Lakehead University Knowledge Commons

Knowledge Commons is an open access repository for scholarship and research produced at Lakehead University. It is a free and secure repository for LU faculty, students, staff, and researchers to preserve and present their scholarship.

Communities in KnowledgeCommons

Select a community to browse its collections.

Now showing 1 - 3 of 3

Recent Submissions

The geologic setting, kinematics and deformation mechanisms of the Eagle River gold deposit, Northern Ontario
(2026) Barkley, Ryan J.; Hollings, Pete
The Neoarchean Eagle River orogenic gold deposit in the Mishibishu greenstone belt of northern Ontario, Canada, was investigated through a multidisciplinary approach integrating field mapping, lithogeochemistry, isotope analysis, EBSD mapping, CVA analysis and geothermometry techniques. Near mine host rocks comprise two distinct suites: tholeiitic and calc-alkaline volcanic rocks. When normalized to primitive mantle values, the tholeiitic basalts and gabbros have negative Nb and Ti anomalies, near flat LREE (La/Smpm = 0.94-1.25) to weakly fractionated HREE patterns (Gd/Ybpm = 0.88-1.62) and εNd T(2700) values of +1.93 to +2.50, indicating little crustal contamination and formation within a primitive intra-oceanic plateau setting analogous to the Phanerozoic Ontong Java plateaus. The second suite (calc-alkaline) comprises intermediate and felsic samples, including diorites, andesites, granodiorites, and granites. The intermediate samples exhibit negative Nb and Ti anomalies, with moderate LREE patterns (La/Smpm = 1.29-5.82) and HREE fractionation (Gd/Ybpm = 0.70-4.28). The felsic samples have moderate LREE enrichment (La/Smpm = 1.29-5.82), HREE fractionation (Gd/Ybpm = 0.70-4.28), and εNd(2700 Ma) values of +1.53 to +2.56, suggesting evolution in a closed system through subduction-driven fractional crystallization, similar to the modern-day western Canadian Cordillera orogeny. The Eagle River deformation zone is a ~4 km-long, curvilinear, along-strike brittle–ductile shear zone characterized by oblique dip-slip deformation. It records two dominant kinematic regimes: a pure shear–dominated component associated with oblique crustal shortening, and a simple shear component reflecting dextral reverse transpression. Sheared quartz veins have been fully recrystallized and exhibit non-coaxial deformation with triclinic flow geometry. Gold mineralization preferentially occurs at vein selvages where fractured plagioclase networks provide a brittle contrast with dynamically recrystallized quartz veins and veinlets. Sheared quartz grains show evidence of grain boundary migration within the dislocation creep regime, with gold grains, sulphides, and other impurities concentrating at the quartz vein selvage. These findings support a tectonic model in which subduction-related, calc-alkaline rocks were emplaced on primitive oceanic plateau crust in an intra-oceanic island arc environment and underwent ductile deformation, with gold concentration facilitated by crystal plastic deformation, creating favorable structural traps and fluid pathway arrays. This research enhances our understanding of the formation and tectonic framework of this high-grade gold deposit, providing insights into exploration prospectivity within similar geological settings.
Experimental investigation on mechanical behavior and properties of cemented paste backfill under biaxial loading condition
(2026) Abi, Mohamed; Cui, Liang; Deng, Jian; Khalid, Muhammad
Cemented paste backfill (CPB) is widely used in underground mines such as Kidd Creek Mine (Ontario) and Red Lake Operations (Ontario) for tailings disposal and ground support. However, its mechanical response is commonly evaluated using uniaxial compression or axisymmetric triaxial tests, which do not fully represent the non-axisymmetric stress conditions acting on exposed backfill structures. This thesis experimentally investigates the mechanical behavior and properties of CPB under biaxial loading conditions, with emphasis on the effects of curing time, cement content, and intermediate principal stress σ2. A custom biaxial compression testing system was developed to independently apply the major principal stress σ1 and intermediate principal stress σ2, while maintaining the minor principal stress as σ3=0. A total of 81 biaxial compression tests were conducted on cubic CPB specimens prepared with cement contents of 2.25%, 4.5%, and 9.0%, and cured for 7, 28, and 90 days. Different σ2 levels were applied to evaluate the influence of biaxial confinement on stress-strain response, volumetric deformation, stiffness, normalized strength, p-q strength envelopes, crack initiation stress, crack damage stress, and failure patterns. The results show that curing time and cement content significantly increased stiffness and peak axial stress, reflecting progressive hydration and improved cementation. The elastic modulus increased from about 4 to 172 MPa. Increasing σ2 enhanced peak strength, reduced post-peak softening, delayed crack development, and shifted failure from brittle tensile-shear cracking toward more ductile shear-dominated deformation. Normalized strength increased with the intermediate principal stress parameter b, especially for weaker and early-age CPB. The p-q strength envelopes shifted upward and rightward with increasing cement content, curing time, and confinement, indicating pressure-dependent strength behavior. Overall, this study provides new experimental evidence for the biaxial mechanical response of CPB and offers useful parameters for constitutive modelling and stability assessment of exposed backfill structures.
Bioretention for fish habitat protection: treatment performance and spatial prioritization in a cold climate
(2026) Muir, Brant; Stewart, Robert; Rennie, Michael; Drake, Jennifer; Kolka, Randall; Khan, Usman
Urban stormwater and meltwater mobilize pollutants and transport them into urban streams, where they pose ecotoxicological risks to aquatic life. Bioretention systems (a.k.a. bioretention cells or rain gardens) are a form of green stormwater infrastructure (GSI; a.k.a. low impact development practice or LID) that retain and filter runoff, reducing volumes and improving water quality before it enters receiving watercourses. This dissertation evaluates the potential for bioretention systems to support urban fish habitat protection by reducing runoff volumes and improving water quality before discharging into urban streams. It also examines whether event-scale stormwater and meltwater treatment improvements are detectable through short-term downstream water quality monitoring and identifies where stormwater interventions should be prioritized to support the protection of sensitive fish habitats. A perspective chapter outlines an integrated approach to urban stream restoration that combines physical habitat improvements with green stormwater infrastructure practices, such as bioretention systems, within urban land use planning and renewal. The chapter emphasizes post-restoration monitoring, incorporating water quality guidelines into GSI performance evaluations, strategically locating restoration and stormwater interventions where they are most likely to support ecological protection, and increasing stormwater management on private property through public engagement. Field investigations evaluated three bioretention systems discharging into trout-sensitive urban tributaries in Thunder Bay. Water quality was monitored at all three systems, while water quantity was monitored only at Bioretention Systems 1 and 2 because site constraints at Bioretention System 3 prevented reliable inflow and outflow discharge measurements. During rainfall events, Bioretention Systems 1 and 2 fully retained runoff during 43 and 70 of 87 monitored events, respectively. When effluent occurred, suspended solids concentrations decreased by 51-64% across the three bioretention systems and turbidity was reduced at two of the three systems. These reductions in runoff volumes, turbidity, and suspended solids suggest a reduced potential for particulate pollutant delivery and fine sediment inputs into fish-bearing streams. Additional analyses examined pollutant accumulation in the winter snowpack and bioretention performance during the spring freshet. Roadside snowbanks contained significantly higher concentrations of chloride, suspended solids, and dissolved organic carbon than open field and bioretention sites. During spring melt, peak and total meltwater volumes were reduced at Bioretention Systems 1 and 2, where hydraulic monitoring was feasible, while water quality was evaluated across all three systems. Across the three systems, pH, turbidity, suspended solids, and dissolved organic carbon concentrations decreased in meltwater before discharging to receiving waters. A rapid assessment framework integrating stormwater impairment data and habitat surveys was developed to identify priority locations for green stormwater infrastructure. Applied to a trout-sensitive tributary in Thunder Bay, Ontario, this framework provides municipalities with a practical tool to prioritize stormwater interventions in locations where they are most likely to support the protection of sensitive fish habitats. This dissertation makes several novel contributions to stormwater management and fish habitat protection in a cold climate. First, it provides a critical perspectives-based synthesis that identifies why urban stream restoration, stormwater management, and land use planning can fail to protect urban streams when implemented independently. Rather than simply arguing that these practices should be integrated, this chapter clarifies specific management disconnects between these practices. It is argued that stream habitat restoration focusses on improving physical fish habitat, but does not adequately address impacts from untreated stormwater runoff, that GSI may reduce runoff quantity and improve runoff quality at the site level, without producing detectable ecological recovery, and that land use planning may miss opportunities to reduce future pollutant loading, protect sensitive areas, or support GSI implementation on private land. The contribution of this chapter is a critical synthesis that reframes urban stream revitalization as an integrated planning challenge rather than a separate set of stream restoration, stormwater and land use practices. Stream habitat restoration projects and green stormwater infrastructure (GSI) aim to protect urban streams, but are often implemented independently. This chapter provides a critical perspectives-based synthesis that reframes urban stream revitalization as an integrated planning challenge. It highlights how isolated approaches can limit ecological recovery and identifies strategies to coordinate habitat restoration, GSI performance evaluation, winter snow monitoring, stormwater controls on private land, and riparian protection in cold-climate urban watersheds. Recommendations include post-restoration monitoring, aligning restoration with local degradation, strategic placement of GSI and habitat improvements, and incorporating land-use planning and zoning to protect sensitive areas. These recommendations provide the conceptual framework for the field-based and applied chapters that follow. Second, it provides empirical evidence from rainfall and snowmelt events demonstrating that bioretention systems can substantially reduce runoff volumes and particulate-associated pollutants before discharging into trout-bearing waters. Third, it demonstrates that treatment performance differs between particulate and dissolved contaminants, with high reductions in turbidity and suspended solids concentrations, but limited or inconsistent reductions in chloride and nutrients, emphasizing the need to reduce pollutant sources at the source through changes in land use practices to complement bioretention treatment performance. Fourth, it identifies roadside snowpack as an important seasonal reservoir of sediment, chloride, and organic carbon, highlighting the influence of winter road maintenance, vehicular activity and spring freshet processes on cold climate stormwater quality. Lastly, it develops a spatial prioritization framework that combines stormwater impairment identification with downstream fish habitat sensitivity analysis to guide green stormwater infrastructure placement where the ecological benefit to fish habitats is most likely.
High-performance model predictive control methods for multilevel inverter-fed medium-voltage drive systems
(2026) Le, Hoang; Dekka, Apparao
This dissertation presents comprehensive research on the modeling, control, and implementation of advanced multilevel inverter (MLI) topologies and model predictive control (MPC) strategies for medium-voltage (MV) drive systems. The primary objective is to achieve superior current tracking performance, reduced switching frequency, and minimized common-mode voltage (CMV), while maintaining low computational complexity. The research addresses critical limitations in existing MLI topologies and MPC methods such as high component count, increased cost and size, model inaccuracy, high computational burden through the development of novel converter configurations and control methodologies. A new five-level (5L) inverter topology is first proposed, featuring a reduced number of components and the elimination of multiple isolated DC-sources. The topology utilizes only flying capacitors (FCs) and switches, thereby reducing control complexity compared to existing 5L-MLI. A finite-control-set-MPC (FCS-MPC) method is also developed to control the proposed 5L-MLI, and the performance of the inverter is experimentally validated under various operating scenarios. Results demonstrate that the proposed inverter has superior harmonic performance and low switching power losses while operating at low switching frequency in comparison to the existing 5L-MLIs. Besides converter configurations, control methods play a pivotal role in system performance. Existing FCS-MPC are modeled based-on the forward Euler’s integration method due to its ease of implementation but suffer from significant prediction errors at larger sampling periods. To tackle this issue, a Heun integration-based-FCS-MPC approach is proposed for MLIs. The proposed method incorporates correction stage along with prediction stage to improve the prediction accuracy, resulting in a substantial reduction in current tracking error and switching activity. Experimental results confirm the effectiveness of the proposed approach through enhanced prediction accuracy while operating at a low switching frequency. To further tackle CMV and computational challenges, improved sequential MPC (SMPC) strategies are proposed. The proposed low-complexity SMPC eliminates the reliance on weighting factors and offline switching vector preselection to reduce the CMV. In addition, an enhanced sampled-data SMPC is proposed to improve the discrete-time model precision, significantly reducing current distortion and FC voltage ripple. Experimental validation on an MLI prototype demonstrates their excellent current regulation, lower CMV, and improved performance compared to existing SMPCs. Finally, an SMPC strategy with cost function-free current control and CMV mitigation is proposed based on the low-complexity SMPC framework. By directly determining the optimal voltage level from the reference AC currents, the proposed method removes the need for cost function optimization in the current control stage, while maintaining low CMV and reducing computational complexity. Experimental and simulation results demonstrate effective current regulation, low harmonic distortion, reduced FC voltage ripple, and satisfactory motor drive performance, confirming the practical suitability of the proposed SMPC for high-performance MLI-fed MV drive systems.
Large-scale news headline quality analysis: clickbait trends, binary classification, and AI-generated content
(2026) McCutcheon, Austin; Brogly, Chris; Tan, Xing; Yang, Xingwei (Nancy)
Online news can be characterized by massive volumes of news content spanning a spectrum from high-quality professional journalism to low-quality articles. This thesis presents four empirical studies that employ methods to analyze, classify, and evaluate quality-varying news headlines at scale. The first two studies apply Interrupted Time Series (ITS) analysis to examine associations between clickbait prevalence and major events. Analysis of 451 million headlines from worldwide news websites (2016-2023) revealed statistically significant associations for three of five events, each showed slight pre-event decreases followed by sustained post-event increases in clickbait levels. A complementary analysis of 7.4 million headlines from Canadian news websites (2017-2023) found similar patterns. The third study benchmarks twelve machine learning and deep learning models for binary classification of perceived news quality on a balanced dataset of 57.5 million headlines labeled according to website-level expert consensus ratings. Results demonstrated that a CPU-based Bagging Classifier achieved 88.1% accuracy with stability across cross-validation folds, while a fine-tuned DistilBERT model achieved the highest accuracy at 90.3% but required substantially greater computational resources. The fourth study evaluates fourteen accessible Small Language Models (SLMs) for their willingness to generate fake news headlines when explicitly prompted and tests whether the trained classifiers from study three generalize to synthetic content. Minimal resistance to generating false news headlines was found, with models refusing requests less than 1% of the time. Both classifiers showed substantially reduced performance on AI-generated headlines (54-63% for DistilBERT, 35-48% for Bagging), with systematic misclassification of AI-generated “high-quality” content as “low-quality,” suggesting that human-trained classifiers do not generalize effectively to current AI-generated text. This thesis contributes the application of ITS methodology to clickbait analysis at web scale, comprehensive benchmarking of model architectures for large-scale headline quality classification, and empirical evidence that quality classifiers trained on human-authored content exhibit reduced performance when applied to SLM-generated headlines.