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Fault zone architecture, deformation conditions, and kinematics of the Camp Lake and Offset faults of the Lac des Iles Mine, Northwestern Ontario, Canada
Full text linkFaults and their associated damage zones are important geologic structures that serve as permeable pathways through the upper crust. The development of fault cores and damage zones is typically controlled by the strength and composition of the protolith, conditions of deformation, and fluid chemistry. The effect of host lithology on fault core development and damage zone structure is currently poorly constrained. This study uses the Lac des Iles palladium mine in northwestern Ontario, Canada as a natural laboratory to study how faults behave in different lithologies. The Lac des Iles mine is hosted in the 2.689 Ga ± 1.0 Ma Lac des Iles mafic-ultramafic intrusion with current reserves of ~5 Moz of 3E (Pd+Pt+Au) at an average grade of 2.6 g/t. The intrusion hosts numerous mineralized zones, most notably the Roby, Offset, and Camp Lake zones, divided by faults. The Camp Lake and Offset faults are two major structures that offset blocks of the ore body within the Lac des Iles mine, with displacements of ~500 and ~275 m, respectively. The faults crosscut gabbronorite and tonalite, often with these rock units in fault contact with each other.
We studied the variation in fracture density surrounding the Camp Lake and Offset faults to quantify how damage zone structure changes with respect to the host lithology. Fracture density decay rates within damage zones (with distance from the fault core) show that fractures in tonalite decay at a faster rate than gabbronorites, irrespective of whether they are in the hanging wall or footwall. The fault cores in gabbronorites are characterized by chlorite-rich gouges whereas tonalite fault cores are composed of silica-rich cataclasites. It is hypothesized that the development of a frictionally weak, chlorite-rich fault core impeded the development of a more fracture-dense damage zone in the gabbronorite. Results from whole-rock geochemistry show variations in major elements that correlate with the largest zones of visible alteration and deformation within the damage zone, and no significant rare earth element variation that can be attributed directly to the faulting. Electron microprobe analysis of chlorite was conducted on fault core and host rock samples to constrain the temperatures of deformation. Three notable clusters in the temperature data were observed, interpreted to represent periods of chlorite formation that were pre-, syn- and post-faulting (290°C, 236°C, and 110 – 175°C, respectively).
A combination of structural and geochemical data shows that the Camp Lake and Offset faults have undergone multiple deformation events, with pulses of hydrothermal fluids altering the mineralogy and geochemical signature of the surrounding rocks in the Lac des Iles mine. Palladium mineralization is depleted within the fault core and damage zones. It is hypothesized that hydrothermal fluids associated with faulting are the cause of stripped palladium mineralization.
This research highlights the interplay of the geological processes associated with faulting and fluid migration and how they have affected the distribution of palladium within the Lac des Iles mine. Understanding the relationship between faulting and economic mineralization can improve exploration strategies and guide mining efforts for the future
In the interest of reconciliation in education: inclusive indigenous content and modifications to the Ontario social studies and history curriculum from 1998 to 2023
Full text linkThe Ontario Social Studies and History curriculum aids students in developing skills, knowledge, understanding, and attitudes that will benefit them in the classroom, their communities, and beyond. Nonetheless, there are disparities in what should be emphasized or included and which historical perspectives matter. Teachers have to deliver Indigenous content to students respectfully and thoroughly yet are provided with few tools and opportunities to do so. While the Ontario Social Studies and History curriculum includes Indigenous histories, its content is limited, and its use in the classroom solely depends on how knowledgeable and comfortable teachers are with the topic. Educators have expressed concern about teaching Indigenous topics while unprepared, under-resourced, and lacking sufficient time and support to convey the material to students effectively. While the Ontario Ministry of Education states it is doing all it can to create an inclusive curriculum covering Indigenous history, the depth of its Indigenous content has yet to be thoroughly examined. Using curriculum design theory and a two-eyed seeing approach, this research examines all elementary Social Studies and History curriculum documents from 1998 to 2023 and analyzes how the Ministry presents Indigenous content to teachers for use in the classroom. My findings show that while Indigenous content in the Social Studies curriculum has improved significantly between 1998 and 2023, gaps remain in key ideas and comprehensive content that would aid in student retention and understanding of Canadian and Indigenous history, as well as Indigenous experiences, perspectives, and subject matter. The curriculum does not adequately cover the impacts of residential schools, forced assimilation, segregation, and other atrocities against Indigenous and other minorities. Canadian history and Indigenous relationships are whitewashed, encouraging misrepresentation, omission, and marginalization while perpetuating biases and stereotypes, minimizing Indigenous voices and creating disparities in the knowledge of Indigenous history
Flow control of low-reynolds number airfoils using morphing surface
No full textThis thesis investigates the application of traveling wave surface morphing as an advanced
active flow control method to enhance the aerodynamic performance of airfoils operating at
low Reynolds numbers of 1000 and 20,000. The motivation for this study stems from the need
to address flow separation and improve aerodynamic efficiency in low-speed applications, such
as micro air vehicles (MAVs) and unmanned aerial vehicles (UAVs). The study focuses on the
NACA 0018 airfoil, analyzing its aerodynamic behavior under various traveling wave
configurations (frequency, amplitude, and wavelength) across different angles of attack,
ranging from 7 to 15 degrees. Through a combination of computational fluid dynamics (CFD)
methods, including the Immersed Boundary-Lattice Boltzmann Method (IB-LBM) and Large
Eddy Simulation (LES), and simulations conducted using OpenFOAM, along with machine
learning (ML) techniques, the research provides comprehensive insights into the optimization
of traveling wave parameters for enhanced lift-to-drag ratios and delayed flow separation. The
findings at a Reynolds number of 1,000 demonstrate that backward traveling waves
significantly improve the aerodynamic performance of the NACA 0018 airfoil. Numerical
simulations show that, for wavelengths between 0.1 and 0.4, the lift-to-drag ratio increases
12% from 3.21 to 3.55, compared to the baseline unactuated case where the ratio remains at
2.83. In contrast, forward traveling waves are shown to decrease the lift-to-drag ratio due to
the induction of reverse flows on the suction side, highlighting the superiority of backward
traveling wave actuation. The results show that amplitudes and frequencies play a crucial role
in achieving optimal flow control. At an amplitude of 0.003 and a frequency of 1.5, backward
traveling waves generate a lift coefficient four times higher than those at a low frequency of
0.25. At a higher Reynolds number of 20,000, traveling wave actuation continues to exhibit
remarkable effects on flow separation control and turbulence management. Results reveal that
backward traveling waves not only enhance lift but also reduce drag by controlling the
turbulent kinetic energy (TKE) and generating coherent flow structures such as quasi-
streamwise vortices and reverse horseshoe vortices. A parametric study shows that a
wavelength of 0.3, an amplitude of 0.003, and a frequency of 1.0 yield the maximum lift-to-
drag ratio of 5.47, compared to 2.91 (i.e. by approx. 88%) for the unactuated airfoil.
Furthermore, large coherent structures (LCS) analysis demonstrates the ability of traveling
waves to stabilize boundary layer dynamics and delay flow separation, especially at higher
angles of attack. For example, at an angle of attack of 11°, the suction peak reduces from −2.15
in the unactuated case to −1.27 with traveling wave actuation, significantly shrinking the
separation bubble. This study also analyzes TWM's effects on boundary layer stability, flow
separation, and vortex structures across angles of attack (7°, 11°, and 14°). The results show
that TWM organizes vortex structures, enhances boundary layer mixing, and delays flow
separation, significantly reducing drag and stall effects. Higher amplitude TWM (a=0.02)
achieves the best results, stabilizing the boundary layer and creating a quasi-laminar flow even
at high angles of attack. These findings highlight TWM as a promising technique for improving
lift and reducing drag in aerodynamic applications. These findings demonstrate the novelty of
applying advanced flow control techniques to a thicker airfoil profile, broadening the scope of
aerodynamic research.
The integration of CFD simulations with machine learning models, such as Gaussian Process
Regression (GPR), Support Vector Machines (SVM), and Decision Trees (DT), enables
efficient prediction and optimization of aerodynamic coefficients. Machine learning techniques
are applied to analyze 93 simulation cases, revealing strong correlations between wave
parameters (frequency, amplitude, and wavelength) and aerodynamic forces. For instance, the
optimal wave configuration at an angle of attack of 11° achieves a drag reduction of 40% and
a lift increase of 20%, reducing computational time significantly compared to traditional CFD
methods.
The thesis highlights the transformative potential of traveling wave surface morphing in
advancing airfoil design for low Reynolds number applications. By bridging numerical
methods and machine learning, this study introduces a practical framework for real-time
optimization of aerodynamic performance. The research establishes that backward traveling
waves are highly effective in mitigating flow separation, enhancing lift-to-drag ratios, and
controlling turbulent flow structures
Photonic sensor based on surface-enhanced raman scattering for the detection of trace chemicals
Full text linkThe research presented in this thesis describes the development of a three-dimensional (3D) tapered optical fiber-based surface-enhanced Raman scattering (SERS) sensor for detecting trace chemicals. The developed system was capable of detecting rhodamine 6G (R6G) and crystal violet (CV) at Picomolar (pM) levels. A Scanning electron microscope (SEM) and an optical microscope were used to characterize the tapered fiber. The unique characteristics of the fabricated SERS substrate, such as the uniform distribution of analyte around a particular diameter of the fiber and a specific location where maximum SERS intensity was observed, have been presented. The developed sensor was used in the real-time detection of chemicals, allowing immediate adjustments. The detection limit of 10-7 M for R6G and 10-8 M for CV was achieved in real time.
A seedless method was used to synthesize gold nanorods (GNRs) with localized surface plasmon resonance (LSPR) closer to the excitation wavelength. The prepared GNRs were tweezed successfully on the tapered fiber surface, and a minimum detectable limit of 10 pM was achieved for CV.
A plasmonic structure using Zinc (Zn) and Zinc Oxide (ZnO) was developed using optical tweezing along the tapered fiber length. The effect of single and double tweezing was investigated. This plasmonic structure has potential applications in biosensing
Computational investigations of integrated Vortex-Odor dynamics in the wake of fish for underwater sensing
Full text linkThis research investigates the interplay between vortex dynamics and odor transport in
undulatory swimming using high-fidelity computational fluid dynamics (CFD) simulations.
Building upon initial two-dimensional (2D) analyses, we extend our study to three-dimensional
(3D) simulations to quantify odor effectiveness and the role of kinematics and morphology in
chemical dispersion. Our results reveal that odor transport is strongly coupled with vortex
structures, with convection dominating over diffusion in aquatic environments. Kinematics,
rather than body shape, primarily dictate odor transport, with anguilliform swimmers generating
broader and more persistent odor trails than carangiform swimmers. Swapping kinematics
between Jackfish and Eel models confirms that swimming motion, not morphology, governs odor
dispersal. Increasing undulation amplitude enhances odor transport by increasing momentum
transfer, reinforcing the dominance of vortex-driven convection. Expanding our study to fish
schooling, we analyze odor dispersion across different group configurations. While lateral odor
spread intensifies with group size, downstream transport remains largely unaffected beyond a
critical distance. Quantitative analysis shows that odor effectiveness decreases linearly with
increased schooling, indicating that collective swimming suppresses, rather than enhances,
chemical cue propagation. These insights advance our understanding of biological chemosensory
mechanisms and inform the design of bio-inspired robotic systems with enhanced chemical
sensing and navigation capabilities
Long bolted HSS-to-HSS connection for modular structures: a solution for indigenous housing challenges
No full textRemote Indigenous communities across Canada are experiencing severe housing shortages and widespread repair needs, both stemming from engineering challenges encountered during construction. To address these issues, prefabricated steel moment-resisting frame modular houses are increasingly being adopted as alternatives to conventional housing. These structures offer several technical advantages, including enhanced quality control, lightweight components, and ease of transportation to remote and rural regions. This thesis explores the application of hollow structural sections (HSS) in panelized steel modular structures by introducing an innovative steel-bolted connection for joining HSS beams to HSS columns using high-strength long bolts as an efficient solution to the Indigenous housing challenge. The proposed connection is designed for easy installation without requiring skilled labour or heavy machinery. This thesis utilizes experimental testing, numerical analysis, and machine learning techniques to comprehensively address the overarching research problem through four integrated studies. In the first study, specimens were fabricated and tested under monotonic loading, with a Digital Image Correlation (DIC) camera used to capture full-field 3D displacement and deformation until failure. This research studies the structural performance of various geometric parameters, including bolt arrangement, extended plate thickness, number of bolts, and the presence of stiffeners in terms of joint stiffness, ductility, ultimate capacity, and failure modes. The second study focused on key connection parameters, including extended plate thickness, bolt arrangement, bolt diameter, and the number of bolts. Results highlighted the critical role of bolt configuration and quantity in maintaining the "strong column weak beam" principle, ensuring plastic hinging at the beam. The third study evaluated the effectiveness of three reinforcement techniques: (1) a stiffener below the extended plate, (2) concrete infill within the column, and (3) a combination of both. These techniques significantly impacted the structural performance of different bolt configurations, preventing premature failures such as extended plate rupture and local column buckling and reducing the ultimate rotation of the connection. Failure mode charts were developed to predict failure modes for both unstiffened and stiffened configurations to streamline the design process. These charts eliminate the need for several iterations of full design analysis, reducing design processing time and trials. In the fourth study, machine learning techniques, including genetic regression, decision trees, and neural networks, were applied to predict the ultimate moment capacity and failure modes of the steel bolted connection under monotonic loading. A dataset of unstiffened configurations from the first study was used to train and test these models, demonstrating high predictive accuracy. Additionally, genetic regression was employed to develop mathematical formulas to predict the ultimate capacity of the connection. These models underscore their potential as reliable computational tools to complement both experimental and analytical approaches
Open access publishing in an African context: Notable improvements and recurring challenges
Full text linkOpen access publishing has been promoted as a pivotal means of bridging the gap in knowledge access and usage. Despite the growing support for open access publishing globally, little is known about African scholars’ engagement with open access publishing and the barriers limiting their open access publishing practices. Using a survey research design, data was collected from 241 researchers from selected universities in Africa, such as Nigerian, Kenyan and South African universities. The data was collected using online surveys and analysed using the descriptive statistics of frequency counts and percentages. The study reveals that while most of the respondents had published open access articles (78.01%) and had a positive perception of the quality of open access journals (73.45%) and editorial teams, more than half were still limited by article processing charges (58.51%) as they had no funding for their research. Although African researchers are embracing open access publishing more now than they were historically, barriers such as article processing charges and the prolonged response time from reviewers continue to pose a serious challenge to open access uptake in Africa. This study proposes five recommendations for improving open access uptake in African and Global South countries
Machine translation in scholarly publishing: A scoping review
Full text linkEnglish occupies a central position in scholarly publishing, but using a lingua franca for scholarly publishing has consequences for scholars, science, and society. For instance, non Anglophone researchers may need longer to read and write in English and may face more manuscript revisions and rejections, potentially leading to a lower volume of research output, which could negatively affect career advancement. To what extent can machine translation (MT) tools (e.g., Google Translate) help to support a more multilingual scholarly publishing ecosystem? To find out, we undertook a scoping review of the literature to investigate how MT tools are being used for multilingual scholarly publishing. Following a multilingual search in nine bibliographic databases, 875 papers were retrieved and screened, and 39 were included for closer investigation. Analysis reveals that MT tools are being actively developed, tested, applied, and evaluated in the context of scholarly publishing. However, at present, these tools are not displacing English from its central position; the main use of MT tools currently is to reduce the burden of publishing in English for scholars with limited English proficiency. This suggests that technology alone cannot create or sustain a multilingual scholarly publishing ecosystem. Hence, meaningful policies, in addition to improved MT tools and language resources, are needed to create a more linguistically diverse and equitable scholarly publishing landscape
Affective visual processing in depression and anxiety
No full textThe influence of visual mental imagery on emotion processing is well-established, and its
vividness has further been shown to vary by valence and diagnostic groups. While both
depression and anxiety are associated with dysfunctions in affective processing of visual imagery
and visual percepts separately, a direct comparison of internal and external visual processing has
not yet been undertaken. Moreover, while individual differences in imagery vividness have been
observed in isolated psychopathologies, the manner in which these differences manifest in
comorbid depression and anxiety is uncertain. The current study examined features of internal
and external affective visual processing in relation to depression, anxiety, and their comorbidity,
through an emotion appraisal task. In separate experimental blocks, participants were presented
with trials of affective pictures and imagery cues and were subsequently asked to rate the
emotional valence and clarity/vividness of each stimulus. Ratings were compared to participants’
scores on self-report measures of depression and anxiety. Further analyses assessed the utility of
continuous (dimensional) versus categorical (multidimensional) models of psychopathology.
Results revealed depression scores alone to be associated with reduced vividness ratings for
positive (but not negative or neutral) imagery. Further, depression was related to more negative
appraisals of valenced imagery but not pictures, and reduced clarity ratings for valenced pictures
but not neutral pictures. Results also support the utility of dimensional models of
psychopathology, with limited evidence to support strong categorization of psychopathological
features. Findings are discussed in relation to attention and reward processing, as well as
cognitive and neural resource engagement
Advancing low-carbon concrete: performance assessment and optimization of glass powder, biomass fly ash, and shredded rubber in concrete mixtures
No full textThe production of conventional concrete has a substantial negative impact on the environment, underscoring the need for effective strategies to lessen this impact. One promising approach is the partial replacement of cement and/or aggregates with waste materials, which enhances the sustainability of concrete. This method reduces the volume of waste sent to landfills while also conserving natural resources and lowering environmental risks. Among various waste materials, glass powder (GP) and biomass fly ash (BFA) have shown promise as partial cement replacements, while shredded rubber (SR) can be used as a substitute for fine and coarse aggregates. However, designing concrete with such materials poses challenges in achieving the required mechanical and durability performance standards. This study aims to develop optimal mix designs incorporating SR, BFA, and GP to meet environmental, durability, workability, and mechanical performance requirements. Durability was assessed using tests such as freeze–thaw resistance test, rapid chloride migration (RCMT), rapid chloride penetration (RCPT), and surface/bulk electrical resistivity. The Global Warming Potential (GWP) and predicted service life were also evaluated to assess environmental impacts. In addition, the mechanical behavior of the developed mixes was studied using compressive strength (CS), splitting tensile strength (STS), and modulus of rupture (MOR). Response Surface Methodology (RSM) was used to model and optimize the mix variables, followed by the development of a meta-model enhanced by Monte Carlo back analysis to improve prediction accuracy and identify the target mix design. Large-scale reinforced beams were cast to evaluate the structural performance of the optimized mixes. The results demonstrate that GP not only improves concrete properties but also mitigates the negative effects of BFA and SR. Overall, the optimized use of GP, BFA, and SR effectively reduces cement content and carbon emissions while satisfying structural, durability, environmental, workability, and mechanical criteria