<p>This thesis reports on a numerical and experimental investigation of the unsteady loading of high solidity vertical axis wind turbines (VAWTs). Two-dimensional, unsteady Reynolds averaged Navier-Stokes simulations of a small scale, high solidity, H-type Darrieus vertical axis wind turbine revealed the dominant effect of dynamic stall on the power production and vibration excitation of the turbine. Operation of the turbine at low blade speed ratios resulted in complex flow-blade interaction mechanisms. These include; dynamic stall resulting in large scale vortex production, vortex impingement on the source blade, and significant flow momentum extraction.</p> <p>To validate the numerical model, a series of full-scale experimental wind tunnel tests were performed to determine the aerodynamic loading on the turbine airfoils, vibration response behaviour, and wake velocity. In order to accomplish this, a complex force measurement and wireless telemetry system was developed. During the course of this investigation, high vibration response of the turbine was observed. This resulted in conditions that made it difficult or impossible to measure the underlying aerodynamic loading. A vibration mitigation methodology was developed to remove the effect of vibration from the measured aerodynamic forces. In doing so, an accurate and complete measurement of the aerodynamic loading on the turbine blades was obtained.</p> <p>Comparison of the two-dimensional numerical model results to the experimental measurements revealed a considerable over-prediction of the turbine aerodynamic force and power coefficients, and wake velocity. From this research, it was determined that the three-dimensional flow effects due to the finite aspect ratio of the turbine and blades, as well as parasitic losses, could be accounted for through the application of inlet velocity and turbine height correction factors. In doing so, the two-dimensional numerical model results could be properly scaled to represent the three-dimensional flow behaviour of the turbine prototype. Ultimately, a validated VAWT design tool was developed.</p> / Doctor of Philosophy (PhD)

<p>As a mid-size industrial city in North America, the City of Hamilton has been increasingly experiencing urban sprawl in the past six decades coupled with population growth and economic development. The study of various interdependent processes driving the evolution of urban form requires the application of simulation models that offer urban planners and policy-makers an efficient means for evaluating urban development policies. This thesis focuses on the modeling efforts towards building a microsimulation residential housing market system for the City of Hamilton. To this end, two major tasks have been conducted in this research. First, a state-of-the-art agent-based microsimulation housing market framework has been designed. Second, two model components in the microsimulation framework, namely a real estate appraisal model and a new housing development model, have been estimated. The objective of the real estate appraisal model is to assess the market values of existing dwellings based on the housing transactions in the previous period. Thre e model forms, including a traditional hedonic model, a spatial regression model, and a regression Kriging model, have been employed in estimations for comparison purposes. A series of independent variables that describe the characteristics of dwelling, location, and neighborhood are specified in the explanatory model. The comparisons among estimation results demonstrate that the spatial regression model has achieved a higher goodness-of-fit than the traditional hedonic model. In addition, we verified that spatial autocorrelation is present in the residuals of the traditional hedonic model, which is explicitly captured by the spatial regression model. In terms of model prediction accuracy, spatial models (SAR and Kriging) both achieve a certain level of improvements over the traditional hedonic model. Overall, we end up recommending that the SAR model is more appropriate to be incorporated into the microsimulation framework, as it provides the best match between predicted and observed values. The new housing development model enables the development of a dynamic housing supply module in the simulation framework by modeling the location and type decisions during the housing development process for each year. A parcel -level two-tier nested-logit model has been estimated. The model is able to deal with not only the decision to develop a specific vacant residential land parcel, but also the development type choice. In terms of the factors influencing the decision to develop, the picture revealed from the model estimation results is that land developers are more likely to start a development project in greenfields than in brownfields. As for the type choice decision during the development process, a variety of variables describing transportation accessibility, residential amenities, the characteristics of the land parcel and neighborhood are included in the model specifications.</p> / Master of Arts (MA)

<p>This dissertation is based on four years of ethnographic research of contemporary women-only social formations. Two women-only leisure activities, women’s flat track roller derby and women-only home improvement workshops, were selected as sites through which to explore the research problem: problematizing contemporary women onlyness. The research problem is developed in direct contrast to the dominant (naturalized, essentialized, assumed) approach to women onlyness in the literature. Specifically, taking a fresh look at women-only social formations by problematizing women onlyness, through exploring women’s experiences of and meaning making about women onlyness, calls critical attention to women onlyness. The analysis, informed by a conceptual framework that draws on Connell’s concept of ‘gender regime’ and a CCCS-inspired approach to cultural production, reveals the ways that women participants are active in the production of women onlyness gender regimes. Specifically, women’s flat track roller derby skaters and women-only home improvement workshop participants consistently and constantly negotiate essentialized stereotypes of gender as they “win space” for themselves in traditionally male-dominated and masculine defined activities and settings, and make meaning of their involvement in these women-only leisure activities. Women participants produce women onlyness gender regimes in the ways they make time and space for and gender mark these activities, and in social interactions with each other, men, and other women. They work to produce women onlyness gender regimes that are experienced as welcoming, supportive, and comfortable, and encourage women to develop expertise and relationships with other participants. Emphasizing these processes of production reveals that these women onlyness gender regimes are not the natural result of a women-only group or the exclusion of men. These findings contradict the tendency in the existing literature to naturalize women onlyness, and contribute to our understanding of contemporary women-only social formations.</p> / Doctor of Philosophy (PhD)

<p>Although liberal attitudes toward homosexuality have been increasing in recent years, sexual minority youth continue to face bullying and isolation at school. Gay-straight alliances (GSAs) have recently emerged as a solution to this problem. While research demonstrates positive effects of GSAs, little is known about the specific processes through which GSAs work to improve the school climate. We must also consider that GSAs operate in high schools which function as their own bounded social worlds with unique sets of rules and social hierarchies. These hierarchies influence both gay and straight youth’s experiences, including who gets bullied, and who carries out the bullying. Using qualitative research methods, including semi-structured interviews with 50 students from 6 Windsor high schools, including 21 lesbian, gay, bisexual, bi-curious, pansexual and queer (LGBPQ) youth, this study explores these issues. I begin by examining how status hierarchies in high schools vary based on the size of the school and average parental income. In doing so, I argue that status hierarchies should be re-conceptualized from being thought of as simply vertical to accommodate multiple sources of status and varying competition. I then delve into an examination of how status and bullying are interconnected. Here, I find that for both gay and straight students, social networks work to prevent isolation as well as bullying. Bullying in high schools also takes on a situational nature, as bullying episodes often predominate in certain areas and in front of certain status group audiences. Finally, I explore how social networks intersect with gay-straight alliances in various social hierarchies, and how GSAs work as social networks that have a protective ability against bullying. I find that GSAs can work to improve school climate and challenge existing hierarchies, but this is tempered by the hierarchies in place. Implications for anti-bullying strategies are also discussed.</p> / Doctor of Philosophy (PhD)

<p>This dissertation takes a multi-level approach to studying attrition and time-to-completion (TTC) in Canadian graduate programs. I draw on three distinct data sources to provide macro, meso, and micro-level analyses of the characteristics, program features, and other aspects that affect graduate student outcomes. My research is informed by existing attrition models and frameworks and takes a policy sociology approach to providing evidence-based recommendations to be implemented at government, institution, and department levels.</p> <p>My meso-level analysis presented in chapter two uses logistic regression and discrete-time survival analysis with time-varying covariates to analyze data from the Youth in Transition Survey, Cohort B. The pre-entry attributes identified in Tinto’s (1993) model of attrition are examined to help to uncover the type of student most likely to dropout of graduate school. Certain demographic and background characteristics, such as being married and having children, are shown to reduce the likelihood of graduating, while academic performance and experiences tend to be most relevant for entry to graduate school.</p> <p>My third chapter presents my meso-level analysis of TTC and completion rates for thirteen doctoral programs at Carleton University using publically available data for six cohorts. In an effort to deepen our understanding of the variation that exists, program requirements, obtained from archived graduate calendars, are coded and included in my analysis. The results show that at the faculty level, Science reports the lowest average TTC, only slightly lower than Engineering, and Social Sciences have substantially longer average TTC. Completion rates are also shown to vary by discipline and faculty, with Science again reporting the highest completion rates and Social Sciences the lowest. In addition to differences by faculty and disciplines, certain program requirements are found to be negatively associated with successfully completing a doctoral degree.</p> <p>The fourth chapter contains my micro-level analysis of two Sociology departments in two Ontario research intensive universities. My research was informed by interviews with completers, non-completers, and faculty I shed light on the process of attrition and barriers to timely completion. This chapter highlights how aspirations differ between groups of students, and how a department’s climate can have indirect effects on student outcomes. Faculty and students are shown to have some different perceptions of factors that lead to non-completion and the importance of supervisory relationships is found to be paramount to both student experiences and outcomes. Students face many challenges throughout their journey in the doctoral program, but many can be overcome through a department’s recognition of challenges faced as well as a commitment to improve them. Additionally, this paper highlights barriers to timely completion and reasons for withdrawal.</p> / Doctor of Philosophy (PhD)

Purpose: This study investigates how software development organizations can identify and utilize tacit knowledge effectively, aiming to develop a practical framework based on empirical data. By exploring methods for accessing and sharing tacit knowledge, the research seeks to enhance organizational efficiency and innovation in software development. Method: The study is conducted through a qualitative case study within a large software development consultancy. The analysis is based on 27 interviews, conducted with employees from the case company. These were later analyzed in a thematic analysis. Findings: We have pinpointed three barriers, alongside identifying three critical components for establishing a robust organizational framework for knowledge sharing. These include culture, empowerment, and practices. Additionally, we have categorized agile practices into socialization and externalization modes and evaluated them from a knowledge sharing perspective, investigating their respective benefits and utility for knowledge sharing in an agile software development organization. Theoretical contributions: The study adds to the literature on knowledge sharing and agile knowledge management. Providing a more practical, concrete, and defined view of how knowledge can be managed, especially in agile software development organizations and contributing with a comprehensive framework for creating a knowledge sharing organization. Practical implications: The practical implication of this study is that managers can better understand different agile tools and in which way they affect knowledge sharing in the organization so that they can be applied more accurately. The framework also provides recommendations for how the organization should be structured and different aspects to focus on to best support knowledge sharing and knowledge sharing practices. Limitations and future research: The most significant limitation is that the data was collected at one consultancy company operating in the software development industry. As such, the results might lack transferability to other industries. The study also lays a foundation for future research to go deeper into specific activities and see their effects. Keywords: Tacit Knowledge, Software Development, Knowledge Sharing, Knowledge Management, Agile Methodologies, Software Development Life Cycle.

Proactive approaches for preventing attacks through security measurements are crucial for preventing sophisticated attacks. However, proactive measures must employ qualitative security metrics and systemic measurement methodologies to assess security guarantees, as some metrics (e.g., entropy) used for evaluating security guarantees may not capture the capabilities of advanced attackers. Also, many proactive measures (e.g., data pointer protection or data flow integrity) suffer performance bottlenecks. This dissertation identifies and represents attack vectors as metrics using the knowledge from advanced exploits and demonstrates the effectiveness of the metrics by quantifying attack surface and enabling ways to tune performance vs. security of existing defenses by identifying and prioritizing key attack vectors for protection. We measure attack surface by quantifying the impact of fine-grained Address Space Layout Randomization (ASLR) on code reuse attacks under the Just-In-Time Return-Oriented Programming (JITROP) threat model. We conduct a comprehensive measurement study with five fine-grained ASLR tools, 20 applications including six browsers, one browser engine, and 25 dynamic libraries. Experiments show that attackers only need several seconds (1.5-3.5) to find various code reuse gadgets such as the Turing Complete gadget set. Experiments also suggest that some code pointer leaks allow attackers to find gadgets more quickly than others. Besides, the instruction-level single-round randomization can restrict Turing Complete operations by preventing up to 90% of gadgets. This dissertation also identifies and prioritizes critical data pointers for protection to enable the capability to tune between performance vs. security. We apply seven rule-based heuristics to prioritize externally manipulatable sensitive data objects/pointers. Our evaluations using 33 ground truths vulnerable data objects/pointers show the successful detection of 32 ground truths with a 42% performance overhead reduction compared to AddressSanitizer. Our results also suggest that sensitive data objects are as low as 3%, and on average, 82% of data objects do not need protection for real-world applications. / Doctor of Philosophy / Proactive approaches for preventing attacks through security measurements are crucial to prevent advanced attacks because reactive measures can become challenging, especially when attackers enter sophisticated attack phases. A key challenge for the proactive measures is the identification of representative metrics and measurement methodologies to assess security guarantees, as some metrics used for evaluating security guarantees may not capture the capabilities of advanced attackers. Also, many proactive measures suffer performance bottlenecks. This dissertation identifies and represents attack elements as metrics using the knowledge from advanced exploits and demonstrates the effectiveness of the metrics by quantifying attack surface and enabling the capability to tune performance vs. security of existing defenses by identifying and prioritizing key attack elements. We measure the attack surface of various software applications by quantifying the available attack elements of code reuse attacks in the presence of fine-grained Address Space Layout Randomization (ASLR), a defense in modern operating systems. ASLR makes code reuse attacks difficult by making the attack components unavailable. We perform a comprehensive measurement study with five fine-grained ASLR tools, real-world applications, and libraries under an influential code reuse attack model. Experiments show that attackers only need several seconds (1.5-3.5) to find various code reuse elements. Results also show the influence of one attack element over another and one defense strategy over another strategy. This dissertation also applies seven rule-based heuristics to prioritize externally manipulatable sensitive data objects/pointers – a type of attack element – to enable the capability to tune between performance vs. security. Our evaluations using 33 ground truths vulnerable data objects/pointers show the successful identification of 32 ground truths with a 42% performance overhead reduction compared to AddressSanitizer, a memory error detector. Our results also suggest that sensitive data objects are as low as 3% of all objects, and on average, 82% of objects do not need protection for real-world applications.

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