The City of Winnipeg, located at the confluence of the Red and Assiniboine Rivers, has over 240 km of natural riverbank property. The increased frequency and magnitude of flooding along the Red and Assiniboine Rivers over the past decade appears to have influenced the number of slope failures along riverbank property, resulting in the loss of both public green space and privately owned land. The loss of private and public property adjacent to the river has led to the loss of valuable real estate and public parkland amenities. To ensure that riverbank property is preserved for future generations, the City of Winnipeg wants to increase the stability of certain reaches of publicly owned riverbank property along the Red and Assiniboine Rivers that are prone to slope movements. Extensive research has been conducted on slope stability problems in the Winnipeg area, but a transparent prioritization procedure for the remediation of riverbank stability problems has not existed. Therefore, a Riverbank Asset Management System (RAMS) was developed for publicly owned riverbank property to prioritize riverbank slope stability problems along the Red and Assiniboine Rivers. The RAMS provides the City of Winnipeg with a rational approach for determining risk levels for specific reaches of the Red and Assiniboine Rivers. The calculated risk levels allow the City to develop recommended response levels for slope stability remediation projects in a fiscally responsible manner with minimal personal and political influences. This system permits the City to facilitate timely and periodic reviews of priority sites as riverbank conditions and input parameters change.

Geotechnical engineering design has relied upon deterministic methods of analysis whereby values for analysis parameters and conditions are selected subjectively based on judgment with the intent of providing acceptable margins of safety. The objective of this research was to improve the use of probabilistic slope stability analysis in practice so that the design of slopes can be made on a consistent and probabilistic basis. The current research involved the development of a methodology for the measurement and modeling of the anisotropic autocorrelation distance of cohesive soils, which was demonstrated at Dyke 17 West of the McArthur Falls Generating Station. In-situ testing using the piezocone and laboratory testing was conducted to characterize the spatial variability of the effective-shear strength envelope. Vertical (down-hole) and horizontal (cross-hole) geostatistical analysis was conducted to assess the anisotropy of the semivariogram. The investigation identified that heterogeneous inclusions had significant impacts on the results, but that simplistic (visual) identification and filtering procedures were adequate. The effective-stress shear strength envelope was statistically characterized as a random field, which was simulated as a first-order Markov process using customized add-in functions in a limit-equilibrium slope stability analysis. The analysis accounts for the spatial variability of shear strength and is capable of simulating both isotropic and anisotropic autocorrelation functions. The study showed that the critical slip surface geometry and the probability of failure can be significantly different when the anisotropy of spatial correlation is accounted for. The study also showed that neglecting spatial correlation may over-estimate the probability of failure, however this finding was noted to be likely case-specific. The primary conclusion of the study was that appropriate representation of spatial correlation is essential to calculating the probability of failure. Finally, convergence of the probabilistic simulation was evaluated using bootstrapping of the simulated factor of safety distribution to assess the standard error in the mean factor of safety, standard deviation of factor of safety and the probability of failure. A convergence criterion based on the percentage standard error in the probability of failure was proposed and used to define the number of Monte-Carlo iterations required.

The City of Winnipeg, located at the confluence of the Red and Assiniboine Rivers, has over 240 km of natural riverbank property. The increased frequency and magnitude of flooding along the Red and Assiniboine Rivers over the past decade appears to have influenced the number of slope failures along riverbank property, resulting in the loss of both public green space and privately owned land. The loss of private and public property adjacent to the river has led to the loss of valuable real estate and public parkland amenities. To ensure that riverbank property is preserved for future generations, the City of Winnipeg wants to increase the stability of certain reaches of publicly owned riverbank property along the Red and Assiniboine Rivers that are prone to slope movements. Extensive research has been conducted on slope stability problems in the Winnipeg area, but a transparent prioritization procedure for the remediation of riverbank stability problems has not existed. Therefore, a Riverbank Asset Management System (RAMS) was developed for publicly owned riverbank property to prioritize riverbank slope stability problems along the Red and Assiniboine Rivers. The RAMS provides the City of Winnipeg with a rational approach for determining risk levels for specific reaches of the Red and Assiniboine Rivers. The calculated risk levels allow the City to develop recommended response levels for slope stability remediation projects in a fiscally responsible manner with minimal personal and political influences. This system permits the City to facilitate timely and periodic reviews of priority sites as riverbank conditions and input parameters change.

Wind-induced damages on low-slope roofs are a major and common problem that many buildings located in high wind areas suffer from. Most of these damages are initiated when the metal roof edge fails first, leading to overall roof failure. This is because peak wind pressures occur at the edges and corners of low-slope roof buildings. Currently, there are not enough wind design guidelines for the Canadian roofing community to quantify the dynamic wind uplift resistance of the roof edge system. The objective of this research is to evaluate the effect of wind-induced loads on roof edges using a finite element model, verify the numerical results with those obtained from controlled experiments, and perform parametric investigations for various design variables. In this research, the overall roof edge system was modelled using the commercial finite element software package ABAQUS, by simulating the roof edge system with shell elements and applying a uniform static pressure against the face of the edge cleat or coping. Results of the modelling were compared to the experimental ones in terms of deflection of the coping under uniform pressure. The results of the numerical model and the experiments show a good agreement. Furthermore, a parametric analysis of the system was conducted under the effect of varying parameters. i.e., coping gauge, nail spacing, coping and cleat length and wind and thermal load application.

The purpose of this study was to develop a methodology to analyse ROV video and scanning-sonar data to document the abundance and distribution of epi-benthic megafauna on the continental slope off Vancouver Island and to quantify the impact of trawling on these megafaunal assemblages. Impacts of bottom trawling on deep-sea ecosystems vary depending on habitat types and species present. Environmental factors such as depth, dissolved oxygen concentration, substratum type, and bottom roughness also affect the diversity and composition of benthic communities. We studied two transects (30km and 12km long) on the upper continental slope off Vancouver Island, BC, Canada, that included areas of seafloor with visible trawl marks. Our study area was also located in an oxygen minimum zone with very low bottom water dissolved oxygen concentrations in its core (600m-1000m). The main target for bottom trawling fisheries in this area is the longspine thornyhead (Sebastolobus altivelis). Field data were collected using the ROV ROPOS equipped with a 3CCD video camera and high-resolution scanning sonar. Megafaunal composition/abundance and bottom characteristic information were extracted from video imagery and assembled using a custom-designed MS Access database. The same database was used to compile information on trawl-door marks detected in recorded sonar imagery. The sonar surveyed a 50m radius around the submersible during transects, providing a broader view of evidence of trawling in the area than video. This thesis reports on relationships between environmental variables and faunal abundance, diversity and species distribution. Following the video and sonar analysis, diversity patterns and general species distribution for both transects were determined. Relationships of community structure to depth and trawling intensity were investigated using the hierarchical clusters technique to identify similarities in the megafauna assemblages between stations . Finally, spatial structures in the megafaunal community and their associated environmental variables were examined using the Principal Coordinates Neighbour Matrices (PCNM) and redundancy analysis tests. Differences in total abundance, species composition and distribution, and species diversity were detected between the high and low trawling intensity areas. One of the main highlights of our results was the dominance of ophiuroids and holothurians along most of the transect, except for the highly trawled area. Spatial structures were identified in the megafaunal community, showing a strong influence of bottom trawling intensity and, to a lesser extent, depth. Nearby water column measurements of dissolved oxygen concentrations suggest that depth might be associated with dissolved oxygen levels, but in situ oxygen data were not available during the ROV surveys. A deeper understanding of in situ oxygen levels would help clarify the role of this factor in shaping megafauna assemblages and its interaction with trawling. / Graduate

Die Oberflächen von Erdbauwerken sind neben den von der Funktion abhängigen Beanspruchungen z. B. als Verkehrsdamm, Deponieböschung oder Deich, auch witterungsbedingten Einwirkungen ausgesetzt. Frost-Tau-Wechsel können zur Auflockerung der obersten Schichten führen und Tauperioden sowie starke Niederschläge zur Sättigung des Bodens. In letzter Zeit häufen sich Rutschungen der oberflächennahen Bereiche an Verkehrsdämmen, Lärmschutzwällen und teilweise auch an Deichen. Ursachen sind die unzureichende Festigkeit des Bodens, die fehlende Stabilisierung durch Bewuchs und Beanspruchungen durch abströmendes Wasser. Das Forschungsprojekt am ZAFT hat zum Ziel, die oberste Schicht von Böschungen zu verbessern. Es sollen wirtschaftliche Alternativen zu den klassischen Verfahren des Erd- und Grundbaus entwickelt werden, mit denen die flächendeckende Sicherung von Erdbauwerken möglich wird.

This thesis studies the value of branding in the smartphone market. Measuring brand value with data available at product level potentially entails computational and econometric challenges due to data constraints. These issues motivate the three studies of the thesis. Chapter 2 studies the smartphone market to understand how operating system platform providers can grow one of the most important intangible assets, i.e., brand value, by leveraging the indirect network between two user groups in a two-sided platform. The main finding is that iPhone achieved the greatest brand value growth by opening its platform to the participation of third-party developers, thereby indirectly connecting the consumers and the developers via its app store effectively. Without the open app store, I find that iPhone would have lost its brand value by becoming a two-sided platform. Hence these findings provide an important lesson that open platform strategy is vital to the success of building platform brands. Chapter 3 solves a computational challenge in structural estimation of aggregate demand. I develop a computationally efficient MCMC algorithm for the GMM estimation framework developed by Berry, Levinsohn and Pakes (1995) and Gowrisankaran and Rysman (forthcoming). I combine the MCMC method with the classical approach by transforming the GMM into a Laplace type estimation framework, therefore avoiding the need to formulate a likelihood model. The proposed algorithm solves the two fixed point problems, i.e., the market share inversion and the dynamic programming, incrementally with MCMC iteration. Hence the proposed approach achieves computational efficiency without compromising the advantages of the conventional GMM approach. Chapter 4 reviews recently developed econometric methods to control for endogeneity bias when the random slope coefficient is correlated with treatment variables. I examine how standard instrumental variables and control function approaches can solve the slope endogeneity problem under two general frameworks commonly used in the literature.

For two fire seasons in Nordegg, Alberta, a system of in-stand weather stations were arranged along a north and south aligned valley and combined with collection of destructive fine fuel moisture content data in order to quantify variations due to differences in slope and aspect. South-facing sites were found to be slightly warmer (1.5°C), less humid (5%) and received on average 20% more solar radiation than the north-facing sites during the peak burning period of the day. Based on these weather observations a difference of 1 or 2 % moisture content between north and south sites was predicted using existing theoretical relationships. A corresponding difference in observed moisture content was not identified, due to the low transmittance recorded at the in-stand sites (<10% of open solar radiation measurements), variation amongst destructive samples and logistical limits on the number of replicates collected.

This thesis studies the value of branding in the smartphone market. Measuring brand value with data available at product level potentially entails computational and econometric challenges due to data constraints. These issues motivate the three studies of the thesis. Chapter 2 studies the smartphone market to understand how operating system platform providers can grow one of the most important intangible assets, i.e., brand value, by leveraging the indirect network between two user groups in a two-sided platform. The main finding is that iPhone achieved the greatest brand value growth by opening its platform to the participation of third-party developers, thereby indirectly connecting the consumers and the developers via its app store effectively. Without the open app store, I find that iPhone would have lost its brand value by becoming a two-sided platform. Hence these findings provide an important lesson that open platform strategy is vital to the success of building platform brands. Chapter 3 solves a computational challenge in structural estimation of aggregate demand. I develop a computationally efficient MCMC algorithm for the GMM estimation framework developed by Berry, Levinsohn and Pakes (1995) and Gowrisankaran and Rysman (forthcoming). I combine the MCMC method with the classical approach by transforming the GMM into a Laplace type estimation framework, therefore avoiding the need to formulate a likelihood model. The proposed algorithm solves the two fixed point problems, i.e., the market share inversion and the dynamic programming, incrementally with MCMC iteration. Hence the proposed approach achieves computational efficiency without compromising the advantages of the conventional GMM approach. Chapter 4 reviews recently developed econometric methods to control for endogeneity bias when the random slope coefficient is correlated with treatment variables. I examine how standard instrumental variables and control function approaches can solve the slope endogeneity problem under two general frameworks commonly used in the literature.

For two fire seasons in Nordegg, Alberta, a system of in-stand weather stations were arranged along a north and south aligned valley and combined with collection of destructive fine fuel moisture content data in order to quantify variations due to differences in slope and aspect. South-facing sites were found to be slightly warmer (1.5°C), less humid (5%) and received on average 20% more solar radiation than the north-facing sites during the peak burning period of the day. Based on these weather observations a difference of 1 or 2 % moisture content between north and south sites was predicted using existing theoretical relationships. A corresponding difference in observed moisture content was not identified, due to the low transmittance recorded at the in-stand sites (<10% of open solar radiation measurements), variation amongst destructive samples and logistical limits on the number of replicates collected.