012

Jan -Dec 2013

Jan-Dec 2014

Jan-Dec 2015

Jan-Dec 2016

Jan-April 2017

Application of project

proposal

Designate responsible at

LKAB* and project

group

Planning installation of

monitoring equipment

Installation in footwall

drifts at level 1108,

opening of level 1079

Continuous follow up

Writing report of the

results of mining one

level

Opening of level 1108

Writing report of the

results of mining two

levels

*responsible for measuring campaign

Table 9 Suggestion of project responsible/participants

Activity April -Dec 2012

Jan -Dec 2013

Jan-Dec 2014

Jan-Dec 2015

Jan-Dec 2016

Jan-April 2017

Project group meetings X X X X X X X X

Responsible at LKAB

Senior researcher at

LTU

Working 20-40% Working 100%

67

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