Theses

Permanent URI for this collectionhttps://uwspace.uwaterloo.ca/handle/10012/6

The theses in UWSpace are publicly accessible unless restricted due to publication or patent pending.

This collection includes a subset of theses submitted by graduates of the University of Waterloo as a partial requirement of a degree program at the Master's or PhD level. It includes all electronically submitted theses. (Electronic submission was optional from 1996 through 2006. Electronic submission became the default submission format in October 2006.)

This collection also includes a subset of UW theses that were scanned through the Theses Canada program. (The subset includes UW PhD theses from 1998 - 2002.)

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Individual Open-Ended Problem Solving and Creativity
(University of Waterloo, 2026-06-18) Doroshenko, Sofiia
Complex real-world problems are often ill-structured and open-ended, with no single correct solution and many possible ways to organize the available information. Despite the prevalence of such problems, most experimental research on problem solving has focused on well-defined tasks with predefined solutions, while studies of ill-structured problems have largely relied on qualitative observational methods. This thesis extends a controlled experimental framework for studying open-ended problem solving, originally developed and tested in a group context by Alattas (2023), to the level of the individual solver. Sixty participants each completed three categorization tasks in which they organized 16 randomly selected pictures into four categories of four pictures each. Task open-endedness was manipulated by varying the goal structure and participants' beliefs about the solution space across three conditions: an Expert condition, in which participants were told to find the single best solution as identified by a panel of experts; a Good condition, in which multiple acceptable solutions were described as available; and a Story condition, in which participants were asked to form narrative-based categories. All participants completed all three conditions with different stimulus sets, using a within-subjects design. Quantitative analyses examined five outcome domains: task difficulty, solution variability, path dependency, association strength, and search behavior. Open-endedness significantly increased solution variability and path dependency, reduced association strength, and led to more direct search paths with fewer direction reversals. However, the effect on task difficulty diverged from the group-level pattern: Expert condition produced the highest difficulty across behavioral measures, while Good and Story were comparable, rather than the graded Expert > Good > Story ordering observed in groups. Post-experiment interviews were analyzed for 30 participants using an inductive thematic approach. Three main themes emerged: interpreting the pictures before categorizing, strategies for building categories under constraint, and using narratives and creativity to reach a solution. These themes illuminate the processes behind the quantitative patterns, revealing how participants interpreted ambiguous stimuli, managed constraints, and sometimes used stories to connect the pictures across all three conditions. Together, the quantitative and qualitative findings show that the effects of open-endedness on solution variability, association strength, and search behavior observed by Alattas (2023) in groups extend to individual solvers, whereas the relationship between open-endedness and task difficulty shifts at the individual level. The study contributes an experimental method for studying individual open-ended problem solving, provides early evidence on how the shift from group to individual processing changes the relationship between open-endedness and difficulty, and raises questions about the relationship between open-endedness and creativity that invite further investigation.
Phases of matter in quantum information and error correction
(University of Waterloo, 2026-06-17) Negari, Amirreza
This thesis investigates phases of matter and phase transitions through the lens of quantum information, with an emphasis on phenomena not fully captured by conventional local observables or equilibrium order parameters. While the traditional framework of phase transitions relies on correlation functions and order parameters, entanglement and other information-theoretic quantities provide a broader language for characterizing both equilibrium and non-equilibrium many-body systems. A central perspective developed here is that such quantities furnish sharp diagnostics of phases and criticality, particularly in topological phases subjected to noise and measurement. First, we study how measurements on topological quantum states reshape entanglement structure and induce phase transitions. Focusing on the toric code, we show that measuring part of the system generates distinct entanglement phases in the remaining degrees of freedom, and that tuning the measurement protocol drives transitions between them. To analyze these phenomena, we develop analytical tools that track the entanglement structure of the post-measurement state and reveal a rich phase diagram. Next, we turn to topological codes in the presence of noise, where information-theoretic probes reveal forms of non-equilibrium criticality invisible to conventional observables. In this setting, we identify extended critical behavior in mixed states and show that conditional mutual information diagnoses transitions between distinct regimes of information retention and loss. Interpreted through quantum error correction, these transitions distinguish phases in which logical information is robustly preserved, only partially accessible, or completely lost. Building on this connection, we extend the mixed-state perspective from static codes to fault-tolerant dynamics by relating faulty syndrome-extraction circuits to the mixed-state structure of an associated higher-dimensional resource state. This leads to a decoder-independent diagnostic of fault tolerance based on the conditional mutual information of syndrome data across spacetime. The resulting spacetime Markov length diverges at the fault-tolerance threshold, providing an intrinsic information-theoretic characterization of the preservation and breakdown of logical information in noisy quantum circuits. Finally, we develop structural results for thermal and symmetry-constrained mixed states. We show that symmetry can obstruct the sudden death of entanglement in thermal states: for canonical ensembles and for Gibbs states subject to superselection rules, entanglement persists, and in broad settings remains nonzero at arbitrarily high temperatures. In fermionic systems, this identifies parity superselection as a generic mechanism protecting mixed-state entanglement and fermionic negativity. Complementing this perspective, we study extendibility as a tractable probe of entanglement structure in fermionic Gaussian states, showing that it admits an efficient characterization and provides practical criteria for mixed-state entanglement, including an extendibility transition in the disordered Kitaev chain. Taken together, these results support a unified picture in which information-theoretic quantities serve as fundamental diagnostics of phase transitions and criticality in both equilibrium and non-equilibrium quantum systems.
Chemical Looping Combustion with an Industrial Waste: Kinetic Modeling and Pilot-Scale Design using Red Mud
(University of Waterloo, 2026-06-17) Ronson, Dana
Chemical looping combustion (CLC) is an emerging carbon capture process that can produce a high-purity stream of CO2 without the energy-intensive separation that is associated with traditional carbon capture strategies. In the process, a solid metal oxygen carrier (OC) facilitates the splitting of the conventional combustion reaction into distinct oxidation and reduction subreactions such that the fuel and air atmospheres remain separate. CLC has yet to be implemented at industrial scale; hence, there is interest in further developing this emerging technology. One such area of development is the OC material, as the overall performance of a CLC system is crucially dependent on the performance of the OC. While synthetic OCs have been the dominant materials used for CLC development, they demand valuable materials. Thus, there has been a recent interest in utilizing lower-cost materials such as industrial wastes in CLC. The use of industrial waste OCs in CLC has gained recent attention as these materials demonstrate the potential to be a cost-effective alternative to synthetic OCs. A key limitation in the development of CLC with industrial waste OCs is the lack of modeling efforts on CLC systems with these materials. This work presents a dynamic multiscale packed bed reactor CLC model to investigate the performance of red mud, an industrial waste from the alumina refining industry, as an OC. Kinetics describing the oxidation reaction of red mud with oxygen as well as reduction reactions of red mud with CH4, CO, and H2 fuels were identified and validated using lab-scale experimental data. Sensitivity analyses were performed on kinetic parameters and reactor operating conditions, where the model exhibited reasonable predictions. The model developed in this work serves to advance the development of CLC by enabling simulation and model-based design methods for the packed bed reactor with a red mud OC. A proposed nominal pilot scale design exhibits moderate utilization of the red mud OC and high fuel conversion. By producing approximately 848.1 MJ of energy in a single cycle, this design demonstrates the potential for red mud to be an effective OC in large scale CLC. The red mud pilot-scale design was compared to a similar system from the literature that used a synthetic OC, and it was found that the red mud system produced less heat as a result of its low density leading to a smaller solids inventory. Nevertheless, red mud boasts lower material costs than traditional synthetic OCs. An economic optimization of the pilot scale design for separate reduction and oxidation stages revealed that it is crucial to consider the integration of both stages to determine an optimal design for a complete cycle of the CLC system (i.e., jointly considering how the performance of reduction impacts the economics of oxidation).
Order in the Open: Symmetries and Entanglement of Many-Body Mixed States
(University of Waterloo, 2026-06-17) Almeida Lessa, Leonardo
Real-world quantum systems are open and interact with their environments, requiring a statistical description via mixed states. This thesis investigates the interplay between global symmetries and quantum entanglement in open many-body systems, asking whether symmetries can robustly enforce long-range entanglement and correlation patterns, even under severe decoherence or high temperatures. In the first half, we extend quantum anomalies to mixed states and establish the anomaly-nonseparability correspondence: mixed states that are strongly symmetric --- where every state in the statistical ensemble possesses the same symmetry charge --- exhibit long-range multipartite entanglement. We show that the unique multipartite structure of this anomalous entanglement gives rise to entirely new phases of matter that are intrinsically mixed, i.e., lacking any pure state representative. Conversely, we demonstrate that strong-weak mixed anomalies, such as Lieb-Schultz-Mattis anomalies, imply long-range correlations without strictly requiring quantum entanglement. Broadening this correspondence to higher-form symmetries, we introduce a definition of mixed-state phases of matter that is insensitive to long-range classical correlations, thereby only capturing distinct patterns of long-range entanglement. We argue that strong symmetries and their anomalies are the defining features of such phases. In the second half, we shift focus to non-anomalous symmetries and show when they alone suffice to enforce entanglement. We investigate maximally mixed states invariant under on-site symmetries, which naturally emerge as steady states of generic quantum evolutions that preserve these symmetries strongly. We exactly calculate the values of several entanglement measures that are notoriously difficult to tackle analytically or numerically, such as the entanglement of formation and distillation. For continuous non-Abelian symmetries, we find high amounts of long-range entanglement, despite the states being maximally mixed within the symmetric subspace. Finally, we prove that the same strong symmetry conditions and superselection rules prevent the sudden death of entanglement at finite temperatures, even for Abelian symmetries. This explains previously observed behavior in canonical ensembles with Ising symmetry and in fermionic systems.
Manu with a Ball: Water Entry of Two Tandem Spheres
(University of Waterloo, 2026-06-16) Chan, Michelle
A popular diving maneuver known as the “manu bomb” has long been a hallmark of recreational water activities in New Zealand. This cannonball-like dive generates a large splash and produces a pronounced air cavity beneath the water surface. As the cavity collapses, it generates a loud noise and focuses the surrounding fluid into a vertex where a vertical jet, known as the Worthington jet, is formed. If a diver performs the maneuver while holding a ball (e.g., a football), the ball is propelled upward by the Worthington jet, which we refer to as the manu with a ball or “manu ball” for short. As interesting as this dive with a ball is to witness, there are no existing studies on this phenomenon yet. In this work, we study the mechanism of the manu ball and provide a theoretical framework for maximizing the height, and thus the “fun”, of launching the ball. We model the manu ball as the tandem water entry of two spheres: the bottom sphere representing the diver, and the top sphere representing the ball. Our theoretical model quantifies the rebound of the top sphere as a momentum transfer ratio, comparing the initial and final momentum of the top ball over the initial and final momentum of the bottom ball. This momentum transfer ratio is a function of the dimensionless h1 number, a number representing the distance from the top ball to the pinch-off point normalized by the size of the bottom ball, which can physically be interpreted as the spacing between the top and bottom ball at water entry. This momentum transfer ratio is also parameterized by key factors such as the mass ratio between the top and bottom balls and jet strength. Our model was then validated by experiments, where the two spheres were positioned at a set initial separation and released with prescribed time delays. The process of water entry and rebound of the balls was recorded using a high-speed camera. The bottom ball was varied across four sizes and a range of weights to achieve different types of water entry-induced cavities, including both quasi-static and deep seal. Our experimentally validated framework provides a quantitative basis for understand- ing and optimizing the manu ball. By modeling the system as a two-sphere water-entry problem and identifying the governing non-dimensional parameters, we capture the essen- tial physics of jet formation and jet-ball coupling. The resulting scaling laws enable the prediction and enhancement of the top ball’s rebound, and establish a foundation for fu- ture investigations of recreational water-entry phenomena and related jet-driven propulsion mechanisms.
Exploring opportunities to enhance social service access among LGBTQ+ refugee claimants in Waterloo Region, Ontario
(University of Waterloo, 2026-06-16) Berisha, Zana
Background: The number of refugee claimants in Canada is increasing. These individuals have applied for refugee status but have not yet received a decision from Immigration, Refugees and Citizenship Canada [IRCC]. Due to their lack of official status, they encounter significant barriers when accessing Canadian social welfare systems. LGBTQ+ refugee claimants experience additional marginalization. Limited linking social capital, defined as restricted connectivity to formal support structures, represents a key barrier. In response to these challenges and the lack of current research on LGBTQ+ refugee claimants' access to social services, this study seeks to examine: (1) how LGBTQ+ refugee claimants navigate settlement, legal, employment, and health services in Waterloo Region, Ontario; and (2) which strategies may mitigate barriers to social support and strengthen linking social capital for LGBTQ+ claimants in this region. Methods: A qualitative research design was used, employing snowball sampling to recruit (n=8) refugee claimants. Semi-structured interviews were conducted to examine how claimants navigate social welfare systems and to assess their need for formal social support. The research was grounded in narrative inquiry to capture participants' experiences. Thematic analysis of the transcribed data was performed using an inductive-deductive approach. Results: Participants faced barriers in accessing and navigating social services. Social identity stressors, such as racism, LGBTQ+ vulnerability, and stigma, impeded service engagement. Institutional challenges included limited information, delayed responses, language barriers, and financial instability. As a result, claimants often self-advocated and relied on informal peer networks. Most participants indicated a strong preference for more robust connections to formal support systems. The study identified five primary strategies to mitigate barriers to social support: (1) utilizing professional referrals as a legitimizing mechanism; (2) positioning caseworkers as trusted navigators; (3) ensuring social support systems acknowledge individuals’ identities to reduce stigma and related barriers; (4) fostering trust through consistent professional relationships to address previous exclusion; and (5) implementing proactive social support to minimize wait times and provide timely responses to institutional delays. Contribution: The study was conducted during a period of significant social change, including the introduction of Bill C-2 and Bill C-12, stricter immigration policies, and unsafe environments for LGBTQ+ individuals in Waterloo Region. It underscores the urgent need for communities to take concrete action in creating solutions that protect the well-being of refugee claimants. By centring LGBTQ+ perspectives, this study fills a critical gap in social service research and supports the development of more inclusive and effective services. The findings urge social service providers to champion proactive efforts to advance inclusion and health equity for LGBTQ+ refugee claimants.
Categorical 't Hooft Expansion and Twisted Holography
(University of Waterloo, 2026-06-15) Lopez Raven, Adrian Khalil
This thesis studies ideas of Holography and 't Hooft expansions in the context of Twisted Holography. The 1st part introduces a novel entry in the Twisted Holography dictionary, associating to certain boundary operators, bulk instantonic deformations of D1-D5 brane systems in SL(2,C). From the boundary operators, we are able to extract the data of both the shape and Chan-Paton bundle of the dual brane, encoding it in a derived coherent sheaf. We then apply this construction to chiral algebras with SO and Sp gauge groups, obtaining branes with Z2 identifications consistent with conjectures relating these chiral algebras to orientifolds of the bulk B-model theory. The second part, extends the conjecture of Twisted Holography to a wide family of chiral algebras. In particular, we study boundary theories containing several βγ-systems with several U(N) gauge groups. Amongst these one has known chiral algebras arising from the twist of quiver-gauge theories, but also new chiral algebras whose dual B-model lives in non-commutative backgrounds. Using techniques from String Field Theory and Homological Algebra, we extract from these chiral algebras, algebraic properties of the conjectural dual worldsheet theories, and track how they deform under backreaction.
Representing Sexual Violence and Sexual Violence on Campus: Institutional Constructions, Student and Staff Perceptions, and Their Effects
(University of Waterloo, 2026-06-15) Goodall, Jade
Universities have increasingly been positioned as key sites of sexual violence prevention and response, yet little attention has been paid to how they construct and represent sexual violence through the institutional texts they produce. This study examines how sexual violence and sexual violence prevention are represented within university polices and prevention materials, and how these representations are perceived and understood by students and staff. This qualitative study draws on a textual analysis of 130 institutional documents and semi-structured interviews with 10 students and staff at a Southwestern Ontario university (referred to as Z University). Guided by Bacchi’s (2009) What’s the Problem Represented to Be? approach, and drawing on theoretical insights from Dorothy Smith (2005) and Patirica Hill Collins (2019), the analysis examines how sexual violence is represented, the assumptions that underpin these representations, what is left unspoken, and how these representations are taken up in practice. The findings demonstrate that sexual violence is predominately framed as a matter of legal compliance, public health education, and individual responsibility. Participants describe tensions between institutional representations and lived experience, particularly among those who feel excluded or misrepresented within dominant framings. Rather than producing generalizable claims, this study offers a critical, context-specific analysis of how sexual violence and sexual violence prevention are constructed within institutional settings and how these constructions are perceived and negotiated by students and staff.
On Initializations for NMF
(University of Waterloo, 2026-06-15) Shi, Sammy
In Ward and Kolda (2023) and Xu et al. (2024), the authors proposed a sketching based initialization for unconstrained two block matrix factorization (MF) with provable guarantee. The purpose of this thesis is to examine the limits of extending these two proof frameworks in the context of Non-negative Matrix Factorization (NMF), as well as its numerical implications. The first chapter deals with fundamentals of NMF: its formulation, the identifiability issue and guarantees, a survey of iterative methods to solve it, and finally some complexity results. In the second chapter, I will quickly go over spectral initialization techniques for matrix optimization problems, and introduce sketching, a family of randomization techniques for numerical linear algebra, with a particular focus on its uses in iterative methods. The core focus of this chapter lies at the intersection of these two topics: a sketching-based initialization for the unconstrained two-block MF problem, using either non-alternating or alternating gradient descent (GD). We will go over the proof frameworks. In the third chapter, I will present my attempts to generalize the proof frameworks to NMF and the conclusions based on the partial progress. The fourth chapter deals with numerics. We will compare the performance of different base methods in different data regimes using all of the initializations mentioned in this thesis.
Recalibrating Reality: Sensory Reweighting and Cybersickness Susceptibility in Virtual Reality
(University of Waterloo, 2026-06-15) Izadi Sokhtabandani, Siyavash
This dissertation investigates how the brain dynamically reweights sensory cues to resolve multisensory conflicts in virtual reality (VR), with a specific focus on the etiology of cybersickness. The research characterises how visual, vestibular, and proprioceptive cues are integrated and recalibrated following VR gameplay while accounting for individual differences in these processes which dictate susceptibility to sickness. Across three experiments, this work challenges the assumption that VR exposure triggers a uniform sensory shift. Experiment 1 utilised the Subjective Visual Vertical (SVV) task, finding that high-intensity exposure shifted participants' perceived upright toward gravitational vertical and away from the body axis. Crucially, individuals who demonstrated greater reweighting reported lower cybersickness, suggesting that rapid sensory adaptation acts as a protective mechanism. Experiment 2 employed the Oriented CHAracter Recognition Test (OCHART) to further tease apart the relative weighting of visual and gravitational cues. While VR exposure did not produce a uniform group-level shift in the Perceptual Upright (PU), exploratory analyses revealed that increased visual weighting post-exposure was associated with higher cybersickness, indicating that a failure to down-weight unreliable visual inputs may be maladaptive. Experiment 3 attempted to manipulate these weights by degrading vestibular reliability through stochastic electrical vestibular stimulation (EVS). Contrary to the hypothesis that reducing vestibular certainty would force a beneficial reweighting, EVS exacerbated cybersickness and increased attrition, while cue-weighting models remained unstable. Altogether, this work demonstrates that cybersickness is not merely a product of sensory conflict, but a failure of the central nervous system to successfully reweight unreliable cues. The results suggest a two-part interpretation: first, that individual differences in sensory plasticity may relate to tolerance, where greater post-VR shifts toward gravitational cues were associated with lower symptom severity in Experiment 1, though this relationship was not consistent across tasks and measures. Second, the results suggest that external disruption of vestibular signals (via EVS) may hinder rather than help adaptation. These findings provide preliminary evidence for a reweighting account of individual differences in cybersickness susceptibility and point toward personalised exposure protocols as a candidate intervention, pending replication with larger and more diverse samples.
Intersectional Incivility in Aviation: Socio-Spatial Relation, Constrained Agency, and Safety Reporting
(University of Waterloo, 2026-06-12) Ram, Angeline
Background: In Canadian air transportation organizations, employee safety reporting programs (ESRPs) are used as formal channels for all workers, including aircraft maintenance engineers and pilots, to raise occupational health and safety and aviation safety management system concerns. However, reportable issues are narrowly defined, so workplace incivility falls outside of sector safety reporting criteria. Although participation in ESRPs is framed as a moral duty within non-punitive, policy-driven safety cultures, policies do not necessarily create environments where workers feel safe to speak up. Instead, workers navigate these environments through constrained agency, intentionally remaining silent. In many cases, workers prioritize coping strategies that support their wellbeing over participation in formal reporting systems. From a labor geography perspective, this gap reflects how socio-spatial relations, shaped by culture, hierarchy, and colonial, imperial, and patriarchal legacies, normalize incivility. Though the Canadian air transportation sector has largely treated workers as a homogeneous group, further investigation is necessary to understand how socio-spatial relations, intersectional identities, and constrained agency shape workplace experiences, wellbeing, and participation in safety reporting. Objectives: Most sector literature examines gender-based incivilities experienced by women pilots through a homogeneous lens, assuming identical experiences regardless of race, occupation, immigration status, or sexual orientation. Workers’ experiences shaped by intersectional identities (race, gender, occupation, occupational status, immigration status, sexual orientation) remain under-examined. Situated within feminist epistemologies, this research asks: How do the lived experiences of air transportation workers in Ontario shape their participation in Employee Safety Reporting (ESR)? Objectives are: 1) explore how occupational identities shape air transportation workers' experiences in the workplace; 2) explore how intersectional identities shape air transportation workers' experiences in the workplace; and 3) investigate how identity-based incivility shapes ESR participation. Methodology: This exploratory qualitative research draws on labor and feminist geographies and Black intersectionality theory to expose power relations and agency. I conducted in-depth, semi-structured interviews with pilots and aircraft maintenance engineers of diverse statuses and identities. Interviews were video- and audio-recorded, transcribed verbatim, and analyzed in NVivo. Analysis used Hollinda et al.’s (2023) blended methods (summative content analysis + thematic analysis) and draws on Nash (2018) to use intersectionality as a methodological tool to generate inter-categorical profiles. Findings and Discussion: Three findings emerged: 1) occupational hierarchies shape incivility and wellbeing; 2) socio-spatial relations through incivility target intersectional identities, and shape wellbeing; and 3) incivility constrains agency, leading to coping over reporting. Workers in the same occupation are not monoliths: interlocking identities shape who is targeted, and incivility shapes how wellbeing is experienced. AMEs reported more identity-based incivility than pilots, and wellbeing impacts increased as occupational status decreased, reflecting power geometries that normalize disrespect toward subordinates. Incivility influenced wellbeing through six connected subthemes: stress and anxiety, frustration and powerlessness, exclusion, obsessing about interactions, self-doubt, and adverse effects on home life. Rather than reporting iv through ESRPs, workers, especially in lower-status roles, used constrained agency to protect wellbeing through overlapping coping strategies of adaptation, tolerance, and withdrawal. These strategies reflect a transaction in which employment security or advancement can outweigh the perceived benefits of reporting, challenging assumptions that policy requirements alone ensure participation. Conclusion: Socio-spatial relations among AMEs and pilots are shaped by hierarchical histories and colonial and patriarchal cultures that normalize identity-based incivility. When workers are targeted because of their intersectional identities, their already constrained agency becomes further limited, and they cope in ways that support their wellbeing rather than participate in safety reporting. Organizations need to integrate psychological safety into Safety Management Systems (SMS) as a foundational aspect of safety across teams and daily operations, and the sector should view workers through an intersectional lens, as occupational status and intersecting identities shape both exposure to incivility and the capacity to raise concerns. Policymakers must address the gap in which normalized incivility continues to cause distress and deter reporting. Recommendations include revising SMS and safety culture requirements to encompass employee wellbeing; training leaders and crews to recognize and address subtle incivility; and linking occupational health reports with safety data to ensure accountability, follow-up, and ongoing evaluation.
Internal conflict within Asian security arrangements
(University of Waterloo, 2026-06-12) Benjamin, Jacob
This dissertation examines a puzzle: allies and interoperable security partners that fight each other. The dissertation gathers and generates data on this confusing state of affairs and explains the factors that can cause this outcome. The dissertation consists of three papers. The first paper devises a new formula to measure the amount of internal conflict in a particular arrangement. I use this method to measure the amount of conflict in over thirty different security arrangements. The data flag anomalous arrangements, which are those alliances and interoperable security partnerships with several members that fight each other. The second paper is a case study on the Shanghai Cooperation Organisation (SCO). The SCO is a salient arrangement because five of the ten SCO members have fought another SCO member in the short span of five years. The third paper broadens the scope of this research to the Association of Southeast Asian Nations (ASEAN). While not an interoperable security partnership, ASEAN is a pertinent case study because it has claimed to be a security community; yet some of its members have fought each other in limited wars, and many members have serious contestations with other members on security issues. The findings of this research have both practical and theoretical significance. During the research design phase, I initially did not consider democratic peace theory as relevant to the dissertation’s topic; however, the findings ended up showing strong support for the significance of regime type in international relations. When there is internal conflict in security arrangements, often it is because of divergent regime types (democratic versus authoritarian regimes). Moreover, the fact that there is so much conflict within the SCO – an authoritarian security arrangement – reinforces the notion that authoritarian states are qualitatively more aggressive than democratic ones. That is, beyond waging conflict on their adversaries, authoritarian states are far more likely to wage conflicts on their so-called friends. Finally, since ASEAN has such a variety of regime types, it became clear why the association has struggled to develop deeper security commitments.
Aggregating and evaluating ambiguity in decision models
(University of Waterloo, 2026-06-12) Van Oosten, Zachary
This thesis develops new decision models under ambiguity that accommodate arbitrary reductions in the absence of ambiguity, that is, models not restricted to expected utility (EU) under pure risk (no ambiguity). A central challenge is the identifiability problem: from preferences alone, one cannot distinguish which features of the representation functional reflect the decision maker's evaluation of pure risk from those that reflect their reaction to ambiguity. To resolve this, we exogenously specify a family of unambiguous events and employ the property of partial law invariance: the DM is indifferent between unambiguous acts with the same distribution. The resulting models developed across the four chapters outlined below are relevant to decision theory, quantitative risk management, mathematical finance, and operations research. Chapter 2 studies partial law invariance in the context of risk measures. We fully characterize partially law-invariant coherent risk measures via a novel representation formula and extend the classical Kusuoka representation. Additionally, we propose new risk measures, including partially law-invariant versions of Expected Shortfall and entropic risk measures, along with tractable formulas for their calculation. Chapter 3 axiomatizes the Choquet rank-dependent utility (CRDU) model, which cleanly separates pure risk from ambiguity and reduces to rank-dependent utility in the absence of ambiguity. We show that the coupling of ambiguity perception and ambiguity attitude can be fully characterized by the matching probability, and that the supermodularity of this matching probability gives CRDU a distributionally robust interpretation. Chapter 4 distinguishes two conceptual frameworks for processing ambiguity: evaluate-then-aggregate (ETA), which first evaluates an act under each plausible model and then aggregates, and aggregate-then-evaluate (ATE), which first reduces ambiguity to a single representative distribution before evaluation. As most existing ambiguity models fall within the ETA framework, we develop and axiomatize the Choquet ATE model that generalizes both Choquet expected utility and CRDU while accommodating arbitrary pure-risk evaluations. Afterward, we provide a rich analysis of the interplay between ambiguity attitudes and risk attitudes. Chapter 5 develops a distributionally robust optimization model whose ambiguity set is derived from a Bayesian second-order belief, providing a clear separation between pure risk, ambiguity perception, and ambiguity attitude. This chapter is motivated by the observation that the smooth ambiguity model does not satisfactorily generalize to arbitrary pure-risk evaluations. A canonical construction based on distorted second-order beliefs is introduced as a tractable instance of this model, with accompanying algorithms and numerical illustrations in the context of portfolio optimization.
Aluminum-Air Batteries Across Scales: A Multiscale Framework for Electrochemical Characterization, Materials Optimization, and Electric Vehicle Integration
(University of Waterloo, 2026-06-10) Shabeer, Yasmin
Aluminum-air (Al-air) batteries have emerged as a promising energy storage technology due to their exceptionally high theoretical energy density, material abundance, and potential for low-cost deployment. However, their practical implementation remains constrained by challenges related to electrochemical performance, parasitic corrosion, electrolyte management, and system-level integration. This thesis presents a comprehensive multiscale investigation of Al-air batteries, integrating techno-economic analysis, experimental characterization, data-driven modeling, and system-level simulation to evaluate their viability as advanced energy storage systems and range extenders in electric vehicles (EVs). The study begins with a techno-economic assessment of metal-air batteries in EV applications. A comparative framework is developed to evaluate the performance of Al-air systems relative to conventional lithium-ion batteries, incorporating key metrics such as gravimetric energy density, vehicle energy consumption, and cost. The analysis shows that Al-air batteries, with practical energy densities of approximately 700-900 Wh kg⁻¹, significantly outperform Li-ion systems (150-250 Wh kg⁻¹), offering strong potential for range extension. Simulated vehicle scenarios indicate that Al-air integration can extend driving range by a factor of 2-5, depending on system configuration and operating conditions. However, these benefits are offset by trade-offs related to system complexity, auxiliary components, and cost, highlighting the need for integrated evaluation frameworks. Experimental investigations are conducted to examine the electrochemical performance of Al-air batteries under varying electrolyte compositions and operating conditions. Using a novel galvanic generator-type Al-air system with a rotating electrode configuration, multiple prototype units provided by AlumaPower were evaluated. The rotating electrode design enhances mass transport, reduces passivation, and promotes uniform anodic dissolution, enabling improved discharge stability compared to conventional static systems. Systematic experiments reveal the alkaline electrolytes, particularly in the range of 6-8 M concentration, provide optimal performance by balancing ionic conductivity and electrochemical kinetics. Peak power densities exceeding 500 mW cm⁻² are achieved under controlled conditions, while discharge tests at moderate current densities (~80-100 mA cm⁻²) exhibit stable voltage profiles in the range of 1.0-1.2 V. The results further demonstrate that increasing electrolyte concentration beyond optimal levels accelerates parasitic corrosion and hydrogen evolution, leading to reduced efficiency and highlighting the importance of electrolyte optimization. To address the critical challenge of aluminum corrosion, a data-driven predictive modeling framework is developed. Artificial neural networks (ANNs) are trained on experimental datasets to model the relationship between electrolyte composition, temperature, and electrochemical variables with corrosion metrics such as corrosion potential (Ecorr) and corrosion current density (Icorr). The ANN models achieve high predictive accuracy, with coefficient of determination (R²) values exceeding 0.99, demonstrating their capability to capture complex nonlinear relationships in electrochemical systems. To further enhance system performance, genetic algorithms (GA) and multi-objective optimization (NSGA-II) are integrated with the ANN framework to identify optimal operating conditions. The optimization results reveal trade-offs between maximizing Ecorr and minimizing Icorr, enabling the identification of optimal electrolyte conditions that balance performance and degradation. This integrated modeling approach represents a significant advancement over conventional empirical methods by enabling predictive and systematic optimization of corrosion behavior. At the system level, the thesis develops a comprehensive modeling framework for integrating Al-air batteries within EV architectures. Using MATLAB and Simulink, a dual-energy storage system is implemented in which Al-air batteries function as range extenders for lithium-ion battery packs. The system incorporates experimentally informed battery models and employs state-of-charge (SOC)-based control strategies to manage power flow between energy sources. Simulations conducted under standard driving cycles, including UDDS, WLTP, and HWFET, demonstrate that Al-air integration can significantly mitigate SOC depletion and extend vehicle range, particularly in reduced-capacity Li-ion configurations (e.g., 50% and 35% baseline energy). The results highlight the importance of control strategy design, power limitations, and system configuration in achieving optimal performance. Collectively, the findings of this thesis establish a comprehensive framework linking electrochemical behavior, corrosion kinetics, and system-level performance of Al-air batteries. The integration of experimental characterization, data-driven modeling, and vehicle-level simulation provides new insights into the practical feasibility of Al-air systems and identifies key design and operational parameters governing their performance. The use of industrially relevant prototype systems further enhances the applicability of the research and bridges the gap between laboratory studies and real-world implementation. This work demonstrates that Al-air batteries, supported by optimized electrolyte conditions, predictive corrosion modeling, and intelligent system integration, represent a viable pathway for next-generation energy storage and EV range extension, while advancing both scientific understanding and practical development.
Autonomous Driving System Rule Learning Using Expert-Defined Causality
(University of Waterloo, 2026-06-10) Bouchard, Frédéric
An increasing number of road users are travelling freely in urban environments. Each of them has their own motion preferences but is expected to comply with the traffic laws. To cope with the motion discrepancies, autonomous vehicles require highly sophisticated reactive decision-making that can adapt their motion given the surrounding environment and the applicable traffic laws. Such decision-makers must be trustworthy, since each mistake can lead to a fatality, and performant, since they must estimate, at a high frequency, which behaviour to implement. This thesis describes how such functionality can be achieved with a practical rule engine learned from expert driving decisions and a precise notion of requirements. We first demonstrate the feasibility of planning the motion of an autonomous vehicle by implementing a prototype that, given a curated training suite of driving examples, can create and maintain a two-layer rule-based theory. Assuming perfect perception, we then design a method that learns the rules based on a precise notion of requirements. An expert anticipates that the decision-maker can enter a state for which a requirement is unmet and therefore specifies with a set of template rules the cause of each anticipated violation. For each template rule, its antecedent entails a notion of causality, and its consequent specifies the behaviour to implement. The set of template rules are used as a labelling function. Namely, each time the decision-maker fails to satisfy a requirement, an associated template rule is used to address the misbehaviour. The rules of the rule-based theory are based on templates. The antecedent of such rules are automatically learned and may have been significantly altered to include new relevant constraints that are expected to cope better with the requirements. Finally, considering that autonomous vehicles rely on sensor capabilities, we thereafter extend our method to compete in the Carla Leaderboard operational design domain. Using the same computer vision as the best performer for which there is code available, we demonstrate that our system can learn a policy that is explainable while performing better than our competitor on the set of provided requirements. This thesis has been divided into three phases, each of which strongly correlates with a paper submitted to a conference or journal for publication. In the first phase, we assess the feasibility of the proposed rule-based architecture by implementing/deploying a rule engine prototype in a level-3 autonomous vehicle driving for 110 kilometres of field tests in an urban environment of the city of Waterloo. Namely, the prototype has an algorithm to create and iteratively refine a rule-based behaviour planner, using a two-layer rule-based theory. The first layer determines a set of feasible parametrized behaviours, given the perceived state of the environment. From these, a resolution function chooses the most conservative high-level maneuver. The second layer then reconciles the parameters into a single behaviour. Based on the set of traffic rules described in a driver handbook, an expert produces a set of training examples expressing the relevant change of behaviours. The algorithm presented in that paper performs hierarchical rule-based machine learning. In the second phase, we formalize the construction of the training suite of driving examples that inevitably comes with the iterative development of the autonomous driving technology infrastructure of software and hardware. Namely, we explore how to extract knowledge from counterexamples encountered while driving in a city generated by the CARLA simulator. For that, we convert the requirements of the CARLA Autonomous Driving Leaderboard into a specification that is used to learn a rule-based policy. We assess the generalization of the learned rule-based policy by evaluating its performance on an unseen city generated by the same simulator. We then compare our performance with InterFuser, a state-of-the-art competing approach, and demonstrate that our method outperforms their method. In the third phase, we use the computer vision and tracker of InterFuser and create our own path generator inspired by the route planner of TransFuser to demonstrate that our method can cope with sensor noise while achieving state-of-the-art performance. In this phase, we use the six official towns that form the CARLA Autonomous Driving Leaderboard as the training towns and attempt to generalize to two unseen towns. Although our initial goal was to become an entry on the CARLA Autonomous Driving Leaderboard, the evaluation infrastructure has become unavailable. Therefore, to be convincing that our approach achieves state-of-the-art performance, we create our own challenge by randomly generating novel routes both on the six official towns and two additional unseen towns that have been released by the same officials. Although we demonstrate that our method outperforms a state-of-the-art end-to-end approach, we list in Limitations a number of issues that have not yet been addressed and constitute limitations to the results presented in this thesis. Thereafter, we speculate on how our method can be extended to mitigate some of these limitations.
Exploring Structure, Agency and Equity in Cross-Sector Partnerships for Advancing Sustainability and Climate Goals
(University of Waterloo, 2026-06-10) Samuel, Naima
The Sustainable Development Goals (SDGs) position partnerships as a central mechanism for advancing sustainability objectives by enabling coordinated efforts across multiple actors and sectors, particularly in addressing complex challenges like climate change. Despite the prominence of partnerships, there remains limited understanding of how cross-sector partnerships function in practice, particularly in local contexts where implementation occurs across municipal, community, and private-sector actors. Existing research has often emphasized formal structures, early phases of collaboration, or normative commitments, providing relatively limited insight into how partnerships are enacted during implementation, how they deliver outcomes, and how equity is embedded and sustained over time. Organized as a three-paper thesis, this dissertation combines a systematic review of sustainability partnerships situated within the SDGs with a comparative qualitative analysis of twelve Canadian local climate action partnerships to examine how cross-sector partnerships are structured, enacted, and adapted, and how effectiveness and equity emerge through the interaction of partnership structures and partner agency. Drawing on document analysis and semi-structured interviews, the analysis is informed by structuration theory, which provides a lens for examining how structures enable and constrain action and how partners reproduce or adapt these arrangements through practice. The findings show that the effectiveness of cross-sector partnerships in local climate action depends on more than formal design alone. Outcomes are shaped through the interaction of partnership structures and partner agency, as structural arrangements influence coordination, participation, and resource allocation while partners interpret, enact, and adapt these arrangements over time. Equity is similarly shaped through these dynamics, not through representational diversity or stated commitments alone, but through deliberate adjustments to decision-making, engagement, and resourcing structures. Co-design emerges as a central practice through which partners collectively reshape partnership arrangements and sustain equity over time. The dissertation contributes an integrated understanding of how cross-sector partnerships support effective and equitable action toward sustainability goals, using local climate mitigation as a site of implementation within the broader sustainability agenda. It extends structuration theory by showing how structure–agency dynamics are enacted through collective practice in multi-actor implementation contexts, highlighting the role of co-design, the influence of partnership arrangements and lifecycle dynamics, and the importance of aligning structures and agency to support both effectiveness and equity. It also offers practical insights for understanding, designing, and adapting partnerships to better support coordinated, inclusive, and effective local climate action.
Effect of Construction Contaminants on the Bond-Slip Behaviour of GFRP Reinforcing Bars
(University of Waterloo, 2026-06-10) Deng, Quanxiang
Glass fibre-reinforced polymer (GFRP) reinforcing bars are an attractive alternative to conventional steel bars in reinforced concrete (RC) bridge construction due to their non-corrosive properties. With advances in production and quality control, GFRP reinforcing bars are an economical alternative for steel reinforcement in many bridge components, particularly in the substructure and at joints. However, gaps remain in the design and construction of GFRP reinforced concrete. including the impact of surface contamination on GFRP reinforcing bars. During construction, construction activities are frequently carried out in close vicinity to exposed GFRP reinforcing bars, which can damage and contaminate their surface. Existing standards, such as CSA S807 and CSA S806, do not provide guidance on how contamination affects performance or how to treat contaminated GFRP reinforcing bars. In Ontario, exposed GFRP reinforcement contaminated by concrete splatter is required to be replaced, leading to costly delays and waste. This study evaluates the impact of surface contamination on GFRP bond behaviour using pullout specimens. 13M and 20M ribbed GFRP bars, and 12M and 20M sand-coated GFRP bars were tested with surface contamination from two common materials used in concrete placement: form oil and concrete splatter. Additionally, non-destructive inspection methods are used to investigate potential differences in ultrasonic pulse velocities associated with different surface contaminants and corresponding bond strength outcomes, and to establish the potential correlation between the contamination effects identified in the pullout and tests those obtained from the non-destructive testing measurements. The results demonstrated that the form oil contamination reduced bond strength and UPV considerably. This suggests that UPV is an effective method for predicting bond loss caused by the form oil contamination. Nevertheless, the concrete splatter contamination exhibited no clear correlations between the pullout test and the Ultrasonic test. Therefore, preventive measures should be applied for the form oil contamination from GFRP reinforcement, and immediate removal is required if detected. Concrete splatter contamination should be removed as a precautionary measure. Furthermore, comparison to the test data showed that the mBPE model yielded a slightly conservative estimate of experimental bond behaviour, while the CMR model tended to under-predict the bond slip response. The experimental bond stresses exceeded the ACI 440 and CSA S806 predictions for all bar sizes and contamination groups.
Parcel-Level Land Valuation under Planning Policy Change: A Spatially Based and Segmented Modeling Framework
(University of Waterloo, 2026-06-10) Wu, Zekai
Planning policies shape land markets by defining development rights, regulating land use intensity, and signaling future growth expectations. However, in current practice, land and parcel value estimation remains highly dependent on expert judgment and manual comparison of recent transactions. While professional appraisal methods are effective for individual assessments, they rely heavily on subjective interpretation and lack systematic mechanisms to identify how planning policy changes influence parcel values across large datasets. This limitation is particularly evident in growing suburban municipalities, where frequent policy updates are used to respond to development pressure and evolving growth objectives. As a result, both municipal decision-making and real estate analysis increasingly require data-driven models capable of automatically evaluating the valuation impacts of planning policy changes. This thesis addresses this gap by developing a spatially explicit, data-driven framework to examine how planning policy changes are capitalized into parcel-level land values in the Town of Aurora, Ontario. The research integrates GIS-based spatial analysis with segmented regression and machine learning modeling to move beyond manual valuation approaches. Parcel-level datasets are constructed by combining transaction records with Official Plan designations, zoning regulations, and adjacent based spatial variables. Parcels are further segmented by size into two datasets to distinguish between house driven and land driven valuation mechanisms, enabling the model to identify the conditions under which planning signals emerge in observed prices.
Multi‑Frequency (X‑, C‑, and L‑Band) F‑SAR Analysis of Scattering Behavior of Freshwater Ice on Noell Lake, Northwest Territories
(University of Waterloo, 2026-06-10) Kharoud, Sukhdip
Lake ice plays a critical role in Arctic and sub-Arctic environments, influencing physical processes within lake systems while also supporting a range of socio-economic activities in northern communities. However, despite its importance, the interaction between lake ice and microwave signals remains inadequately understood, particularly in terms of backscatter behavior during the simultaneous acquisition of active microwave wavelengths. This study utilizes the fully polarimetric FSAR (Flexible Synthetic Aperture Radar) system developed by the Deutsches Zentrum für Luft- und Raumfahrt (DLR), which simultaneously acquired repeat-pass imagery at C-, X-, and L-bands over Noell Lake in the Northwest Territories to investigate the dominant scattering mechanisms associated with lake ice. The results of this study indicate that single-bounce scattering is the dominant scattering mechanism over Noell Lake at all frequencies, but with variable intensities proportional to the wavelength. Furthermore, the influence of tubular bubbles is observed in X- and C-bands but is not detectable in the L-band, aligning with recent research suggesting that tubular bubbles do not significantly increase backscatter, but influence the roughness at the ice-water interface, and is therefore wavelength dependent. These coincident observations at X-, C-, and L-bands improve the understanding of microwave interactions with freshwater ice and the role of ice structural variability in influencing wavelength-dependent scattering responses. Additionally, the investigation of ice property retrieval provides a theoretical foundation for future SAR missions, including support for the NASA–ISRO (NISAR) and TanDEM-L L-band sensors.
Long-term Durability of Iron-based Shape Memory Alloys (Fe-SMAs) and their Performance in Structural Strengthening Applications
(University of Waterloo, 2026-06-09) Carofilis, Wilson
A wide range of repair and strengthening techniques have been developed to address vulnerabilities in aging civil infrastructure. Nevertheless, most conventional approaches rely on passive mechanisms that contribute resistance only when external demands are applied. Active retrofitting strategies, by contrast, introduce permanent restorative forces, such as prestressing, that proactively enhance structural performance, reducing damage accumulation and extending service life. Shape memory alloys (SMAs) offer a unique advantage in this context due to their heat-activated shape memory effect, which enables prestressing without bulky equipment or invasive procedures. Among them, iron-based shape memory alloys (Fe-SMAs) have emerged as a cost-effective and promising solution for structural applications. Despite their growing implementation, the long-term durability and sustained mechanical performance of activated Fe-SMAs remain insufficiently understood, limiting their reliable implementation under environmental exposure and repeated loading. This thesis addresses this critical gap through an integrated experimental–numerical investigation of the durability, fatigue behaviour, and seismic retrofit applications of activated Fe-SMA systems. The experimental program quantifies the evolution of mechanical and functional properties under corrosion and repeated loading. Accelerated durability tests were conducted on activated Fe-SMA dogbone specimens exposed to a sodium chloride solution for varying durations to characterize corrosion induced degradation. Likewise, fatigue tests were performed on pre-cracked reinforced concrete (RC) beams strengthened with Fe-SMA strips to evaluate structural-level performance and service-life implications under cyclic loading. Complementing the experimental work, the numerical investigation evaluates an innovative SMA– based seismic retrofitting strategy. Advanced nonlinear static and dynamic time-history analyses were utilized to quantify global seismic response, identify governing SMA material parameters for retrofit design, and determine critical structural demand parameters influencing performance. Additionally, a resilience-based assessment framework incorporating post-earthquake recovery time was implemented to extend evaluation beyond conventional seismic demand metrics toward functional performance. Experimental results demonstrate that activated Fe-SMAs experience progressive reductions in recovery stress, ultimate tensile strength, and deformation capacity as corrosion develops, while retaining reactivation capability at reduced prestress levels. At the structural scale, RC beams strengthened with Fe-SMA exhibit enhanced fatigue resistance, characterized by reduced crack growth, lower deflections, and decreased of steel reinforcement and concrete strain accumulation. Numerical simulations indicate that the proposed retrofit strategy significantly reduces lateral displacements and residual deformations under seismic loading, although potential increases in floor accelerations highlight important design considerations for non-structural components and functional recovery. Overall, this research establishes a multi-scale understanding of activated Fe-SMA performance by explicitly linking material degradation, structural fatigue behaviour, and system-level seismic response. The findings provide new experimental evidence on long-term durability, performance, structural validation under repeated loading, and application-oriented SMA-based retrofit solutions evaluated through resilience metrics. Together, these contributions support the development of more reliable, durable, and resilient active retrofitting strategies for strengthening deficient and seismically vulnerable infrastructure.

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