Natural Resources Engineering - Master's Theses

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Numerical modeling of brittle rock failure around underground openings under statis and dynamic stress loadings
(Laurentian University of Sudbury, 2013-10-09) Golchinfar, Nader
Stability of underground excavations is a prerequisite for the proper functioning of all other systems in a mining environment. From a safety point of view, the lives of people working underground rely on how well the support systems installed underground are performing. The ground control engineer cannot design an effective support system unless the area of the rock mass around the opening, prone to failure, is well identified in advance, even before the excavation of the tunnel. Under high stress conditions, usually experienced at deep mining levels, stress-induced rock failure is the most common type of instability around the underground openings. This thesis focuses firstly on the use of the finite difference numerical tool FLAC to simulate brittle rock failure under static in-situ stresses. Brittle failure of the rock mass around underground openings is a particular type of stress-induced failure, which can result in notch-shaped breakouts around the boundary of the tunnel. Generation of these breakout zones is a discontinuum process and approximating this process using FLAC, which is a continuum tool, requires careful consideration of the stress conditions and the stress related behavior of rock material. Based on plasticity theory, this thesis makes an effort to estimate the breakout formation using an elastic – brittle - plastic material model. Due to seismic challenges that deep mining operations are currently experiencing, rockbursting is a major hazard to the stability of underground structures. Therefore in this research, brittle failure of rock in the vicinity of the underground excavations is approximated also under dynamic loading conditions. The numerically modeled results of two different material models iv are compared with each other along with a previously developed empirical graph. This assessment, when further validated by field observations, may provide a different perspective for underground support design under burst-prone conditions.
Application of seismic monitoring in caving mines
(Laurentian University of Sudbury, 2013-10-10) Abolfazlzadeh, Yousef
Comprehensive and reliable seismic analysis techniques can aid in achieving successful inference of rockmass behaviour in different stages of the caving process. This case study is based on field data from Telfer sublevel caving mine in Western Australia. A seismic monitoring database was collected during cave progression and breaking into an open pit 550 m above the first caving lift. Five seismic analyses were used for interpreting the seismic events. Interpretation of the seismic data identifies the main effects of the geological features on the rockmass behaviour and the cave evolution. Three spatial zones and four important time periods are defined through seismic data analysis. This thesis also investigates correlations between the seismic event rate, the rate of the seismogenic zone migration, mucking rate, Apparent Stress History, Cumulative Apparent Volume rate and cave behaviour, in order to determine failure mechanisms that control cave evolution at Telfer Gold mine.
In SITU railway track fault detection using railcar vibration
(Laurentian University of Sudbury, 2014-03-17) Pagnutti, Jeffrey L.
This thesis investigates the development of an automated fault detection system developed for a novel lightweight railway material haulage system; in particular, the study aims to detect railway track faults at the incipient stage to determine the feasibility of maintenance decision support, ultimately with the function of preventing catastrophic failure. The proposed approach is an extension of the current state of the art in fault detection of unsteady machinery. The most common railway track faults associated with train derailment were considered; namely, horizontal and transverse crack propagation, mechanical looseness, and railbed washout were the faults of interest. A series of field experiments were conducted to build a database of vibration, speed, and localization data in healthy and faulted states. These data were used to develop, investigate, and validate the effectiveness of various approaches for fault detection. A variety of feature sets and classification approaches were investigated to determine the best overall configuration for the fault detector. The feature sets were used to condense data segments and extract characteristics that were sensitive to damage, but insensitive to healthy variations due to unsteady operation. The pattern recognition classifiers were used to categorize new data members as belonging to the healthy class or faulted class. The fault detection results from the proposed approach were promising. The feasibility of an automated online fault detection system for the lightweight material haulage system examined in this study was confirmed. The conclusions of this research outline the major potential for an iv effective fault detection system and address future work for the practical implementation of this system.
Towards modeling heat transfer using a lattice boltzmann method for porous media
(Laurentian University of Sudbury, 2014-05-16) Banete, Olimpia
I present in this thesis a fluid flow and heat transfer model for porous media using the lattice Boltzmann method (LBM). A computer simulation of this process has been developed and it is written using MATLAB software. The simulation code is based on a two dimensional model, D2Q9. Three physical experiments were designed to prove the simulation model through comparision with numerical results. In the experiments, physical properties of the air flow and the porous media were used as input for the computer model. The study results are not conclusive but show that the LBM model may become a reliable tool for the simulation of natural convection heat transfer in porous media. Simulations leading to improved understanding of the processes of air flow and heat transfer in porous media may be important into improving the efficiency of methods of air heating or cooling by passing air through fragmented rock.
The use of mechanical redundancy for fault detection in non-stationary machinery
(Laurentian University of Sudbury, 2014-11-14) ElMaghraby, Mohamed H.
The classical approach to machinery fault detection is one where a machinery’s condition is constantly compared to an established baseline with deviations indicating the occurrence of a fault. With the absence of a well-established baseline, fault detection for variable duty machinery requires the use of complex machine learning and signal processing tools. These tools require extensive data collection and expert knowledge which limits their use for industrial applications. The thesis at hand investigates the problem of fault detection for a specific class of variable duty machinery; parallel machines with simultaneously loaded subsystems. As an industrial case study, the parallel drive stations of a novel material haulage system have been instrumented to confirm the mechanical response similarity between simultaneously loaded machines. Using a table-top fault simulator, a preliminary statistical algorithm was then developed for fault detection in bearings under non-stationary operation. Unlike other state of the art fault detection techniques used in monitoring variable duty machinery, the proposed algorithm avoided the need for complex machine learning tools and required no previous training. The limitations of the initial experimental setup necessitated the development of a new machinery fault simulator to expand the investigation to include transmission systems. The design, manufacturing and setup of the various subsystems within the new simulator are covered in this manuscript including the mechanical, hydraulic and control subsystems. To ensure that the new simulator has successfully met its design objectives, extensive data collection and analysis has been completed and is presented in this thesis. The results confirmed that the developed machine truly represents the operation of a simultaneously loaded machine and as such would serve as a research tool for investigating the application of classical fault detection techniques to parallel machines in non-stationary operation.
Predicting blast-induced damage for open pit mines using numerical modelling software and field observations
(2014-12-02) Hall, Alexander K.
Blasting is the most common method used to fragment rock in the mining industry. However, given the violent nature of explosives and the high variability of results that can occur from blast to blast, there is potential to cause significant damage to the final walls of an open pit, which can lead to slope stability problems, catch bench filling, long-term rock fall hazards and ramp closure. Blasts need to be designed to suit the characteristics of the rock to be broken. Characteristics of the existing rock mass such as natural jointing, joint orientation, joint condition, and the strength of the rock, all need to be accounted for prior to designing a blast. In general, blasting engineers rely on a combination of empirical analysis and rules of thumb for blast designs. The uncertainty involved with these techniques can lead to significant problems in open pit mining. At the bench scale of an open pit mine, the loss of the bench crest is a concern, however at the full pit scale, bench deterioration can jeopardize worker safety and lead to potential closure of the mine. The results of a blast can be highly variable – a blast design that yields favorable results on one side of a pit can have detrimental effects on another wall of the pit or at different elevations in the pit, based on the characteristics of the rock. It often takes multiple iterations of blast designs to achieve an optimal result, which is costly and time consuming for the company that operates the mine. The purpose of this thesis is to evaluate the effectiveness of a relatively new software package, Blo-Up, that combines both a finite difference continuum code and a distinct element code in order to model the entire blasting process from start to finish. The main focus of the research will be to examine blast induced damage sustained to final pit walls and provide techniques for minimizing damage. The specific areas of the study are: 1) To confirm the software is able to give results similar to those observed in the field; 2) To model pre-split designs in homogeneous rock; 3) To model pre-split designs in jointed rock masses; 4) To model the effect of a production hole detonation on inclined pre-split holes, as opposed to vertical pre-split holes, and 5) To model effects of large scale production blasts on final wall stability. For the purposes of this review, kimberlite rock was chosen to be the focus of the study due to its ductile characteristics, which makes controlled blasting difficult. The main findings of the research are as follows: 1) The software is able to replicate blast outcomes observed in the field; 2) The importance of tailoring the pre-split design to the rock mass is critical, and 3) The main production blast must be well balanced if the explosive energy is to be evenly distributed through the system.
Cross-linked polymers of phenylacetylene and 1,3-diethynylbenzene: new polymer precursors for nanoporous carbon materials for supercapacitors and gas storage
(Laurentian University of Sudbury, 2015-01-09) Grundy, Mark
The increasing threats of global warming, rapid depletion of fossil fuels, and increasing energy demands are driving an enormous amount of research into clean renewable sources of energy, flue gas capture technologies, and environmentally friendly energy storage devices, to name a few. Activated carbons present a multipurpose material commonly used in many of these increasingly popular green technologies. A wide range of cross-linked acetylenic polymers of phenylacetylene and 1,3- diethynylbenzene were synthesized and investigated in this thesis to generate materials for electrochemical double layer capacitors, CO2 capture, and hydrogen storage. Chemical activation of the copolymers in the presence of KOH was shown to produce highly microporous carbons with various textural properties. The specific cross-linking densities of the polymer precursors prior to carbonization were shown to greatly affect the carbon yield, surface area, pore volumes and pore sizes of the carbons produced. Electrochemical measurements of the activated carbons showed their impressive performances as capacitor materials, with high specific capacitances (up to 446 F g−1 at 0.5 A g−1 in 3-electrode cell) and long cycle life. Gas sorption studies also demonstrated impressive H2 and CO2 adsorption capacities (up to 2.66 wt% or 13.3 mmol g−1 for H2 adsorption at 77 K and 1 atm, and up to 30.6 wt% or 6.95 mmol g−1 for CO2 adsorption at 273 K and 1 atm). Owing to the high content of pendent alkyne groups in these polymers, complexation reactions with metallic carbonyl ligands are able to provide an effective iv way of dispersing metallic and metal oxide nanoparticles within the synthesized copolymers, which could provide additional pseudocapacitive properties. An appropriate copolymer with high alkyne content was subjected to complexation with Co2(CO)8, and subsequently carbonized and oxidized to yield carbon-supported CoxOy/Co nanoparticles (CoxOy@C-CPD76%). In addition to pseudocapacitive contributions, the cobalt species also effectively catalyzed the production of graphitic networks within the carbon support, improving their conductive properties. Electrochemical measurements demonstrated impressive specific capacitance (310 F g−1 at 0.1 A g−1) compared with non-activated carbons (160 – 177 F g−1 at 0.1 A g−1) synthesized at identical conditions, and provided a large stable potential window (1.4 V) in an aqueous KOH solution. The combined electrochemical double layer capacitance and pseudocapactiance behaviour of the carbon and CoxOy/Co also provided improved energy densities (21 W h kg−1), and uncompromised power densities (2017 W kg−1) compared with the pristine carbons (~2034 W kg−1).
Numerical analysis of porous piezoelectric materials
(Laurentian University of Sudbury, 2015-01-13) Singh, Jaspreet
Three-dimensional finite element models based on unit-cell approach are developed to characterize the complete electromechanical properties of: (i) zero-dimensional (3-0), one-dimensional (3-1) and three-dimensional (3-3) type porous piezoelectric structures made of lead zirconium titanate (PZT-7A) and relaxor (PMN-PT based) ferroelectrics (RL); and (ii) 3-3 type porous piezoelectric foam structures made of several classes of piezoelectric materials such as barium sodium niobate (BNN), barium titanate (BaTiO3) and relaxor (PMN-PT based) ferroelectrics (RL). In this thesis, finite element software named ABAQUS is used to characterize the electromechanical response of 3-0, 3-1 and 3-3 type porous piezoelectric structures. Appropriate boundary conditions are invoked for various porous piezoelectric structures (i.e. 3-0, 3-1 and 3-3 type) to ensure that the electromechanical deformation response of the unit-cell, under conditions of electrical and mechanical loading, is representative of the entire porous piezoelectric structures. Overall, this thesis demonstrates that the microstructural features such as porosity connectivity, porosity aspect ratio, porosity volume fraction, foam shape, and material selection play significant roles on the electromechanical properties and the figures of merit of porous piezoelectric structures.
Modeling and fault detection of an industrial copper electrowinning process
(2015-01-22) Wiebe, Susan
Copper electrowinning plants are where high purity copper (Cu) product is obtained through electrochemical reduction of copper from the leaching solution. The presence selenium (Se) and tellurium (Te) in copper sulphide minerals may result in contamination of the leach solution and, eventually of the copper cathode. Unfortunately, hydrometallurgical processes are often difficult to monitor and control due to day-to-day fluctuations in the process as well as limitations in capturing the data at high frequencies. The purpose of this work is to model key variables in the copper electrowinning tank and to apply statistical fault detection to the selenium/tellurium removal and copper electrowinning process operations. First principle modeling was applied to the copper electrowinning tank and partial differential equation models were derived to describe the process dynamics. Industrial data were used to estimate the model parameters and validate the resulting models. Comparison with industrial model shows that the models fit reasonably well with industrial operation. Simulations of the models were run to explore the dynamics under varying operating conditions. The derived models provide a useful tool for future process modification and control development. Using the collected industrial operating data, dynamic principal component analysis (DPCA) based fault detection was applied to Se/Te removal and copper electrowinning processes at Vale’s Electrowinning Plant in Copper Cliff, ON. The fault detection results from the DPCA based approach were consistent with the industrial product quality test. After faults were detected, fault diagnosis was then applied to determine the causes of faults. The fault detection and diagnosis system helps define causes of upset conditions that lead to coppercathode contamination.
Longterm schedule optimization of an underground mine under geotechnical and ventilation constraints using SOT
(Laurentian University of Sudbury, 2015-01-26) Sharma, Vijay
Long-term mine scheduling is complex as well time and labour intensive. Yet in the mainstream of the mining industry, there is no computing program for schedule optimization and, in consequence, schedules are still created manually. The objective of this study was to compare a base case schedule generated with the Enhanced Production Scheduler (EPS®) and an optimized schedule generated with the Schedule Optimization Tool (SOT). The intent of having an optimized schedule is to improve the project value for underground mines. This study shows that SOT generates mine schedules that improve the Net Present Value (NPV) associated with orebody extraction. It does so by means of systematically and automatically exploring the options to vary the sequence and timing of mine activities, subject to constraints. First, a conventional scheduling method (EPS®) was adopted to identify a schedule of mining activities that satisfied basic sets of constraints, including physical adjacencies of mining activities and operational resource capacity. Additional constraint scenarios explored were geotechnical and ventilation, which negatively effect development rates. Next, the automated SOT procedure was applied to determine whether the schedules could be improved upon. It was demonstrated that SOT permitted the rapid re-assessment of project value when new constraint scenarios were applied. This study showed that the automated schedule optimization added value to the project every time it was applied. In addition, the reoptimizing and re-evaluating was quickly achieved. Therefore, the tool used in this research produced more optimized schedules than those produced using conventional scheduling methods.
Application of GenRel for maintainability analysis of underground mining equipment: based on case studies of two hoist systems
(Laurentian University of Sudbury, 2015-01-29) Xu, Chao
With the increasing costs of extracting ores, mines are becoming more mechanized and automated. Mechanization and automation can make considerable contributions to mine productivity, but equipment failures and maintenance have an impact on the profit. Implementing maintenance at suitable time intervals can save money and improve the reliability and maintainability of mining equipment. This thesis focuses on maintainability prediction of mining machinery. For this purpose, a software tool, GenRel, was developed at the Laurentian University Mining Automation Laboratory (LUMAL). GenRel is based on the application of genetic algorithms (GAs) to simulate the failure/repair occurrences during the operational life of equipment. In GenRel it is assumed that failures of mining equipment caused by an array of factors follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest using genetic algorithms (GAs) coupled with a number of statistical techniques. This thesis will show the applicability and limitation of GenRel through case studies, especially in using discrete probability distribution function. One of the objectives of this thesis is to improve GenRel. A discrete probability distribution function named Poisson is added in the pool of available probabilities functions. After improving and enhancing GenRel, the author carries out two groups of case studies. The objectives of the case studies include an assessment of the applicability of GenRel using real-life data and an investigation of the relationship between data size and prediction results. Discrete and continuous distribution functions will be applied on the same input data. The data used in case studies is compiled from failure records of two hoist systems at different iv mine sites from the Sudbury area in Ontario, Canada. The first group of case studies involves maintainability analysis and predictions for a 3-month operating period and a six-month operating period of a hoist system. The second group of case studies investigates the applicability of GenRel as a maintainability analysis tool using historical failure/repair data from another mine hoist system in three different time periods, three months, six months and one year. Both groups apply two different distribution probability functions (discrete and continuous) to investigate the best fit of the applied data sets, and then make a comparative analysis. In each case study, a statistical test is carried out to examine the similarity between the predicted data set with the real-life data set in the same time period. In all case studies, no significant impact of the data size on the applicability of GenRel was observed. In continuous distribution fitting, GenRel demonstrated its capability of predicting future data with data size ranging from 166 to 762. In discrete probability fitting, the case studies indicated to a degree the applicability of GenRel for the hoist systems at Mine A and Mine B. In the discussion and conclusion sections, the author discloses the findings from the case studies and suggests future research direction.
Star-structured polyethylene nanoparticles via Pd-catalyzed living polymerization : synthesis, characterization, and catalytic applications.
(Laurentian University of Sudbury, 2015-07-08) Landry, Eric D.
The arm-first synthesis of large unimolecular star-structured polyethylene nanoparticles or SPE-NPs (MW > 1,000 kg/mol, PDI ≈ 1.1) joined by a cross-linked polynorbornadiene (PNBD) core is described in this thesis. SPE-NPs having high arm number (fn > 100) and tunable arm topologies (hyperbranched HBPE or linear-but-branched LBPE) are conveniently synthesized in a single reactor following four consecutive steps. In step 1, living ethylene polymerization is catalyzed by 0.1 mmol of Pd-diimine catalyst 1 to grow HBPE arms (1 atm C2H4/15 °C) or LBPE arms (27 atm C2H4/5 °C) of tunable lengths (tE = 1-5 h, Mn = 11-40 kg/mol). In step 2, the norbornadiene (NBD) cross-linker is added into the ethylene reactor for several hours (tNBD = 1-4 h) yielding PE-b-PNBD block copolymers with a short PNBD segment bearing cross-linkable pendant double bonds. SPEs are then formed in step 3 during precipitation in acidified methanol (H+/MeOH) and the final SPE-NPs are formed in step 4 after several hours of drying in vacuo at 120 °C. A thorough systematic investigation of the reaction parameters indicates that to produce increasingly larger SPE-NPs, it is essential to add a significant molar excess of NBD to 1 ([NBD]0/[1]0 > 50) and synthesize short LBPE arms but large HBPE arms. When synthesized with LBPE arms, the SPE-NPs have higher MW compared to those synthesized with HBPE arms due to the lower steric hindrance of the linear arms which enables a high number of arms to be joined at the PNBD core. Furthermore, the Pd-diimine catalyst used in the synthesis of the SPE-NPs was encapsulated within the cross-linked PNBD core. These encapsulated Pd(II) species were tested for their activity in hydrogenation reactions of terminal alkenes and alkynes (1-octene, 1-hexene, and 1-hexyne) and Heck coupling reactions of iodobenzene and n-butyl acrylate. Preliminary data suggests that these SPE-NPs may be used as models for the design of more advanced recyclable nanovessel for Pd(II) catalysts.
Object distance measurement using a single camera for robotic applications
(Laurentian University of Sudbury, 2015-08-10) Alizadeh, Peyman
Visual servoing is defined as controlling robots by extracting data obtained from the vision system, such as the distance of an object with respect to a reference frame, or the length and width of the object. There are three image-based object distance measurement techniques: i) using two cameras, i.e., stereovision; ii) using a single camera, i.e., monovision; and iii) time-of-flight camera. The stereovision method uses two cameras to find the object’s depth and is highly accurate. However, it is costly compared to the monovision technique due to the higher computational burden and the cost of two cameras (rather than one) and related accessories. In addition, in stereovision, a larger number of images of the object need to be processed in real-time, and by increasing the distance of the object from cameras, the measurement accuracy decreases. In the time-of-flight distance measurement technique, distance information is obtained by measuring the total time for the light to transmit to and reflect from the object. The shortcoming of this technique is that it is difficult to separate the incoming signal, since it depends on many parameters such as the intensity of the reflected light, the intensity of the background light, and the dynamic range of the sensor. However, for applications such as rescue robot or object manipulation by a robot in a home and office environment, the high accuracy distance measurement provided by stereovision is not required. Instead, the monovision approach is attractive for some applications due to: i) lower cost and lower computational burden; and ii) lower complexity due to the use of only one camera. Using a single camera for distance measurement, object detection and feature extraction (i.e., finding the length and width of an object) is not yet well researched and there are very few published works on the topic in the literature. Therefore, using this technique for real-world robotics applications requires more research and improvements. This thesis mainly focuses on the development of object distance measurement and feature extraction algorithms using a single fixed camera and a single camera with variable pitch angle based on image processing techniques. As a result, two different improved and modified object distance measurement algorithms were proposed for cases where a camera is fixed at a given angle in the vertical plane and when it is rotating in a vertical plane. In the proposed algorithms, as a first step, the object distance and dimension such as length and width were obtained using existing image processing techniques. Since the results were not accurate due to lens distortion, noise, variable light intensity and other uncertainties such as deviation of the position of the object from the optical axes of camera, in the second step, the distance and dimension of the object obtained from existing techniques were modified in the X- and Y-directions and for the orientation of the object about the Z-axis in the object plane by using experimental data and identification techniques such as the least square method. Extensive experimental results confirmed that the accuracy increased for measured distance from 9.4 mm to 2.95 mm, for length from 11.6 mm to 2.2 mm, and for width from 18.6 mm to 10.8 mm. In addition, the proposed algorithm is significantly improved with proposed corrections compared to existing methods. Furthermore, the improved distance measurement method is computationally efficient and can be used for real-time robotic application tasks such as pick and place and object manipulation in a home or office environment.
Seismic hazard evaluation using apparent stress ratio for mining-induced seismic events
(2015-08-20) Brown, Laura Grace
This thesis investigates precursory trends in seismic data prior to the occurrence of large and potentially damaging seismic events at Agnico Eagle’s LaRonde mine. A variety of sample populations are selected to represent varying degrees of seismic hazard within a large area of interest at LaRonde. The main factor considered for hazard assessment is the local stress conditions within the rock mass, inferred from the apparent stress of seismic events. An alternative means of analyzing apparent stress measurements using a relative ratio, referred to as Apparent Stress Ratio (ASR), is presented. The use of a ratio eliminates the need for thresholds values to define high and abnormal apparent stress. ASR values are analyzed in reference to varying time frames, allowing for changes in stress conditions over time to be considered. Hazard maps created using ASR and peak ASR values correspond well to areas of elevated seismic hazard previously identified at LaRonde. For an area of interest at LaRonde, ASR as an alarm tool possesses a success rate of 68% with a false alarm ratio of 2:1.
Mine schedule optimization with geotechnical constraints
(2015-09-28) Saeidi, Negar
If a mining project consists of n stoping activities these can be scheduled in n! ways according to the duration between the activities and their precedence. Mine schedule optimization manipulates the precedence relationships and the duration of the mining activities in order to maximize the Net Present Value (NPV). However, unexpected instabilities may impede or disrupt the schedule and thus reduce the profitability and so geotechnical aspects of the operation need to be taken into account. The mine schedule optimization software considered in this work is the so-called Schedule Optimization Tool (SOT). This thesis reports the work for development of new geomechanical constraints for any mine scheduling tool to find the safest and the most profitable schedule, exemplified within the SOT framework. The core hypothesis of this research is that there is a time-dependent aspect of the rock behaviour that leads to instability, a consequence of dependence of geotechnical instability upon the sequence and duration between stoping activities. There is evidence presented in this work that supports this hypothesis. An automated procedure for timely and computationally efficient calculations of the instability metrics is presented. This can be applied to evaluate the geomechanical stability of any of the n! schedules for excavating n stopes or applied to evaluate geomechanical stability of schedules arising in the schedule optimization process. However, in practice, the number of feasible schedules is much less than n! due to the precedence constraints. The approach starts with computing n elastic stress fields induced after excavating each individual stope independently within an identical computational domain using Compute3D. The stress-time series of each iv and/or every sequence of stoping are generated through superimposition of these pre-computed stress fields, and the time stamps of blasting for excavation are allocated corresponding to the stoping timetable. Different blasts are allowed to be timetabled at the same time. By means of Hooke’s law and the 3D Kelvin-Voigt creep model the elastic strain time series and the viscoelastic strain time series are produced for the stress-time series. Based on the Mohr- Coulomb Failure criterion three (in)stability indicators are defined: i. ‘Strength Factor’ to evaluate state of stress at each stage of each schedule as a proportion of is strength ii. ‘Strainth Factor’ to evaluate state of elastic strain at each stage of each schedule as a proportion of a limiting ‘rupture’ strain iii. ‘Viscoelastic-strainth Factor’ to evaluate state of viscoelastic strain at each stage of each schedule as a proportion of a limiting ‘rupture’ strain. To provide a perspective of the (in)stability condition in the computational domain for all the feasible sequences of stoping, 12 (in)stability metrics were defined and the results of each are illustrated in the form of ‘(in)stability indicator diagrams’. The overall methodology is applied to an example of excavating 6 open stopes. Additionally, a methodology is theorized to evaluate the stability condition in the rock mass surrounding the stopes for a series of stoping and backfilling schedules. The methodology is based on pre-computing one additional stress field element for each stope, which represents the effect of the fill loading on the rock mass. The calculations for this approach are consistent with the time and computational efficiency of the original methodology. The computational effort v increases to ‘2n’ pre-computed stress fields rather than ‘n’: as problem sizes double, computational time doubles, rather than increases in polynomial or exponential time.
Design, construction and testing of a Tesla Turbine
(2016-02-26) Holland, Kris
This thesis presents the design, construction and testing of a boundary layer turbine, also known as a Tesla Turbine. A turbine, with discs of 92mm in diameter, central exhaust, plenum chamber, and swappable nozzles was constructed. The setup included instrumentation and a simple torque sensor with which to sense the relatively low torques given the low testing pressures. After construction, the setup was tested with various angles of nozzles ranging from 2.5° to 45° from tangential. The testing resulted in an estimated maximum efficiency of 8.5%, while running the rig at 3 bar, which is comparable to the literature. Unexpectedly, this maximum was achieved with a nozzle pointed at 45° from tangential, which may have been caused by the disc pack variant used in the tests.
Employing heat pumps to recover low grade industrial thermal resources for space heating and cooling
(2016-05-16) Ross, Ian Michiel
The use of heat pumps to upgrade and recover low grade industrial thermal resources is an opportunity for industry to deliver low cost space heating at a reduced carbon footprint. Heat pumps also offer the potential to provide space heating and space cooling from a single unit. To facilitate rapid determination of the potential for low grade heat recovery using ground source heat pumps, a rapid scoping method was developed capable of establishing critical temperatures to help elucidate which resources are most likely to be recovered economically. To demonstrate the applicability of the rapid scoping method, an analysis of various process cooling waters present at a smelter site was undertaken. The implications for cost and carbon dioxide emissions, were both analyzed for this facility, although the concepts developed can be employed to any site that generates large quantities of thermally low-grade heat.
Human detection and face recognition in indoor environment to improve human-robot interaction in assistive and collaborative robots
(2016-10-14) Kunwar, Sumesh
Human detection in indoor environment is essential for Robots working together with humans in collaborative manufacturing environment. Similarly, Human detection is essential for service robots providing service with household chores or helping elderly population with different daily activities. Human detection can be achieved by Human Head detection, as head is the most discriminative part of human. Head detection method can be divided into three types: i) Method based on color mode; ii) Method based on template matching; and iii) Method based on contour detection. Method based on color mode is simple but is error prone. Method based on head template detects head in the image by searching for a template which is similar to head template. On the other hand, Method based on contour detection uses some information to describe head or head and shoulder information. The use of only one criteria may not be sufficient and accuracy of human head detection can be increased by combining the shape and color information. In this thesis, a method of human detection is proposed by combining the head shape and skin color (i.e., Combination of method based on Color mode and method based on Contour detection). Mainly, curvature criteria is used to segment out curves having similar curvature to find human head. Further, skin color is detected to localize face in image plane. A curve represents human head curve if only it has sufficient skin colored pixel in its closed proximity. Thus, by using color and human head curvature it was found that promising results could be obtained in human detection in indoor environment. iv After detecting humans in the surrounding, the next step for the robot could be to identify and recognize them. In this thesis, the use of Gabor filter response on nine points was investigated to identify eight different individuals. This suggests that the Gabor filter on nine points could be applied to identify people in small areas, for example home or small office with less individuals.
Nanocomposites of carbon nanosphere and graphene oxide with iron oxide as high-performance adsorbents for arsenic removal
(2016-11-17) Su, Hui
Arsenic is a widely distributed element in the Earth’s crust with an average terrestrial concentration of about 5 g ton-1 . Arsenic is a persistent, bio-accumulative, toxic element. The United States Environmental Protection Agency (EPA) has implemented the discharge criterion of 10 µg L -1 for arsenic as the maximum acceptable level for ground water. During the past decades, several techniques have been developed for the removal of arsenic from the wastewater, including chemical precipitation, adsorption and ion exchange, membrane and biological removal processes, and so on. Because of the good arsenic removal efficiency and the low cost, adsorption is a more popular method. In this thesis research, two ranges of iron oxide nanocomposite adsorbents have been developed and studied for their performance properties towards arsenic removal. Novel iron oxide encapsulated carbon nanospheres (FeOx-CNS) with excellent arsenic adsorption performance has been successfully synthesized. CO2 activated carbon nanospheres material (A-CNS) with high surface area (2271 m²g -1 ) and high pore volume (5.18 cm³g -1 ) was selected as the porous matrix. After surface oxidation by ammonium persulfate (APS), iron oxide was loaded into the carbon nanospheres as the effective arsenic adsorbent. Transmission electron microscopy (TEM) and Braunauer–Emmett– Teller (BET) results indicate that iron oxide nanoparticles (7-60 wt%) are well-dispersed within the mesopores. In particular, FeOx-CNS-13 composite shows most optimum performance properties, with high arsenic adsorption capacities achieved for both As(III) (416 mg g−1 ) and As(V) (201 mg g−1 ). Another range of amorphous iron oxide-graphene oxide (FeOx-GO) nanocomposites having different graphene oxide (GO) content (36-80 wt%) was prepared by coprecipitation of ferrous sulfate heptahydrate and ferric sulfate hydrate on GO sheets. The composites have been thoroughly characterized and investigated for their performance towards arsenic removal. The optimum composite, FeOx-GO-80 having the highest iron oxide content of 80 wt% shows excellent arsenic adsorption capacities for both As(III) (147 mg g−1 ) and As(V) (113 mg g−1 ), which are highest among iron oxideGO composites reported to date for arsenic removal. The high performance along with low cost and convenience in synthesis makes this range of amorphous iron oxide-GO nanocomposites promising for applications.
Monte Carlo simulations and experiments of Bessel beams and tissue-like phantoms interaction
(2017-02-23) Yang, Jianing
In this thesis, the propagation of Bessel beam in tissue and its potential advantages were explored numerically and experimentally. In the numerical simulations, the Monte Carlo method is used to simulate the propagation of Gaussian and Bessel beams in tissue. By convolving the impulse profile generated by a pencil beam’s propagation with either beam intensity profile, the response of the propagation of the said beam can be approximated. This process was done by modifying and using MCML and CONV software which are available from the literature. Experimentally, the Bessel beams were generated by a laser and axicons, and made to propagate through optical phantoms formed with variable density intralipid solutions. The intensity distribution of the transmitted Bessel beam at the exit of the scattering media was measured and compared with transmittance results from simulation. At last, a separate experiment was designed to investigate the reconstruction of a Bessel beam after it passes the optical phantom.

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