Dissertation Defense Announcements

Subjective perceptions of social mobility are critical for defending societal system and maintain political stability (Day and Fiske 2017; Houle 2019). This dissertation enhances our understanding of factors that shape beliefs in opportunity for upward mobility by focusing on the living environments in American neighborhoods. Inspired by the research from psychology and development economics, I developed and tested the Opportunity Beliefs Theory to explain how the built environment in neighborhoods affects individuals’ opportunity beliefs. The theory aims to elucidate how environmental factors psychologically affect people’s beliefs and behavior. The Opportunity Beliefs theory argues that the living environment can rouse positive or negative emotions. These emotional incentives shape residents’ self-efficacy. These emotions and self-efficacy largely affect people’s expectations for the future. According to the Opportunity Beliefs Theory, for people with low/middle income, those who live in a neighborhood with a better-maintained built environment are more likely to possess positive emotions and hold a high-level of self-efficacy. Furthermore, these residents will perceive more opportunities for themselves and their children for getting ahead in life, and they are more likely to agree that the opportunities are distributed equally in the society.

I have designed three studies which can support each other to explore the valid causal inferences between the built environment in neighborhoods and opportunity beliefs. First, In order to understand how the built environment in neighborhoods affects Americans’ opportunity beliefs, I designed a conventional survey which can obtain samples nation-wide and has high external validity. Next, I conducted two-round survey experiments to explore the causal inference. The results support my hypotheses.

This dissertation explores the interaction between the living environment and human psychological states and enriches the knowledge of emotions, self-efficacy, and opportunity beliefs. This research has important implications for poverty reduction and redistributive policy.

Gentrification research almost exclusively focuses on traditional postindustrial cities. Despite a growing number of scholars emphasizing the importance of understanding gentrification outside of traditional urban areas, its presence and modalities in mid-sized cities remains underexplored. This holds particularly true in the U.S. South where unique historical processes of industrialization, segregation, and immigration form low-density spatial patterns of urbanization that set Southern cities apart from other U.S. regions. A group of rapidly emerging mid-size U.S. Sunbelt cities – known as the New South – share concerns over a number of converging and interrelated trends: urban core revitalization, rising housing costs, lagging economic mobility, investing in public infrastructure, and shifting demographics. In this context, the New South is an ideal region for investigating longitudinal neighborhood development trends within a gentrification framework. Using a case study approach in Charlotte, my dissertation explores the spatial, temporal, and spatial-temporal aspects of contemporary gentrification. A survival analysis also tests the relationships between gentrification and changes in housing renovation, urban amenities, proximity to light rail development, and other factors. Results reveal that administrative data at the parcel level is more precise at pinpointing where gentrification occurs and how it diffuses overtime. Findings also identify substantial differences between area estimates of gentrification hot spots calculated from parcel data, demonstrating that spatial aggregation error may lead to significant errors in measuring gentrification. Findings suggest that aggregating data to census blocks or tax parcel spatial unit provide more precise measurements of gentrification. Key findings from the survival analysis identify that neighborhood parks and greenways increase the likelihood of gentrification. Results also highlight a strong spatial effect, demonstrating that neighborhood effects do influence spatial patterns of gentrification. Unexpectedly, light rail variables do not increase the likelihood of gentrification. Additional variables that increase the likelihood of gentrification include parcels with older homes, parcels in and around historical areas, lower home values per square foot, proximity to quality education, proximity to highways, and proximity to commercial areas increase the likelihood of gentrification. Thus, at a time when urban areas are rapidly changing and considering how to accommodate future growth, a local level understanding of gentrification aids policy makers and community organizers to tailor more effective public policy.

Several urban areas are building new facilities to encourage users of alternative modes of transportation (e.g., public transportation, walking, and bicycling). The existing infrastructure is changed to accommodate/ encourage these alternative mode users. However, there is not enough evidence to justify whether such plans are instrumental in improving mobility and enhancing safety of the transportation system from a multimodal perspective Therefore, the goal of this research is to model the operational performance and safety of urban roads with heterogeneous traffic conditions to improve the safety, reliability, and mobility of people and goods. A two-step approach is used to assess the operational performance of the urban roads with heterogeneous conditions. Firstly, a travel time reliability-based modeling and analysis was conducted to analyze the transportation system performance comprehensively accounting for all the modes of transportation. Secondly, a simulation-based modeling and analysis was conducted to assess the effect of light rail transit (LRT), pedestrian activity, bicyclist activity, and traffic, individually or combined, on the operational performance of the transportation system. Further, surrogate safety assessment was conducted to check the effect of LRT, pedestrian activity, bicyclist activity, and traffic, individually or combined, on the overall safety performance of the transportation system. Notable effects on operational and safety performance were observed between the modeled and evaluated hypothetical scenarios, emphasizing the need to plan and build infrastructure by evaluating complex mobility patterns and interactions between all the mode users. The proposed methodological framework is cross-disciplinary, transferable, and can be applied to other regions.

To stay competitive within the gas turbine community, turbine aero designers strive to maximize the total work output of each turbine stage through a combination of airfoil design improvements and increased total pressure ratio. Although increasing the mass flow rate could achieve a higher power target, the resultant increase in turbine annulus would result in structural limitations due to longer blades which cause increased strain on the blade root as well as amplified flutter and rotor dynamic excitation. An alternative path to achieving higher power output is to maximize the loading of each turbine stage through increased pressure ratio, but this may lead to airfoil limit loading and high aerodynamic losses.

This research systematically develops a detailed methodology to simulate the prediction of airfoil limit loading as well as provides a thorough investigation into the factors that influence the limit loading condition. A computational baseline was established using data previously collected at the Pratt & Whitney Canada High-Speed Wind Tunnel at Carleton University near design conditions using the Reynolds-Averaged Naiver-Stokes shear stress transport k-ω turbulence model (SST) with γ transition. An adaptive mesh refinement algorithm was developed based on the normalized local cell gradients of total pressure, total temperature, density, turbulent kinetic energy, turbulent eddy viscosity and the specific dissipation rate of turbulence. An overall reduction in computational cost was determined as 50% per simulation. The SST turbulence model with Gamma transition was found to have superior predictive veracity compared to other eddy viscosity turbulence models for the limit loading condition.

Variation of turbine inflow conditions were analyzed for four different transonic turbine airfoils based on the potential flow conditions exhausted by an upstream combustor. Influence of inflow conditions was found to be minimal on the exit flow profile with the exception of the mass-flow averaged total pressure loss coefficients. Results show incidence variation to change the total pressure loss coefficient differently for each airfoil, whereas turbulence intensity and turbulent length scale predicted a drastic rise in loss with increased turbulence level for all airfoils considered. The geometric characteristics of each airfoil were also investigated for influence on the stages to limit loading. Similar to previous experimental work, the limit loading pressure ratio and the mass-flow averaged outlet flow angle were strongly correlated with the airfoil outlet metal angle. It was also determined that the airfoil stagger and trailing edge blockage ratio play a role in the determination of the sublimit loading range, although no definitive parameter could be isolated due to lack of specific geometric constraints.

Lastly, the effect of transient vortex shedding on the nature of the trailing edge shock system and subsequent influence on the stages towards limit loading were investigated. A detailed review of the boundary layer states at the trailing edge were performed showing that all of the modeling approaches predicted laminar boundary layer profiles along the pressure surface trailing edge and turbulent profiles along the suction surface. Each modeling strategy (unsteady Reynolds-Averaged Navier Stokes, Delayed Detached Eddy Simulation and turbulence model free) predicted separation along the suction surface during limit loading due to acoustic wave propagation caused by the shock-base pressure interaction, although with varying degrees of size and magnitude. Temporal evolution of the mass flow averaged total pressure loss coefficient downstream of the airfoil allowed for the dominant vortex shedding frequency to be determined and subsequent Strouhal number to be calculated. It was found that each transient modeling strategy predicted the vortex frequency differently. A formal documentation and review were made outlining the required simulation time step to achieve accurate temporal resolution as well as approximate vortex shedding period. Qualitative images of numerical Schlieren (normalized density gradient) contours were presented and reviewed showing large differences in the prediction of vortex shape, size, and subsequent shock influence. Although conclusions were made on modeling ability, without extensive experimental documentation no concrete justification can be made at this time, outlining the importance of an experimental investigation.