This dissertation provides a comprehensive and practical analysis of basis risk in the U.S. variable annuity market and examines effective fund mapping strategies to mitigate the level of basis risk while controlling for the associated transaction costs. Variable annuities are personal savings and investment products with long-term guarantees that expose life insurers to extensive financial risks. Liabilities associated with VA guarantees are the largest liability component faced by U.S. life insurers and have raised concerns to VA providers and regulators. And the hedging performance of these guarantee liabilities is impeded by the existence of basis risk. I look into 1,892 registered VA-underlying mutual funds and two VA separate accounts to estimate the basis risk faced by U.S. VA providers at the individual fund level and the separate account level. To evaluate the degree to which basis risk can be mitigated, I consider various proxy instrument sets and assess different variable selection models. The LASSO regression is shown to be most effective at identifying the most suitable (combination of) mapping instruments that minimize basis risk, compared to other test-based and screening-based models. I supplement it with the Sure Independence Screening (SIS) procedure to further limit the number of instruments requested in the hedging strategies, and modify it by introducing the diff LASSO regression to restrict the changes in instrument allocations across rebalancing periods and, therefore, control for transaction costs. I show that VA providers can reduce their exposure to basis risk by applying data analytic techniques in their mapping process, by hedging with ETFs instead of futures contracts, and through diversification at the separate account level. Combining the traditional fund mapping method with the machine learning algorithm, the proposed portfolio mapping strategy is efficient at reducing basis risk in VA separate accounts while controlling for the tractability and transaction costs of the mapping and hedging procedure, and is practical to incorporate newly-developed VA funds, as well as the varying compositions of separate accounts. Overall, this study presents that U.S. VA providers have the ability to mitigate basis risk to a greater extent than the limited literature on this topic has suggested. / Business Administration/Risk Management and Insurance

Current progress in mobility assistive devices revolves around traditional actuation methods including electric motors, hydraulics, and pneumatic cylinders to provide assistive joint torques to the user. While these mechanisms are effective at providing the torques needed, they are often bulky, heavy, and suffer from poor alignment with the joints of the user. These drawbacks have created a need for novel technologies that can provide a more compact and compliant form of actuation. Twisted and coiled polymers, under the thermomechanical class of smart material actuators, have emerged as a strong candidate for use as soft actuators in assistive devices due to their low cost, commercial availability, high stroke capacity, and power density. Progress to their development is currently limited by lack of proper standardization in the fabrication process, along with incomplete characterization of its quasi-static mechanical and thermal behaviours and how the performance is influenced by various design considerations. This thesis defined a fabrication process of twisted coiled polymer actuators and evaluated the trends between design considerations and their impacts on the final actuator performance. In this work, a fabrication rig was developed to manufacture consistent and repeatable actuators, while enabling the control of various identified design parameters. Subsequently, a comprehensive experimental evaluation was accomplished which resulted in a better understanding of the relationships between these parameters and the actuator performance including its tensile stroke, force generation, and variable stiffness properties. The results provided a foundation for designers to consider which variables should be controlled during both actuator fabrication and operation, in order to optimize its final performance to meet a set of prescribed requirements.

This thesis focuses on evaluating the appropriate speed at which vehicles should travel under different traffic conditions on freeways and its impact on crash frequency. The common belief is that the lower speed results in fewer crashes as reduced speed provides drivers with more time to react effectively and avoid collisions. However, this perspective overlooks the interplay among traffic speed, average spacing between consecutive vehicles, and the distance available for stopping a vehicle. Hence, we propose a safety parameter termed ‘Safety Correlate' (SCORE), which is defined as the proportion of average spacing relative to the stopping distance. To determine the relationship between SCORE and crash frequency, data from 366 4-lane urban freeway segments located in Virginia was analyzed and a Random-effects Poisson Lognormal model was developed. The obtained result indicated that the safety parameter SCORE is negatively associated with the annual hourly crash frequency, implying that the lesser the average spacing as a proportion of the stopping distance while traffic flow remains constant, the more frequent will be the crashes. Additionally, this research presents an application of SCORE in setting variable speed limits under various traffic flows. Overall, the study results provide valuable insights by investigating SCORE to improve traffic safety. Also, this research would help practitioners and policymakers to incorporate safety aspects while setting variable speed limits on freeways.

Fault Detection and Diagnosis (FDD) constitutes an essential aspect of modern life, with far-reaching implications spanning various domains such as healthcare, maintenance of industrial machinery, and cybersecurity. A comprehensive approach to FDD entails addressing facets related to detection, invariance, isolation, identification, and supervision. In FDD, there are two main perspectives: model-based and data-driven approaches. This thesis centers on model-based methodologies, particularly within the context of control and industrial applications. It introduces novel estimation strategies aimed at enhancing computational efficiency, addressing fault discretization, and considering robustness in fault detection strategies. In cases where the system's behavior can vary over time, particularly in contexts like fault detection, presenting multiple scenarios is essential for accurately describing the system. This forms the underlying principle in Multiple Model Adaptive Estimation (MMAE) like well-established Interacting Multiple Model (IMM) strategy. In this research, an exploration of an efficient version of the IMM framework, named Updated IMM (UIMM), is conducted. UIMM is applied for the identification of irreversible faults, such as leakage and friction faults, within an Electro-Hydraulic Actuator (EHA). It reduces computational complexity and enhances fault detection and isolation, which is very important in real-time applications such as Fault-Tolerant Control Systems (FTCS). Employing robust estimation strategies such as the Smooth Variable Structure Filter (SVSF) in the filter bank of this algorithm will significantly enhance its performance, particularly in the presence of system uncertainties. To relax the irreversible assumption used in the UIMM algorithm and thereby expanding its application to a broader range of problems, the thesis introduces the Moving Window Interacting Multiple Model (MWIMM) algorithm. MWIMM enhances efficiency by focusing on a subset of possible models, making it particularly valuable for fault intensity and Remaining Useful Life (RUL) estimation. Additionally, this thesis delves into exploring chattering signals generated by the SVSF filter as potential indicators of system faults. Chattering, arising from model mismatch or faults, is analyzed for spectral content, enabling the identification of anomalies. The efficacy of this framework is verified through case studies, including the detection and measurement of leakage and friction faults in an Electro-Hydraulic Actuator (EHA). / Thesis / Candidate in Philosophy / In everyday life, from doctors diagnosing illnesses to mechanics inspecting cars, we encounter the need for fault detection and diagnosis (FDD). Advances in technology, like powerful computers and sensors, are making it possible to automate fault diagnosis processes and take corrective actions in real-time when something goes wrong. The first step in fault detection and diagnosis is to precisely identify system faults, ensuring they can be properly separated from normal variations caused by uncertainties, disruptions, and measurement errors. This thesis explores model-based approaches, which utilize prior knowledge about how a normal system behaves, to detect abnormalities or faults in the system. New algorithms are introduced to enhance the efficiency and flexibility of this process. Additionally, a new strategy is proposed for extracting information from a robust filter, when used for identifying faults in the system.

[pt] Uma bomba centrífuga, depois de concluída a sua instalação, deve vencer uma elevação constante. A variação da rotação vai alterar diretamente a descarga. Como bomba centrífuga é acionada por motor de indução, a variação da freqüência não acarreta variação proporcional na rotação devido a que a nova rotação implica em outro valor da descarga que somente ocorre com torque diferente do anterior e em conseqüência, o deslizamento deve se ajustar para igualar o torque fornecido pelo motor com o novo torque requerido pela bomba. A análise parte dos estudos que relacionam a descarga com a rotação para relacionar a descarga com a freqüência. / [en] Once installation is concluded, a centrifugal pump should withstand constant head. The variation of rotation directly alters the discharge. Since centrifugal pump operates by induction motor, the variation in frequency does not lead to proporcional variation in rotation due to the new rotation being of another discharge value which only occurs with a different torque. Consequently, the sllep should adjust itself to equalize the torque provided by the motor to the new torque required by the pump. The analisis derives from studies which related the discharge to the rotation in order to relate the discharge to the frequency.

Rock grouting is an effective technique frequently used in rock engineering to reduce  groundwater ingress and increase the stability of surrounding rock mass. The real time grouting control (RTGC) is one of widely used  analytical models to predict the grouting process. In previous research, this method was discussed under constant pressure condition. However, in practice, the injection is not always constant. The effect of variable injection pressure was not fully discussed. In this study,  a 2D radial single-phase flow model is applied to describe the rock grouting process. The model  is solved using numerical integration to incorporate variable injection pressure. The sensitivity of the model is reviewed afterward. In this paper, the dynamic grouting technique is analyzed using the new model. Field data from three rock engineering projects are compared with the model prediction to assess the performance of the model. The results from  the traditional  RTGC  method  are  compared with the model prediction.  The results show that  modeling prediction using variable injection  pressure condition significantly differs from that using constant injection pressure.  Moreover, time-variable model which is an extended version of the traditional RTGC theory shows a slightly better prediction when compared with recorded data and RTGC result. It also can be concluded that dynamic grouting could improve grouting performance from an analytical perspective. In the end, this research would result in an effective tool for further study in this field. / Berginjektering är en effektiv teknik som ofta används inom bergteknik för att minska grundvatteninträngning och öka stabiliteten hos omgivande bergmassa. The real time grouitng control (RTGC) är en av de mycket använda analytiska modellerna för att förutsäga injekteringsprocessen. I tidigare forskning har denna metod diskuterats under konstant tryck. Men i praktiken är injektionen inte alltid konstant. Effekten av variabelt insprutningstryck diskuterades inte fullständigt. I denna studie används en 2D radiell enfasflödesmodell för att beskriva berginjekteringsprocessen. Modellen löses med hjälp av numerisk integration för att införliva variabelt insprutningstryck. Modellens känslighet granskas efteråt. I denna artikel analyseras den dynamiska injekteringstekniken med den nya modellen. Fältdata från tre bergtekniska projekt jämförs med modellprognosen för att bedöma modellens prestanda. Resultaten från den traditionella RTGC-metoden jämförs med modellprognosen. Resultaten visar att modelleringsförutsägelse med användning av variabelt insprutningstrycksvillkor avsevärt skiljer sig från det som använder konstant insprutningstryck. Dessutom visar tidsvariabel modell, som är en utökad version av den traditionella RTGC-teorin, en något bättre förutsägelse jämfört med registrerade data och RTGC-resultat. Man kan också dra slutsatsen att dynamisk injektering skulle kunna förbättra injekteringsprestandan ur ett analytiskt perspektiv. I slutändan skulle denna forskning resultera i ett effektivt verktyg för vidare studier inom detta område.

The evolution of electronics in the vehicle industry has introduced the possibility for more X-by-wire systems in future vehicles. However, the use of steer-by-wire systems has not yet been widelyimplemented. This opens up an opportunity to explore strategies around the potential use of such asystem.The purpose of the project was to evaluate how to design a variable steering ratio which would give asuitable ratio in all speeds. This would, in turn, make it possible to reduce the need for large steeringwheel angles. Additionally, steering wheel designs which can be implemented with a steer-by-wiresystems are discussed and what possibilities there are to move certain interfaces to the steering wheel.The evaluation process consisted of driving a real car with a constant steering ratio in normal trafficand later modelling a variable steering ratio and testing it in a simulator. This was to get data on howlarge steering wheel angles that are needed in different driving scenarios to then be able to design asuitable variable steering ratio. The tests conducted on normal roads in a real car has shown that thedriver utilises the whole steering range (full lock-lock distance) at speeds below 30 km/h and about±10° on the steering wheel at high speeds. The tests conducted in the simulator show that the variablesteering ratio presented in this report decreases the workload on the driver most of all at speeds below30 km/h.The variable steering ratio presented has been compared with a fixed steering ratio in the simulatorand the tests show that the variable steering ratio works similar to the fixed steering ratio in the samescenarios. The variable steering ratio also decreases the need for a steering wheel angle greater than±180°.

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This study seeks to validate a recently introduced global preconditioning technique for the Euler equations. Energy and enthalpy equations are nondimensionalized by means of a reference enthalpy, resulting in increased numerical accuracy for low-speed flows. A cellbased, finite volume formulation is used, with Roe flux difference splitting and both explicit and implicit time integration schemes. A Newton-linearized iterative implicit algorithm is implemented, with Symmetric Gauss-Seidel (LU/SGS) nested sub-iterations. This choice allows one to retain time accuracy, and eliminates approximate factorization errors, which become dominant at low speed flows. The linearized flux Jacobians are evaluated by numerical differentiation. Higher-order discretization is constructed by means of the MUSCL approach. Locally one-dimensional characteristic variable boundary conditions are implemented at the farfield boundary. The preconditioned scheme is successfully applied to the following traditional test cases used as benchmarks for local preconditioning techniques: point disturbance, flow angle disturbance, and stagnation point arising from the impingement of two identical jets. The flow over a symmetric airfoil and a convergentdivergent nozzle are then simulated for arbitrary Mach numbers. The preconditioned scheme greatly enhances accuracy and convergence rate for low-speed flows (all the way down to M ≈ 10E − 4). Some preliminary tests of fully unsteady flows are also conducted.

Weeds typically grow in patches across agricultural landscapes. Because of this characteristic growth pattern, it seems logical to apply herbicides site-specifically to control them. To do this effectively, methods must be identified to accurately map weed presence and make cost effective herbicide application decisions to control them. The primary objective of this research was to develop a site-specific herbicide decision support system. Additional objectives include evaluating the effects of sampling patterns and interpolation techniques for weed mapping accuracy and evaluating texture analysis for weed patch detection in row-crops. A geographic information system (GIS) extension was developed to work in conjunction with a commercial software component for calculating site-specific herbicide applications based on user input weed maps. Results of the extension were compared to that of the commercial software. The GIS extension was able to accurately develop herbicide options based on the given weed densities and potential net return for treatment of the weeds in any specific area of the field. Sampling techniques and interpolation methods were compared to assess the accuracy of each pattern/method combination. The patterns used in this study were the W- and Z-shaped pattern, and the interpolation methods used were kriging and inverse distance weighted. Neither the pattern nor method impacted the results of the predicted average values for a given weed species. The last objective addressed was texture analysis? ability to distinguish weed patches in row-crops. Texture analysis was also tested to determine its ability to distinguish between areas requiring a herbicide application and areas not requiring a herbicide application. The analysis was performed on 3 vegetative indices and the NIR band of multispectral imagery at three different spatial resolutions (0.14 m, 0.5 m, and 1 m), and for two dates in the growing season. Texture analysis performed better on late season for both scenarios, with the highest classification accuracies (45 to 75%) coming from distinguishing areas that were below a given weed threshold from those that were above.