Probabilistic-based hurricane risk assessment and mitigation considering the potential impacts of climate change

Studies are suggesting that hurricane hazard patterns (e.g. intensity and frequency) may change as a consequence of the changing global climate. As hurricane patterns change, it can be expected that hurricane damage risks and costs may change as a result. This indicates the necessity to develop hurricane risk assessment models that are capable of accounting for changing hurricane hazard patterns, and develop hurricane mitigation and climatic adaptation strategies. This thesis proposes a comprehensive hurricane risk assessment and mitigation strategies that account for a changing global climate and that has the ability of being adapted to various types of infrastructure including residential buildings and power distribution poles. The framework includes hurricane wind field models, hurricane surge height models and hurricane vulnerability models to estimate damage risks due to hurricane wind speed, hurricane frequency, and hurricane-induced storm surge and accounts for the timedependant properties of these parameters as a result of climate change. The research then implements median insured house values, discount rates, housing inventory, etc. to estimate hurricane damage costs to residential construction. The framework was also adapted to timber distribution poles to assess the impacts climate change may have on timber distribution pole failure. This research finds that climate change may have a significant impact on the hurricane damage risks and damage costs of residential construction and timber distribution poles. In an effort to reduce damage costs, this research develops mitigation/adaptation strategies for residential construction and timber distribution poles. The costeffectiveness of these adaptation/mitigation strategies are evaluated through the use of a Life-Cycle Cost (LCC) analysis. In addition, a scenario-based analysis of mitigation strategies for timber distribution poles is included. For both residential construction and timber distribution poles, adaptation/mitigation measures were found to reduce damage costs. Finally, the research develops the Coastal Community Social Vulnerability Index (CCSVI) to include the social vulnerability of a region to hurricane hazards within this hurricane risk assessment. This index quantifies the social vulnerability of a region, by combining various social characteristics of a region with time-dependant parameters of hurricanes (i.e. hurricane wind and hurricane-induced storm surge). Climate change was found to have an impact on the CCSVI (i.e. climate change may have an impact on the social vulnerability of hurricane-prone regions).

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

International teachers in the American classroom : deposing the myth of monolingualism

An international graduate teaching assistant‘s way of speaking may pose a challenge for college students enrolled in STEM courses at American universities. Students commonly complain that unfamiliar accents interfere with their ability to comprehend the IGTA or that they have difficulty making sense of the IGTA‘s use of words or phrasing. These frustrations are echoed by parents who pay tuition bills. The issue has provoked state and national legislative debates over universities‘ use of IGTAs. However, potentially productive debates and interventions have been stalemated due to the failure to confront deeply embedded myths and cultural models that devalue otherness and privilege dominant peoples, processes, and knowledge. My research implements a method of inquiry designed to identify and challenge these cultural frameworks in order to create an ideological/cultural context that will facilitate rather than impede the valuable efforts that are already in place. Discourse theorist Paul Gee‘s concepts of master myth, cultural models, and meta-knowledge offer analytical tools that I have adapted in a unique research approach emphasizing triangulation of both analytic methods and data sites. I examine debates over IGTA‘s use of language in the classroom among policy-makers, parents of college students, and scholars and teachers. First, the article "Teach Impediment" provides a particularly lucid account of the public debate over IGTAs. My analysis evidences the cultural hold of the master myth of monolingualism in public policy-making. Second, Michigan Technological University‘s email listserve Parentnet is analyzed to identify cultural models supporting monolingualism implicit in everyday conversation. Third, a Chronicle of Higher Education colloquy forum is analyzed to explore whether scholars and teachers who draw on communication and linguistic research overcome the ideological biases identified in earlier chapters. My analysis indicates that a persistent ideological bias plays out in these data sites, despite explicit claims by invested speakers to the contrary. This bias is a key reason why monolingualism remains so tenaciously a part of educational practice. Because irrational expectations and derogatory assumptions have gone unchallenged, little progress has been made despite decades of earnest work and good intentions. Therefore, my recommendations focus on what we say not what we intend.

Cylinder wall waste heat recovery from liquid-cooled internal combustion engines utilizing thermoelectric generators

This report is a dissertation proposal that focuses on the energy balance within an internal combustion engine with a unique coolant-based waste heat recovery system. It has been predicted by the U.S. Energy Information Administration that the transportation sector in the United States will consume approximately 15 million barrels per day in liquid fuels by the year 2025. The proposed coolant-based waste heat recovery technique has the potential to reduce the yearly usage of those liquid fuels by nearly 50 million barrels by only recovering even a modest 1% of the wasted energy within the coolant system. The proposed waste heat recovery technique implements thermoelectric generators on the outside cylinder walls of an internal combustion engine. For this research, one outside cylinder wall of a twin cylinder 26 horsepower water-cooled gasoline engine will be implemented with a thermoelectric generator surrogate material. The vertical location of these TEG surrogates along the water jacket will be varied along with the TEG surrogate thermal conductivity. The aim of this proposed dissertation is to attain empirical evidence of the impact, including energy distribution and cylinder wall temperatures, of installing TEGs in the water jacket area. The results can be used for future research on larger engines and will also assist with proper TEG selection to maximize energy recovery efficiencies.

MULTIDIMENSIONAL OPTIMAL DROOP CONTROL FOR WIND RESOURCES IN DC MICROGRIDS

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.