Engineering: Theses and Dissertations

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Open Access
Development and validation of processing algorithms to delineate individual foot reactions from a single-belt instrumented treadmill to generate synchronised acoustic emission and lower-limb biomechanics data
(2023) Sinclair, James Thomas
The human hip joint plays a vital role in daily activities such as walking, standing, and running, contributing significantly to health-related quality of life. The joint's natural structure involves a ball- and-socket connection between the femur and pelvis, allowing for complex movements. Unfortunately, various factors, including trauma, wear, arthritis, and pathological conditions, can compromise the integrity of the hip joint, leading to conditions like osteoarthritis, developmental dysplasia, Paget's disease, and more. Hip osteoarthritis, a prevalent cause of debilitating pain, often necessitates primary hip arthroplasty, a surgical procedure replacing the natural joint with an artificial implant. As the aging population undergoes increasing hip arthroplasties, monitoring the prosthetic's condition becomes crucial. Traditional inspection methods, such as x-ray and CT imaging, have limitations, including radiation exposure and can only capture a single frame. The research performed explores the use of acoustic emissions (AE) as a non-invasive and continuous monitoring method for prosthetic hips. AE consists of “listening in” to the sound waves generated by the prosthesis during movement. Unlike other conventional imaging methods, AE allows for dynamic inspection of the prosthesis without subjecting the patient to ionising radiation. This research builds on previous work performed at the University of Canterbury by Dr. FitzPatrick, transferring the AE monitoring procedure from an overground gait on a stationary forceplate, to an instrumented treadmill to collect continuous, prolonged recordings with a steady state walking gait. This study addresses key objectives, including successfully transitioning to an instrumented treadmill while still collecting the same quality of data to what was performed by Dr. FitzPatrick, reliably separating the combined ground reaction force during the double support stage of the walking gait into the left and right foot contributions, and the identification and mitigation of artefacts introduced by the instrumented treadmill. Additionally, modifications were made to the foot delineation methods that improved the accuracy of the delineation calculation, reducing the mean error. In conclusion, this research advances the application of AE monitoring as a method for inspection of prosthetic hips by facilitating a larger data set to be collected allowing for future researchers to make broader conclusions on the features and trends observed from AE monitoring. These findings contribute to the ongoing efforts to enhance the reliability and longevity of hip prosthetics in an ageing population.
Open Access
Computing non-square elements of square norm in a number field.
(2023) Kent, Joe
In this thesis we explore the unit group of the ring of integers of number fields. In our exploration we look at Dirichlet’s unit theorem which shows that the unit group is a finitely generated abelian group. This will allow us to explore computing the generating set of the unit group. From this basis we then extend the computation of unit groups to describe and implement an algorithm in PARI for finding elements in the kernel of the norm mapping K×/K×2 Q×/Q×2. Elements in this mapping are of particular interest for finding Brauer Manin obstructions with current implementations using a set of fundamental units.
Open Access
Assessing the effect of visual accessibility features on player performance in videogames through simulating visual impairments.
(2023) Fremaux, Andre
This thesis evaluates the effectiveness of visual accessibility features in video games by measuring the player performance of participants who are experiencing simulated effects of Macular Degeneration with a Head Mounted Display. In this thesis, the following research questions are posed: • Q1: How does a non-visually impaired person’s performance playing videogames vary with and without simulated visual impairments? • Q2: How do accessibility features affect a person’s performance when playing games with simulated Macular Degeneration? A mixed methodology approach was used to evaluate the player performance across three types of videogames: First-Person Shooter, Racing, and 2D Platformer. For each videogame, the participant’s experienced three implemented accessibility features: Object Highlighting, Object Outlining, and Desaturation of the Environment. Participant interviews for each videogame were also conducted to gain insight into any changes in performance. Results indicate a difference in performance when participants played each videogame with simulated Macular Degeneration. However, even when accessibility features were introduced to mitigate or overcome the effects of simulated Macular Degeneration, performance was still negatively affected in the presence of simulated Macular Degeneration compared to playing unimpaired. Unfortunately, there is no quantitative or qualitative results that suggest any of the evaluated accessibility features significantly improved performance of users experiencing simulated Macular Degeneration.
Open Access
Exploring the interface between engineering and the indigenous Maori dimension : a study concerning the seismic performance expectations of buildings for Ngati Toa and Ngai Tahu.
(2023) Royal, Kākati Te Kākākura
This thesis contains chapters which are associated with each research objective. Chapters generally build on each other and follow the general process of the research as it was carried out. Chapter 2 - A Cultural Statement: This chapter provides a comprehensive foundation for the thesis, connecting personal motivations, tribal priorities, and an institutional innovation process. Chapter 3 - Setting the research priority and context: This chapter highlights the crucial role of engineers in addressing New Zealand's challenges and opportunities, while simultaneously meeting the needs and values of Māori communities. It explores government policies, tertiary institution initiatives, industry efforts, and tribal organisations that aim to leverage Māori knowledge and assets. Chapter 4 – Current knowledge and practice to the engineering of buildings: This chapter discusses various methods for revising the design process and criteria to align with tribal performance objectives in the seismic design of light-framed timber buildings. Chapter 5 – Methodology: The chapter outlines a comprehensive methodology for incorporating indigenous Māori values and tribal seismic performance objectives into New Zealand's building regulatory system. This chapter introduces the Māori Performance Assessment Procedure (MPAP) as an adaptation of the (FEMA-P58-1, 2018) framework. Chapter 6 – Tribal Seismic Performance Objectives: This chapter provides essential clarifications of conducting tribal research within institutions and the challenges around representation. It then presents the results of interviews that were conducted to establish tribal performance objectives. Chapter 7: Design and Modelling of a Timber-Framed Building for Tribal Seismic Performance Assessment - This chapter outlines the design process and detailed model for light-frame wood buildings using state-of-the-art modelling software, Timber3D.
Open Access
Forecasting the forest growing workforce demand within the Canterbury/West Coast region.
(2023) Parkes, Heath
The forestry industry has grown into becoming a major contributor to New Zealand’s economy and employment by becoming one of the country’s staple export earners. It is estimated that the industry currently employs over 40,000 individuals, this number has been rising steadily since 2015. Employment within the industry is heavily dependent on the export timber market in the short term and the area by age class distribution of the forestry resource in the long term and can at times create abrupt shortages in job-specific roles within the industry. A survey of the forest-growing workforce within the Canterbury/West Coast region was conducted in order to characterise the region's employment. A total of 42 businesses were identified during the study, of these businesses a response rate of 69% was achieved. Using data collected from the survey alongside publicly available information, a regional workforce forecasting model was developed in order to forecast regional demand between 2023 – 2053. Results were then analysed to determine the key trends in future workforce demand and more specifically demand which job roles experience the most fluctuation under the forecast conditions. Results showed that the majority of employment falls within forest harvesting and log transportation. It was found that these two sub-groups are affected the most by changes in wood availability, this is due to the fact that both harvesting and log transportation are completely reliant on future harvest volumes. It is expected that the Canterbury/West Coast forest workforce demand will contract significantly from 2023 – 2043 as regional wood availability reduces. Workforce demand is expected to recover from 2036 – 2044, however, still expected to be 23% lower than employment levels experienced during 2023. The Canterbury/West Coast forest industry needs to prepare for a reduction in forest harvest activity and employment. This research quantifies the impact of the decline in harvesting activity on those job roles associated with harvesting. The future trend in forest management and silviculture job roles also depends on the level of investment in new planting and replanting. Employment at the port depends on the volume of wood allocated to the export log market and to domestic processing. It is important to fully quantify how the workforce will be affected in order to make better decisions based on more robust data.
Open Access
An assessment of ecosystem restoration at Styx Mill Conservation Reserve, Christchurch, New Zealand.
(2023) Walters, Emma
With human arrival in New Zealand, many indigenous flora and fauna have become extinct or endangered. The 90% loss of lowland wetlands, due to conversion and fragmentation, is of significant concern. Large-scale restoration efforts must occur across the country to preserve the remaining ecosystems and re-establish degraded areas. Styx Mill Conservation Reserve (SMCR), Christchurch, New Zealand is a remnant freshwater wetland where restoration activities are occurring. The progress of ecosystem restoration at SMCR will be assessed by understanding how species composition varies across the reserve, determining whether the restoration efforts are creating an ‘ecologically authentic’ representation of the historic ecosystem, and identifying whether, and where, natural seedling regeneration is occurring. A hierarchical cluster analysis used vascular species composition to identify four vegetation communities at SMCR (low forest, high grassland, riparian/marshland, and low shrubland). An nMDS ordination showed that the low forest community was most distinct from the other communities. The low forest community was abundant in indigenous Griselinia littoralis and Cordyline australis. The other three communities were abundant in exotic Lotus pedunculatus; suggesting that its abundance reduces as forest canopy closes. Indigenous species that are present in the four О̄tautahi Christchurch Ecosystems Map plant lists (Wet plains – Kahikatea, Dry plains – Tussock, Dry plains – Ti Kouka, and Dry plains – Houhere) were most dominant (mean importance value= 0.22) across the reserve (exotic species= 0.12, indigenous species not present on lists= 0.07). The low forest plots were the only community where the indigenous – present species were significantly greater (p-value= 2.21x10-6) than the indigenous – not present and exotic species. The species regenerating the most were Coprosma robusta (0.45 seedlings/m2) and Griselinia littoralis (0.42 seedlings/m2). All seedlings were found in the low forest plots, aside from one Coprosma robusta seedling in a riparian/marshland plot. Restoration at SMCR can be thought of as incomplete, due to the high abundance of exotic species and lack of seedling regeneration in all areas of the reserve apart from the low forest community. The incomplete areas of restoration will require the most attention by management and efforts should be focused on assisting these areas to move to a composition similar to that of the low forest community.
Open Access
Comparing performance of Douglas fir growth and yield models in the South Island of New Zealand.
(2023) Walker, Liam
Douglas fir (Pseudotsuga menziesii) is New Zealand's second most important plantation tree species. Of the total plantation area (100,105 ha), approximately 75% is planted in the South Island regions of Canterbury, Otago, and Southland. There are three common growth and yield models for Douglas fir in the South Island: the 500 Index model (500 Index), South Island Douglas fir model (SIDFIR) and the Douglas fir National model (DFNAT). Although frequently used, it is unknown how the models perform on datasets outside those used for initial validation. Predictions of mean top height (MTH), basal area/ha and stocking by the three models were compared to 315 growth measurements across 8,376 ha of Douglas fir forests throughout Canterbury, Otago, and Southland. The ability of each model to match actual historical growth measurements in an independent dataset formed the basis for comparison. The effects of region and several site characteristics were also tested for their impact on residual errors of model predictions. Site characteristics shown to affect residual errors significantly were used to adjust model predictions to increase precision and reduce bias. Substantial imprecision, systematic bias, and regional variations were found in predictions of MTH, basal area/ha and stocking by the 500 Index, SIDFIR and DFNAT growth and yield models. Regional variations and significant effects of site characteristics were also shown to exist. The SIDFIR model performed the best with the most precision and least bias of the three models; however, predictions still displayed considerable imprecision and bias. Thus, developing a new growth and yield model for Douglas fir in the South Island is recommended. This model should utilise a hybrid modelling approach to account for climatic variations between sites and provide increased precision and reduced regional variation. A new model would allow forest managers to make effective decisions to ensure the productivity, profitability, and sustainability of Douglas fir forests in the South Island of New Zealand.
Open Access
Assessment of wood stiffness by species and aging: a Nelder experiment.
(2023) Wright, Nathan
Pinus radiata timber is inherently hindered by low stiffness due to high microfibril angle in the corewood zone. Determining how foresters can manipulate microfibril angle in plantation forests to increase stiffness is of high economic and silvicultural importance. A Nelder systematic spacing design in Canterbury was used to assess the stiffness and tree dimensions of 16-year-old P. radiata (n = 344) and 15-year-old Eucalyptus nitens (n = 211) at stocking levels ranging from 271 stems per hectare to 40,466 stems per ha. Using regression modelling independent variables species, aging and stocking were used to predict response variables outerwood stiffness, diameter at breast height (DBH) and tree height. Stocking, species and physiological aging had a significant effect on modulus of elasticity (MOE). Outerwood MOE significantly increased with increasing stocking for P. radiata up to 17,564 stems per hectare and up to 1,023 stems per hectare for E. nitens (P < 0.001). There was little stiffness gain in planting E. nitens at a greater stocking than 1,023 stems per hectare. By planting P. radiata at 2,505 rather than 823 stems per hectare, stiffness can increase by 14%. Stiffness was 41% greater for E. nitens however, P. radiata stiffness can be significantly (P < 0.001) increased by up to 1.2 GPa by planting physiologically aged clones. Stocking had significant effects on tree dimensions (P < 0.001) for both species: DBH decreased in an exponential trend, whereas tree height decreased more linearly. Physiological aging significantly affected DBH (P < 0.0067) but not tree height (P = 0.31). Wind direction was a significant predictor of MOE and as such standing tree stiffness should be measured on the windward and leeward sides of the tree to account for compression wood. At present, the potential of E. nitens as an alternative structural timber species is limited by its poor sawing and machinability due to growth stresses. However, the increasing trend of MOE seen with increasing stocking demonstrates that foresters have a lot of control over the stiffness of a tree crop through the choice and manipulation of stocking, seed stock and species.
Open Access
Non-destructive wood evaluation : operationalising a resistograph in the South Island of New Zealand.
(2023) Doyle, Ryan
In New Zealand, some sawmills are requesting logs above a stiffness grade, prompting forest managers to integrate stiffness-related data into their resource inventories. The IML PD400 resistograph provides a rapid and non-destructive means of sampling trees for density with studies demonstrating a high correlation between site-average estimates of basic density and site-average stiffness of board outturn at a sawmill. OneFortyOne New Zealand has purchased a resistograph with the intention of using the estimates of basic density that it provides to segregate their stands for stiffness. This study investigated the sampling intensity necessary to achieve a probable limit of error (PLE) of 10-15 % for stand-level basic density estimates to help OneFortyOne operationalise the tool. High-intensity sampling was carried out across 15 stands that covered a range of environmental conditions. Simulations of the PLE equation were run in R with the sampling intensity systematically reduced to assess the influence on PLE. Results suggested that sampling programs for stand-level estimates of basic density can be carried out at a very low sampling intensity. With only 10 total measurements across two sample plots, a PLE of less than 12.5% was achieved across the range of stands assessed. Increasing the sampling intensity to 30 total measurements across 15 plots returned a PLE of 2.5-5%. However, beyond this point, further increases to sampling intensity yielded diminishing returns. Decisions relating to sampling intensity should be an operational call that takes into account the findings of this study alongside manager experience and knowledge of wood variability across a forest estate. Further research should be conducted to confirm the relationship between site-average estimates of basic density and site-average stiffness of board outturn. The IML PD400 and the processing software is a rapidly evolving space that will likely continue to be adopted as wood product customers demand higher quality logs.
Open Access
Immersive virtual reality for children in formal education.
(2023) Belter, Meike
This PhD thesis explored the integration of virtual reality (VR) technology into formal education, specifically targeting school-aged children. While VR has gained traction primarily for entertainment, this study sought to harness its immersive potential for educational purposes within, for example, schools. Games have long been recognized as valuable tools for enhancing learning experiences. In recent years, schools have increasingly adopted them, particularly in subjects such as math. Not all learning methods and tools are inclusive to all learners. Common challenges for children in a school context are inattention and hyperactivity. VR, with its ability to create immersive and customizable environments, presents an intriguing avenue for addressing these challenges. To address this, a VR math game was developed for this research, drawing from established educational frameworks and insights garnered from subject matter experts. Through qualitative interviews and thorough requirement analysis, the game’s design was refined. Subsequently, two user studies were conducted within real-world school environments. The initial study focused on assessing usability and refining the prototype based on user feedback. Encouraging outcomes paved the way for a more extensive second study. This followup delved into the influence of a reward system and virtual agent on the user experience, and comparing the VR game against a non-VR counterpart. The findings demonstrated that the VR game not only cultivated positive user experiences but also heightened motivation and engagement. Despite these promising results, further exploration is necessary to determine the role of ‘peerpresence’ in VR learning, and the game’s suitability for children with clinically diagnosed attention and hyperactivity issues. This research adds valuable insights into the process of creating inclusive and effective VR learning experiences. Through a comprehensive research approach, including design, usability testing, and user studies, the thesis underscored the potential of VR to enhance user engagement and experiences within educational contexts.
Open Access
Percolating networks of nanoparticles for neuromorphic computing.
(2024) Heywood, Zachary
Inspired by biology, neuromorphic (brain-like) computing aims to capture the incredible capabilities of the human brain with physical devices. The brain completes numerous complex tasks such as pattern recognition using a fraction of the time and energy of conventional computers. In order to build systems with similar computational abilities, it makes sense to investigate systems that have intrinsic brain-like qualities. Percolating networks of nanoparticles (PNNs) have many features that make them suitable for neuromorphic computing. The neuromorphic properties of PNNs have previously been demonstrated for simple two-electrode devices. Multiple electrodes are required, however, for the implementation of PNNs as the reservoir in a conventional reservoir computing (RC) scheme, where multiple inputs and outputs are used. This thesis focuses on simulations of PNNs and it is demonstrated that the neuromorphic properties are conserved in devices with multiple electrodes. RC utilises temporal correlations in a dynamical system in order to perform computation. A model for operating in the low-voltage tunnelling regime is described, which allows PNNs to be used as the physical reservoir. A range of benchmark tasks are successfully performed and the effect of network size on RC performance is investigated. The RC scheme is extended to the emulation of swarming behaviour, like that seen in flocks of birds. A number of approaches are investigated and a novel method is developed that produces ‘swarm-like’ behaviour with PNNs for the first time. The results presented in this thesis demonstrate that PNNs have capability for neuromorphic computing and show that there is promise for solving even complex problems.
Open Access
Noodle : design of a modular and re-configurable serpentine robot, with series elastic actuators and modular ventral panels.
(2023) Lay, Gordon
In the field of mobile robotics, there is a substantial challenge surrounding reliable navigation of unstructured environments with irregularities. A robot capable of versatile and robust locomotion is required, in order to handle randomly cluttered environments, which may also vary in substrate. This problem has two interdependent components; the physical form of the robot, and its mode of locomotion, or gait. By observing nature, researchers can find inspiration in organisms that have spent decades of evolution becoming expertly adept in particular tasks, and manifest this through behaviours and physical features. As a species, snakes are fascinatingly versatile at locomoting; depending on the substrate and irregularities of the environment, various gaits are used. The physical features of biological snakes are also diverse; microscopic ventral scale structures vary with habitat and primary gait. These scale structures impact the frictional properties of the ventral scales, resulting in varying degrees of anisotropy. The physical form of biological snakes is also attractive from a design perspective; a slender form, instrinsic stability and hyper-redundancy make a snake-inspired robot (snake robot) ideal for navigating cluttered environments. A snake robot able to harness the diverse set of available snake gaits presents an appealing solution to versatile locomotion. The aforementioned relationships between substrate, gait and ventral scale structure are conflicting, however; for a snake robot to perform all snake gaits, it must also possess ventral scales that can vary in structure. This thesis presents Noodle; a cost-effective snake robot with modular ventral panels on the sides of its body. This enables configuration of the ventral contact surfaces prior to deployment onto a given substrate, and the ability to ‘select’ its ventral side simply by rolling. By modularising the contact surfaces into these panels, access to varying degrees of frictional anisotropy is granted simply by swapping them. The cross-section of Noodle ressembles a chamferred square; thus, there are up to 4 unique sets of panels able to equipped at a time. Two panel designs are 3D printed from PLA, to assess the effectiveness of altering geometry to achieve frictionally isotropic and anisotropic designs. The anisotropic design is able to achieve 3 times more friction in the lateral direction than longitudinal when interacting with carpet, which served as a textured, slightly yielding surface. The body of Noodle is modularised into identical single degree of freedom (DOF) segments, which may be appended to one another with the rotational axes in parallel, or alternating in pitch and yaw; these achieve the planar and 3D configurations, respectively. Through the inclusion of series elastic actuators (SEA), compliance and torque sensing are achieved. The SEA is realised by attaching a compliant element in between the servo motor and driven segment. A conventional hobby servo was used. Two designs of compliant element, or series elastic element (SEE), are presented: coil spring and elastomer, where the latter is used in the final design. The material properties of elastomers depend on temperature, while the elastomer itself exhibits dampening and hysteretic deformation; the coil spring SEE offers higher temperature invariance and no hysteresis, but meeting the stiffness requirements of the SEE were challenging. Furthermore, the elastomer SEE is much simpler to manufacture, and its shortcomings have been shown to be relatively minor in the use case of a snake robot SEE. The elastomer SEE is experimentally characterised to have a torsional stiffness constant of 3.54 [N·m/rad]; with a 12-bit rotary encoder resolution, a 0.005 [N·m] torque-measurement resolution is achieved. Each segment of Noodle consists of a custom embedded system, SEA, and 3D printed body. Special attachments to ressemble the head and tail are also included in the proposed design. These attachments, the segment bodies, and parts of the SEA, are 3D printed from PLA; a cost-effective manufacturing decision that also allows for rapid prototyping. To validate the design and assess gait-execution capabilities, Noodle is configured in the planar configuration, with a total of 8 joints. The average cost per segment module is 158 NZD. In the planar configuration, with the joints acting in the pitching direction, the rectilinear gait can be implemented; the robot propels itself by executing successive poses that ressemble a dorsally-propagating wave. The impacts of the wave parameters on average movement speed are investigated; keeping temporal frequency constant (which will self-evidently affect movement speed) and using a range of values for amplitude and phase shift, speeds between 2.5±0.1 and 5.2±0.1 [cm/s] are achieved. A control architecture and system are proposed, based on the embedded architecture and torquemeasuring SEAs. Local stiffness control (LSC) is implemented, which allows closed-loop control of the joint stiffnesses, which in turn achieves adaptive behaviour in response to environmental stimuli. The effectiveness of the LSC is evaluated across several experiments wherein Noodle successfully overcomes an obstacle approximately 70% of its own height, using the impedance variation of the LSC. The results show decreased time taken to conquer the obstacle with increasing torque control gain, to an extent; beyond a certain gain value, the decrements in the times taken become marginal. The implications of the control and embedded architectures on the control system responsiveness are also evaluated. Noodle, with its modular ventral panels, poses an appealing solution to the problem of conflicting snake gaits, ventral surface properties, and traversed substrate. Preliminary planar control with joint torque feedback is demonstrated, paving the way for the implementation of sophisticated 3D gaits. Ultimately, these elements make Noodle an excellent intermediate platform in the pursuit of mobile robots capable of navigating unstructured environments with irregularities.
Open Access
Sequential of acid, alkaline and torrefaction of wood pre-treatments to improve bio oil quality through fast pyrolysis.
(2023) Mohd Safaai, Nor Sharliza
Alternative and renewable energy sources have been explored and investigated over the world to meet the sustained increase in energy demand of and to abate the environmental problems due to heavy reliance on fossil fuels. Woody biomass has abundant resources and is renewable, therefore attracting great interest in the production of energy and fuels. In New Zealand, radiata pine is a dominant species in plantation forests, and residues from forest harvesting and wood processing have a strong potential for energy conversion because it is readily available at relatively low costs. Fast pyrolysis offers a promising way to turn the woody biomass into a liquid product called bio-oil at high yield, together with non-condensable gases (NCGs) and solid char as byproducts. Bio-oil has an extremely complex composition, consisting of hundreds of organic oxygenate compounds as well as water. The qualities of the bio-oil degrade with time during storage. In order to improve the bio-oil quality, bio-oil upgrading has been investigated, however, this normally operates at high temperatures and high pressure thus is a costly operation. Biomass pretreatments have also been reported in which some undesirable components in the biomass are removed before the pyrolysis thus better quality of bio-oil can be produced in the pyrolysis. This study aims to investigate the effects of various biomass pretreatments on bio-oil yield and composition from the subsequent pyrolysis. The biomass pretreatments include solely torrefaction and chemical pretreatments, as well as their combinations. In the chemical pretreatments, sulfuric acid (0.5%, 1.0%, 1.5% and 2.0%) and sodium hydroxide (4%, 7%, 10% and 13%) were used, while torrefaction was performed at 220 and 250 oC. These pretreatments produced treated biomass samples identified as AC (acid), AL (alkaline), ACAL (acid followed by alkaline), ALAC (alkaline followed by acid), ACTO (acid followed by torrefaction), ALTO (alkaline followed by torrefaction), ACALTO (acid + alkaline + torrefactoion) and ALACTO (alkaline + acid + tporrefaction), representing the pretreatment methods. Based on the analyses, the sample treated with solely acid (AC) showed high volatile matter (80.2%), indicating high volatilization during the subsequent pyrolysis. Biomass treated with alkaline (AL) illustrated a slight reduction of volatile matter (76.8%), which would hinder the volatilization process in the subsequent pyrolysis. ACAL and ALAC samples had 76.6% and 85.7% volatile matters, respectively. With torrefaction pretreatment, the volatile matter was further reduced, ranging from 72.9% to 80.02%. The reduction of inorganic elements in the biomass was also observed after the chemical pretreatments. Upon torrefaction as the last step, each studied sample portrayed a unique behaviour upon degradation, reflecting its unique elemental composition attained from earlier chemical pretreatment. Of all the samples including the torrefaction, the ACTO-250 sample showed more cracked fragments which could be linked to the effective inorganic removal and small molecular compounds by acid due to low lignin content. All treated samples showed changes in concentration of alkali metals and alkaline earth metals (AAEMs) recorded after analysis using ICP-OES unit. Morphological images from SEM recorded massive destruction after pretreatments that was obviously due to the elimination of lignin and hemicellulose during pretreatments. Thermogravimetric analysis (TGA) tests of all samples were conducted to investigate the pyrolysis kinetics by determination of the activation energies (Ea) and pre-exponential factors (A) in various kinetic models, including Kissinger, Kissinger-Akahira-Sunose (KAS), Flynn- Wall-Ozawa (FWO), and simplified Distributed Activation Energy Model (DAEM) methods. The results show that the Ea values for all of the treated samples ranged between 170.9 and 270.9 kJ mol−1 for Kissinger model 170.1–262.3 kJ mol−1 for KAS model, 186.2–259.2 kJ mol−1 for FWO model and 169.3–266.3 kJ mol−1 for DAEM model, respectively. The mean Ea values of the pretreated samples increased in comparison with that of the Control sample. In general, the Ea values increased over the degree of conversion from 0.2 to 0.8 attributed to the crystallinity and carbonisation effects upon the pretreatments. The A values determined for all of the treated biomass samples varied over a broad magnitude ranging from 105 to 1026 s−1 for the adopted kinetic models. Fast pyrolysis of the pretreated biomass samples and the Control sample were conducted in a lab-scale fluidized bed reactor at 400, 450 and 500oC for the production of bio-oil. The bio-oil was analysed for its chemical composition using GC-MS, NMR, FTIR and ICP-MS. Water content, acidity and viscosity were also determined using corresponding techniques. For the chemically-treated samples, the highest bio-oil yield was recorded from AC (39.72 wt%) at pyrolysis temperature of 450°C whereas the highest bio-oil yield from pyrolysis of pretreated samples including torrefaction was 34.05 % for the ACTO sample at the same pyrolysis temperature of 450°C. The bio-oil yields in these two cases were higher than that from pyrolysis of the Control sample (32.79±7.93%) at the same pyrolysis temperature. This study revealed that both chemical pretreatment and torrefaction of biomass were required to overcome the drawbacks of bio-oil from raw biomass. Using acid as the medium of pretreatment is preferable than using alkaline due to the suppression of inorganic matters in biomass and subsequent bio-oil. Torrefaction lowers the cost of biomass grinding, which is essential in balancing the higher process costs for pretreating biomass. Therefore, the combinatorial approach of pretreatments is required to improve the quality of crude bio-oil, depending on the final usage. By comparing to the Control bio-oils and other fuels, the results proved that less works are required to further upgrade the oils from ACTO and ALACTO pretreatments. Thus, ACTO and ALACTO bio-oils have the potential to be applied as transportation fuel with further upgrading process. Other applications are bio-adhesive (phenol), bio-based pesticides and biodegradable plastics.
Open Access
Computational modeling of 3D printed porous media for process engineering.
(2023) Kadzungura, Luckmore
Triply periodic minimal surface (TPMS) structures, known for their unique geometric properties such as high surface area, customizable pore structures, and continuous networks, are evaluated as promising candidates for process engineering applications, including separation, heat exchange, and fluid flow management. This thesis details a computational approach to model and analyze TPMS structures in the Open- FOAM environment using the Finite Volume Method (FVM). Phenomena such as pressure drop, particulate flow, residence time distribution, heat transfer in TPMSbased heat exchangers, and adsorption were all simulated, with the computational results validated by experimental studies. The investigation centered on the Schoen Gyroid, Schwarz Primitive, and Schwarz Diamond surfaces, generated by implicit mathematical functions and parameterized to manipulate pore size, unit cell size, and overall shape. Insights were derived on how the selection of TPMS structures and geometric parameters impact process engineering applications. The determination of pressure drop across different TPMS structures, for both laminar and turbulent flows, was found to be influenced by their inherent pore connectivity and tortuosity. The contrast between low and high Reynolds numbers clearly illustrated as the transitional fluid flow behaviour at about Reh = 20. Additionally, particle flow behaviour was seen to be affected by variables such as pore size, velocity, particle size, and surface properties. A study of the residence time distribution in TPMS structures showed that cell orientations pose effects on the perfomances and also provided insights into their potential use in mixing and reaction engineering. The performance of TPMS-based heat exchangers was evaluated, with findings showing efficient operation at low Reynolds numbers 20 Reh 300, pointing to their potential for effective heat transmission due to the extensive surface area and interconnected channels. In separation processes, the adsorption capabilities of TPMS structures were analyzed, highlighting the importance of customized surface qualities for enhanced selectivity and capacity. Experimental tests conducted to validate the computational findings supported the projected performance of TPMS structures in various process engineering applications, particularly in the areas of fluid flow and heat transfer, which validates the credibility of the computational models. In conclusion, the research offers an in-depth, experimentally validated computational methodology for modeling TPMS structures for process engineering applications, placing emphasis on their performance across diverse applications. The groundwork is laid for the development and optimization of innovative TPMS-based materials with application-specific advantages, thereby contributing to the advancement of more efficient and sustainable process engineering solutions.
Open Access
Modular multilevel converters for electric vehicle applications.
(2024) Omar, Alaa
The increasing focus and global support for the transition to electric vehicle traction systems drive rapid advancements in electric vehicle technologies. One essential component of electric vehicles is the main traction converter, which controls the power flow and drives the electric motor. Additionally, a dedicated arrangement is required for managing the batteries state of charge and the charging process. The modular multilevel converter with submodules that comprises half-bridges and batteries is currently being investigated for its suitability in traction systems. This converter offers many advantages in terms of integration, modularity, and redundancy. It combines multiple functions of various electrical components within the vehicle, and it can partially support vehicle operation even during undesired battery conditions. In this research, a real-time emulation approach of the modular multilevel converter is developed using MicroLabBox/dSPACE to investigate the operation of the converter. A physical prototype of the converter is also constructed in the laboratory and compared to the real-time model to validate its accuracy and effectiveness. This model is implemented by utilising a single look-up table in each arm of the converter. The dynamic performance of the converter in the emulated system resembles the dynamic operation of the converter prototype, confirming its fidelity and suitability for further investigations. The developed model is then integrated into a simplified real-time model of the vehicle to demonstrate the converter’s potential in driving the motor, balancing battery state of charge, and regenerative braking. Furthermore, the research investigates a novel approach for balancing the average state of charge of the converter phases and demonstrates the override capability of the converter through the integration of an override subroutine in the central control and balancing system. The balancing arrangement is independent on the system parameters and reduces the number of controllers required in the converter’s conventional balancing arrangement. This approach balances the average state of charge of the converter legs during different vehicle driving conditions. This investigation also shows that a balanced converter operation can be achieved while overriding particular submodules due to undesired conditions. A practical approach to minimise the sensing devices in the converter is developed in this thesis. Instead of using hundreds of sensors, only six sensors are utilised to estimate the voltage of the individual submodules. This approach reduces the cost and minimises the potential points of failure in the system. Also, this approach reduces the required analogue inputs in the controller system, particularly for systems with a large number of submodules. Finally, this research investigates the utilisation of the converter as an onboard charger without altering the converter connection or adding extra components. This charging arrangement enables faster charging of batteries with a lower state of charge and ensures equalised charging of all batteries in the converter. The charging arrangement is for a single-phase source and can be used for three-phase source charging if needed. In summary, this thesis studies the utilisation of the modular multilevel converter as a central traction converter in electric vehicles. The investigation provides an optimal and reliable converter integration to achieve multiple functions in the electric vehicle system. The optimisation includes a balanced converter operation under various driving conditions and implementing a submodule override algorithm. The reduced number of sensors enhances the overall reliability of the converter while reducing the cost. The research is conducted using a validated real-time emulated model of the converter in conjunction with a laboratory prototype converter. This work can also be extended to investigate many potential electric vehicle drive system optimisations.
Open Access
Using field based power meter data to model track cycling performance.
(2023) Ferguson, Hamish
Track cycling events, both sprint and endurance, are primarily focused on performance of high and medium power durations, and it is suggested, measures of peak power govern performance in the sprint and pursuit cycling events. Various tests and metrics in the laboratory have been used to try and model track cycling. With the advent of power meters cyclists have been able to record power output in the field and several basic tests have evolved to use as a means to get started with training and racing with power. This thesis proposes a linear model based on total least squares regression, to evaluate these models and provide an option for coaches to see what durations are key for performance, and for sprint cyclists what types of training should be performed at a given part of a training build up. This analysis is applied to sprint cycling, male and female sprint cyclists, and pursuit cyclists to evaluate field-based data compared to lab and model derived metrics. The key conclusions from this thesis are: 1. For each specific power duration along the hyperbolic power-duration curve shows field-based data offers a better model for both sprint and pursuit durations. The linear model has a parabolic relationship the closer the inputs get to the specific duration assessed. 2. This disproves the contention of a linear process governed by peak power being the key metric of sprint cycling. The data in this thesis shows not only is this relationship incorrect, but strong relationships with sprint cycling durations hold for durations as long as 20-min. 3. This thesis finds there are sex differences for the model showing women have a higher variation of sprint power than men. 4. The linear model is applied to track endurance cycling to show, again, how a peak power (or maximal sprinting power or 𝑉̇O2max) does not govern performance, more a broad base of capacity reflected by a high lactate threshold, ventilatory threshold, critical power or other estimates of the maximal metabolic steady state. 5. Based on an understanding of the importance of capacity as well as peak power Chapter 6 shows this information can successfully be applied to the performance of sprint cyclists training towards peak performance.
Open Access
The effects of applied stress and heat treatment on the stress corrosion cracking behaviour of manganese bronze.
(2023) Manz, Olaf
Stress corrosion cracking (SCC) is a cracking mechanism requiring a tensile stress on a susceptible material in a corrosive environment. Changes to, or the removal of, any of these three conditions can cause significant impacts on the SCC susceptibility. The propagation of SCC is typically described as being predominately transgranular (TG) or intergranular (IG). AW Fraser is an original equipment manufacturer (OEM) that produces extrusions and precision machined components from bronze alloys. The particular alloy used for this project’s investigations is a manganese bronze designated as UNS C86300, which is primarily used in high-wear engineering applications such as bushings in earthmoving equipment due to its excellent strength and wear resistance. The material consists of equiaxed grains of the BCC β-phase, with iron-rich κ-phase precipitates within the grains and at grain boundaries. Cracks were discovered in parts of rough-machined UNS C86300 after as little as 24 hours when stored outside. A failure analysis determined the cracking mode to be intergranular SCC due to the residual stresses from rough machining. A preliminary project found UNS C86300 to be susceptible to SCC in an environment of deionised water. The current method AW Fraser uses to prevent SCC in these parts is to cast sections far thicker than the final part to reduce the residual stresses induced by the clamping force of the lathe chuck, yet this process increases production time and cost significantly. SCC in copper-based alloys has been extensively researched after first being documented in the late 19th century, and the effects of the environment, material, and stress are well understood. However, the majority of the research focuses on α-phase alloys. Although there are some documented cases of β-phase brass alloys experiencing SCC in deionised water, there is a gap in the literature concerning this phenomenon. To contribute towards filling this gap in the literature and to provide valuable data to AW Fraser, the effects of applied stress and heat treatment on the SCC behaviour of UNS C86300 have been investigated. As-received, stress-relieved, annealed, and quenched C-ring specimens were tested in deionised water at applied stresses ranging from 25–95% of the material’s yield strength. Dezincification susceptibility tests and various analytical methods have been conducted on selected specimens to determine any relationships between failure time and applied stress or heat treatment.
Open Access
Kōpaki Waiora Tamaiti o Aotearoa | New Zealand Child Wellbeing Project
(2023) Knight, Ashley Rose
The aim of this MProdDesign project was to design an intervention product and/or service that supports childrens’ emotional regulation (ER) learning within primary education in Aotearoa. Aotearoa has cultural and environmental influences that have greatly affected our tamariki (children’s) development. Aotearoa has a history of colonization and ongoing coloniality that has caused inequities in educational and health societies that has impacted behavioural and social norms (Hobbs et al., 2019). These influences have caused wellbeing and mental health deficiencies for tamariki that may inhibit their behavioural, social, and emotional skills as they grow. Emotional regulation (ER) is the extrinsic and innate processes responsible for monitoring, evaluating, and modifying emotional reactions (Thompson, 1991). Thus, ER is important in aiding a tamaiti (child’s) ability to identify, understand and integrate emotional information while managing behavioural responses (e.g., anger, sadness, distress) to different situations (Adrian, Zeman, & Veits, 2011). Progressive (and government supported) Modern Learning Environments (MLE) have shifted towards holistic pedagogies. Some holistic teaching approaches promote ER techniques to support the development of behavioural, emotional, and social capacities. One way that MLEs integrate teaching of ER skills is through the practice of mindfulness. Mindfulness refers to a state of awareness that is focus on one’s present moment experiences, with an attitude of non-judgement. (Shapiro, Carlson, Astin, Freedman, 2006). Mindful awareness is cultivated through formal meditation practices (e.g., focusing on relaxation sounds like heartbeats, breathing patterns) and through formal practices that involve bringing mindful awareness to everyday activities (e.g., showering). Mindfulness has previously been linked to emotional regulation by promoting enhanced attention in the present moment. Mindfulness can improve an individual’s ability to attend to specific aspects of a situation, as well as aspects of their own experience (e.g., mental and/or physical awareness) (Roemer, 2015; Roemer, Williston, Rollins, 2015). Using a product design-focused codesign framework, this project facilitated research focus groups that directed design decisions and developments from learner and education facilitator insights. As a result, mindfulness-based wearable prototypes were produced and play-tested with young learners and education facilitators over a 5-week period. The qualitative testing data conveyed what functional, aesthetic, sensorial and ergonomic aspects were successful and what were shortcomings for both young learners to use and for education facilitators to deliver within a Modern Learning Environment. Thematic analyses of the testing data proved that the learner participants maintained consistent engagement with the prototypes over the testing period and found them an effective tool to aid in refocusing their attention to the present moment during their school day and mindfulness lessons. This project opens future opportunities to explore lesson plans and projects that are framed with both learners and their education facilitator teams to grow their familiarity and engagement with their mindfulness journeys together.
Open Access
Ground motion simulations validation via response of complex structures.
(2023) Loghman, Vahid
This dissertation addresses a diverse range of applied aspects in ground motion simulation validation via the response of complex structures. In particular, the following topics are addressed: (i) the investigation of similarity between recorded and simulated ground motions using code-based 3D irregular structural response analysis, (ii) the development of a framework for ground motion simulations validation to identify the cause of differences between paired observed and simulated dataset, and (iii) the illustration of the process of using simulations for seismic performance-based assessment. The application of simulated ground motions is evaluated for utilisation in engineering practice by considering responses of 3D irregular structures. Validation is performed in a code-based context when the NZS1170.5 (NZS1170.5:2004, 2004) provisions are followed for response history analysis. Two real buildings designed by engineers and physically constructed in Christchurch before the 2010-2011 Canterbury earthquake sequence are considered. The responses are compared when the buildings are subjected to 40 scaled recorded and their subsequent simulated ground motions selected from 22 February 2011 Christchurch. The similarity of recorded and simulated responses is examined using statistical methods such as bootstrapping and hypothesis testing to determine whether the differences are statistically significant. The findings demonstrate the applicability of simulated ground motion when the code-based approach is followed in response history analysis. A conceptual framework is developed to link the differences between the structural response subjected to simulated and recorded ground motions to the differences in their corresponding intensity measures. This framework allows the variability to be partitioned into the proportion that can be “explained” by the differences in ground motion intensity measures and the remaining “unexplained” variability that can be attributed to different complexities such as dynamic phasing of multi-mode response, nonlinearity, and torsion. The application of this framework is examined through a hierarchy of structures reflecting a range of complexity from single-degree-of-freedom to 3D multi-degree-of-freedom systems with different materials, dynamic properties, and structural systems. The study results suggest the areas that ground motion simulation should focus on to improve simulations by prioritising the ground motion intensity measures that most clearly account for the discrepancies in simple to complex structural responses. Three approaches are presented to consider recorded or simulated ground motions within the seismic performance-based assessment framework. Considering the applications of ground motions in hazard and response history analyses, different pathways in utilising ground motions in both areas are explored. Recorded ground motions are drawn from a global database (i.e., NGA-West2 Ancheta et al., 2014). The NZ CyberShake dataset is used to obtain simulations. Advanced ground motion selection techniques (i.e., generalized conditional intensity measure, GCIM) are used for ground motion selection at a few intensity levels. The comparison is performed by investigating the response of an example structure (i.e., 12-storey reinforced concrete special moment frame) located in South Island, NZ. Results are compared and contrasted in terms of hazard, groundmotion selection, structural responses, demand hazard, and collapse risk, then, the probable reasons for differences are discussed. The findings from this study highlight the present opportunities and shortcomings in using simulations in risk assessment. i
Open Access
Deteriorated capacity assessment of aging bridge structures in seismic areas complimented by artificial intelligence modeling.
(2023) Matthews, Benjamin James
Chloride-induced deterioration of reinforced concrete (RC) structures severely depreciates the mechanical advantages provided by the composite action of concrete and steel reinforcing. Degradation of the embedded steel and succedent effects on the surrounding concrete occur naturally over several decades, depending on the in-situ environmental conditions and construction quality. As many RC structures are reaching the end of their initial design lives, progressive deterioration of the reinforcing steel over time has created a far-reaching issue of compromised structural reliability, particularly in seismically active zones. Transverse reinforcement faces additional susceptibility to decay, due to its geometric and physical design relative to the longitudinal steel. The increased vulnerability alludes to an accelerated loss of shear and confinement-related mechanical properties as degradation advances with time. This Ph.D. research explores the implications of chloride-induced corrosion on the mechanical response of degrading RC members. The project is separated into two primary scopes. The first involves a comprehensive multi-phase experimental program to characterize the effect of corrosion on the cyclic shear degradation of affected circular RC columns. The second explores machine learning as a high-performing alternative to conventional modeling approaches, for predicting key mechanical properties in degrading RC members. Artificially accelerated methodologies have become indispensable for achieving a broad spectrum of corrosion damages, enabling researchers to analyze the performance of affected reinforced concrete elements. However, an issue exists in over- accelerating the process, which creates unrealistic morphologies, limiting the experimental value of the test. An experimental study is undertaken to investigate the effects of the degree of acceleration on the corrosion morphology, sectional properties, and crack distribution of laboratory-scale RC elements. Twenty-four RC cylinders were constructed, corroded at two current densities, two concrete cover thicknesses, and using two variations of the impressed-current method. Results suggest a maximum upper bound threshold of 300 µA/cm2 should be used to ensure realistic corrosion morphologies and crack behavior. It is recommended that wet-dry phasing be implemented as the primary variant of the impressed-current method because of its superiority in producing morphologies, sectional properties, and cracking that adequately reflect those found in naturally corroding elements. This experimental phase also serves as a calibration benchmark for the proceeding artificial corrosion implementation on large-scale RC circular columns. The ever-growing volume of experimental and field data continually enables advances in the field through deeper micro-macro analyses and various modeling applications. Machine learning offers powerful and robust methodologies for improving the predictive capabilities of complex phenomena, with the additional benefit of continual adaptability as more data emerges. An experimental phase is introduced, describing the tensile testing of 284 artificially corroded, 25 mm diameter deformed Grade500E reinforcing bars. Next, the mechanical characteristics of corroded bars are predicted through a collection of regression-based machine-learning algorithms. Models are trained and tested on a database of 1,387 tensile tests compiled from 25 other experimental programs available in the literature. The complete database includes 19 input parameters used to predict nine key mechanical properties of the corroded steel bars: yield force, ultimate force, effective yield stress, residual engineering yield stress (%), effective ultimate stress, residual engineering ultimate stress (%), ultimate strain, elastic modulus, and ductility. Nine machine learning models were selected from a balanced assortment of algorithm typologies to determine the most appropriate methodology for each response variable. Literature-supplied decay laws serve as null models for statistical analysis. Results indicate that machine learning applications can drastically improve the predictive accuracy for both strength and displacement-based characteristics. The adaptive-neuro fuzzy inference system (ANFIS) model was found to have the strongest individual predictive ability across all models. Meanwhile, ensemble tree-based learning algorithms categorically provided the most consistently high-performing models over the selected response variables. Following on from the small-scale corrosion phase, a similar comparative assessment of two artificial corrosion techniques was undertaken in large-scale circular RC columns to quantify the authenticity of the induced damage patterns. The impressed-current method was divided into two subgroups – constant saturation and wet-dry phasing, at two imposed current densities of 200 µA/cm2 and 300 µA/cm2. The assessment was applied over a large-scale experimental program, testing the cyclic shear behavior of eight circular RC concrete piers. Analyses were conducted from the local corrosion distribution and morphology scale through to each test specimen’s global structural behavior and cyclic response. The seismic shear response of fourteen scaled circular RC piers subjected to artificial chloride-induced corrosion is then investigated. Each pier was designed to trigger a shear-dominated failure and artificially corroded at two current densities. A further parametric study is undertaken, investigating the influence of confinement effective- ness, spiral diameter size effect, and pier aspect ratio on the rate of cyclic shear loss. As corrosion increases, a shift in failure mode towards a more brittle mechanism is consistently observed. Significant reductions in shear capacity were observed, with significant implications on the ultimate deflection capacity at severe levels of deterioration. In the most severe case, a maximum reduction of 37.5 % and 70.9 % were recorded in peak shear capacity and ultimate deflection, respectively. A series of empirical modifications to an existing three-step analytical model is proposed to derive the cyclic shear capacity of circular RC columns considering corrosive conditions. The results of sixteen shear-critical RC columns, artificially corroded to various degrees and tested under quasi-static reversed cyclic loading, were used for model verification. Two simplified degradation models are developed to serve as performance benchmarks. The final model is proposed in a stepwise format relative to the measured damage of the steel reinforcement. New empirical decay law coeﬀicients were derived for determining the degraded material properties based on the extensive database of over 1,380 corroded tensile tests. An additional experimental database of 45 corroded RC circular piers, with displacement ductilities ranging between 1.4 to 11.9, was collected to assist in the modification of ductility- based parameters. The results of the model, compared to experimental tests failing in shear-dominated modes, indicate that the peak shear capacity can be predicted well across a range of deterioration severities (0 – 58.5 % average transverse mass loss). As corrosion damage increases, the distribution of the corrosion relative to the location of the shear plane becomes a critical performance consideration, increasing predictive variance. Lastly, an extensive database is introduced, aggregating 54 experimental programs with 804 test specimens and 45 input parameters, investigating the implications of chloride-induced corrosion on the deteriorated response of corroded reinforced concrete beams. Several statistical models are explored to determine the highest performing predictor for five key response variables – the residual ultimate moment capacity, residual capacity factor, yield load, yield displacement, and the ultimate displacement. Three existing analytical approaches were included for comparative purposes to test the eﬀicacy of the trained statistical models. The optimized machine learning models outperformed conventional analytical approaches and achieved high levels of predictive accuracy. Ensemble tree-based learning algorithms consistently produced the best predictions.