COVID-19 pandemic has caused a severely detrimental effect on the physical, psychological, and functional well-being of the older adults by limiting their social and out-of-home activities, which in turn is likely to affect their habitual physical activity level. Physical activity (PA) is vital for healthy aging and the health-related benefits of PA for older adults are well-established. In the current context of COVID-19 pandemic, the changes in PA level, resulting from physical distancing adherence and social isolation, can be a major health concern for the older adults, as they are more prone to physical inactivity than the younger population. Accurate PA assessment at population levels is necessary to understand the trend in PA and sedentary behavior among the older adults during the pandemic. Self-reported assessments can be inexpensive and easy to administer, but they are often subjected to measurement biases such as misinterpretations or deliberate alterations (social desirability bias) and participants having difficulty in remembering activities (recall bias). Accelerometer-based PA monitoring can overcome these limitations of self-reported assessment and objectively measure the amount and intensity of PA in a free-living environment. The objective of this study is to examine the PA levels in the older adults, who were living under the physical distancing guidelines during the COVID-19 pandemic, using an accelerometry-based assessment. The study also investigates how such objectively measured PA levels varied among the older adults based on different sociodemographic factors. In this cross-sectional study, 124 community-dwelling older adults (Age: 60–96 years) were recruited from the region of Central Florida between March 2021 and August 2021. The findings of this study can infer guidelines and/or interventions to promote physical activity and healthy aging among the older adults, particularly those who are susceptible to social isolation and disconnectedness due to COVID-19 pandemic.

A novel experiment has been conducted to investigate the effect of dynamic spanwise bending on the formation of a dynamic stall vortex on a rapidly pitching flat plate. Experiments have been performed in a towing tank at different nondimensional pitch rates (Kp) in the range of 0.4112 < Kp < 0.8225, and four maximum pitch angles (30° , 45°, 60°, and 90°) at a Reynolds number of 12,000. Synchronized direct force measurements and particle image velocimetry (PIV) are used to characterize the effect of bending on the unsteady forces and the flow field. An unsteady analytical model based on the bending and pitching kinematics is used to model the lift force histories. It is found that a spanwise bending of a pitching wing alleviated the unsteady lift forces. However, the main contribution was found to come from the non-circulatory forces. The circulation and pressure analysis of the pitching wing revealed little or no sensitivity to the wing bending motions examined.

Deep learning has shown success in several applications involving pattern recognition, expert systems, and scientific discovery. However, existing methods struggle with industrial applications, which are often challenged by non-ideal datasets. In many cases, the datasets are small, poorly labeled, noisy, or have unbalanced class distribution or any combination of such problems. In this Master's research, we propose a generative adversarial network (GAN) strategy that is able to circumvent limitations imposed by tiny datasets. As a case study, we use the extrapolation of corrosion in automobiles and feed our deep learning framework with only a few dozen images instead of the thousands to million images commonly found in many computer vision problems. In order to handle such a reduced dataset, we use one GAN for the rust level and one for the rust texture. The rust level GAN is conditional on random samples from the dataset and uses an additive random noise in the latent space to add variability to the generated rust level maps. The rust texture GAN adds shades of brown to the outputs of the rust level GAN. Loss functions are carefully designed to produce a robust training scheme for both GANs. In addition, given the significantly reduced size of our dataset, it is unfeasible to break down the data into training, validation, and test sets. We overcome this limitation by using the discrepancy between the generated and target distributions of the rust level and texture intensities as a way to monitor the convergence of training. The resulting models can ingest an image with a car having no corrosion and generate an image of this car with parts exhibiting varying degrees of corrosion (from mild to moderate to severe).

The focus of this thesis is to research, analyze, and design a reliable and economical control system for the Cal Poly Wind Energy Capture System (WECS). A dynamic permanent magnet generator model is adopted from [1] and [2] and combined with an existing wind turbine model to create a non-linear time varying model in MATLAB. The model is then used to analyze potentially harmful electrical disturbances, and to define safe operating limits for the WECS. An optimal operating point controller utilizing a PID speed loop is designed with combined optimization criteria and the final controller design is justified by comparing performance measures of energy efficiency and mitigation of mechanical loads. The report also discusses implications for a WECS when blade characteristics are mismatched with the generator. Finally, possible ways to improve the performance of the Cal Poly WECS are addressed.

This thesis presents an analysis of CubeSat orbits for both Low Earth Orbit (LEO) and Sun-Synchronous Orbit (SSO) missions using Systems Tool Kit (STK). The study focuses on analyzing communication, power generation, and radiation exposure while considering various factors. The analysis is based on the 3U CubeSat called UT-ProSat-1, developed by students at Virginia Polytechnic Institute and State University (VT) for an upcoming mission. The orbit size and mass adjustments were made for the LEO mission to enhance communication performance. The influence of solar activity on CubeSat lifetime and access time was examined, highlighting the significance of mass and solar activity. The impact of increasing orbit size on communication time was analyzed, emphasizing the trade-offs between mass, orbit size, and communication performance. The SSO mission prioritized power generation optimization resulted in generating sufficient power for the nominal phase of the mission. It also considered the effects of the South Atlantic Anomaly (SAA) on radiation exposure. Effective risk management of increasing the shielding for the avionics were emphasized which consequently will stabilize the orbit and prolong its lifetime. Additionally, temperature dynamics were investigated, indicating the need for further analysis considering heat dissipation and utilizing a more accurate CubeSat model. The insights gained from this study contribute to the improved the performance of CubeSats and validate the mission results, providing valuable information for successful missions in the future. / Master of Science / This project explored the trajectories that small satellites, known as CubeSats, follow around Earth. Two main paths were investigated: the Low Earth Orbit (LEO), which is close to the Earth's surface, and the Sun Synchronized Orbit (SSO), which aligns with the Sun's movement. The software called Systems Tool Kit (STK) served as the simulation tool, helping to analyze the satellites' abilities to communicate, generate power, total space radiation, and satellite's temperature throughout the missions. The study was conducted on the satellite called UT-ProSat-1, a design by students from Virginia Polytechnic Institute and State University (VT). For the LEO path, changes to the satellite's size and weight were applied to analyze its effect on the communication capabilities. Also the Sun's effect on the satellite's operational life and communication windows was assessed. Changes in the satellite's orbit can influence its communication duration, and this necessitates a balance between its weight, trajectory, and communication capacity. Regarding the Sun-aligned path, SSO, the power generated from the Sun was sufficient for the satellite's power needs throughout its mission. A particular space zone with high radiation, the South Atlantic Anomaly (SAA), was evaluated. The majority of total radiation build up on the satellite was determined to came from this area. However, risks associated with this radiation can be minimized by enhancing protection for the satellite's electronics. Such measures not only safeguard the satellite but also increase its stability and longevity in space. The temperature behavior of the satellite was analyzed, underscoring the need for a deeper examination of its thermal patterns. Insights from this study will bolster CubeSat performance and provide valuable information for future successful space missions.

There is a small but growing population of people who suffer from impaired balance. The causes range from old age to stroke to cerebral palsy. For those with only minor problems staying upright, a cane or walker is all that is needed. For some it is so debilitating that they are confined to a wheel chair. The precise cause of impairment can vary. In some, the vestibular, proprioceptive or visual impairments affect balance. In others, muscle weakness or brain damage is the cause. In another group, the brain never learned to balance in the first place. Relearning how to balance can be a struggle requiring months of costly physical therapy with a physical therapist. A machine that could help teach them how to balance would be a great help in the improvement of their lives. This thesis presents a set of control models for an exoskeleton that will stabilize and restore stability to those with impaired balance. The control models are designed for an exoskeleton to initially force the wearer into a known profile for balancing and moving. There will then be a steady reduction in the authority of the exoskeleton over time, requiring the patient to assert more control over his or her own movement. As the authority of the exoskeleton is reduced, the patient will have to increase his or her own authority and develop his or her own control law or the patient will become less stable and eventually unbalanced. We expect this treatment method will increase the stability of patients, allowing them to steadily adapt to standing and walking. This will then allow them mobility without the use of a wheel chair and decrease their risk of falling. Further, the use of this device will enable the patients to receive therapy at home and in their normal life without the need to visit a physical therapist for rehabilitation, enabling the patients to receive therapy at home and for a longer period of time than they currently do. / Master of Science

In this study, we assess the robustness of four distinct control approaches: pole placement; the command generator tracker (CGT) approach to model reference control; model reference adaptive control (MRAC); and MRAC using a fixed feedback gain. We use a second order, single-input single-output (SISO) plant to examine the performance and stability of each method. This evaluation spans a broad range of design goals and uncertainty in models of the plant. Pole placement and CGT designs are linear and relatively easy to implement, but require explicit knowledge of the plant. Although MRAC schemes require little knowledge of the plant's dynamic characteristics, such algorithms are non-linear and involve design variables whose effects are not readily apparent. Currently, there are no general design procedures for MRAC. In this study, we propose a method for designing an MRAC controller applied to a second order SIS a plant. This method does not require the controller to be tuned for different closed-loop performance goals. This procedure also creates a consistent basis for comparing the robustness of all four algorithms. Pole placement and the CGT control perform as designed if the plant is modeled correctly. Under this circumstance, the adaptive controllers also perform at levels equivalent to the linear algorithms. However, conditions with plant modeling error highlight enormous differences among the four algorithms. Pole placement suffers the largest response error and for extreme testing conditions, instability. The CGT controller exhibits better performance than pole placement and remains stable over all testing variables. NIRAC maintains a high performance level under severe testing conditions. MRAC requires minimal plant knowledge to guarantee stability and good performance. / Master of Science

Master of Science / Department of Mechanical and Nuclear Engineering / Warren N. White / The objective of this research was to show that controls demonstrations and education can be greatly improved with the use of Web 2.0 tools. First, a user-centered and collaborative website was developed using the freely available Web 2.0 tools. Then procedures for creating animations using control system simulations were developed. Using the Java programming language, interactive graphs were constructed for display to allow the viewer to change the initial conditions of the controls system and plot the results of the simulation as calculated. These animations and interactive graphs used already developed MatLab resources. Using Web 2.0 tools, the collaborative web site can be easily updated by several people simultaneously, only requiring access to the internet. Because of these advantages, collaboration between multiple universities and controls researchers in distant locations is possible, and the new website has the potential of becoming the center of controls research around the world. More importantly, the procedure allows future systems to be demonstrated while requiring minimal additional work, thereby increasing the universities' ability to educate their students, as well as the general public, about controls system research.

International Telemetering Conference Proceedings / October 25-28, 1993 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Pulse Code Modulation (PCM) data systems are used extensively in testing aircraft all over the world. These systems can be tailored to almost any set of measurement requirements using flexible, modular equipment available from several sources. This paper describes a system assembled from readily available components manufactured in the United States that is being used to certify a Russian aircraft flying in The Commonwealth of Independent States. The system features distributed data acquisition, programmable signal conditioning and PCM encoding modules, multi-channel temperature and pressure scanners and real time data displays on board the aircraft. The impact of U.S. export controls and our experience to date is also discussed.

The automotive industry is required to meet improved fuel efficiency standards and stricter emission controls. Aluminum tube hydroforming is particularly well suited in meeting the goals of lighter, more fuel-efficient and less polluting cars. Its wider use in industry is hindered however by the reduced ductility and more complex constitutive behavior of aluminum in comparison to the steels that it is meant to replace. This study aims to address these issues by improving the understanding of the limitations of the process as applied to aluminum alloys. A series of hydroforming experiments were conducted in a custom testing facility, designed and constructed for the purposes of this project. At the same time, several levels of modeling of the process, of increasing complexity, were developed. A comparison of these models to the experiments revealed a serious deficiency in predicting burst, which was found experimentally to be one of the main limiting factors of the process. This discrepancy between theory and experiment was linked to the adoption of the von Mises yield function for the material at hand. This prompted a separate study, combining experiments and analysis, to calibrate alternative, non-quadratic anisotropic yield functions and assess their performance in predicting burst. The experiments involved testing tubes under combined internal pressure and axial load to failure using various proportional and non-proportional loading paths (free inflation). A number of state of the art yield functions were then implemented in numerical models of these experiments and calibrated to reproduce the induced strain paths and failure strains. The constitutive models were subsequently employed in the finite element models of the hydroforming experiments. The results demonstrate that localized wall thinning in the presence of contact, as it occurs in hydroforming as well as other sheet metal forming problems, is a fully 3D process requiring appropriate modeling with solid elements. This success also required the use of non-quadratic yield functions in the constitutive modeling, although the anisotropy present did not play as profound a role as it did in the simulation of the free inflation experiments. In addition, corresponding shell element calculations were deficient in capturing this type of localization that precipitates failure, irrespective of the sophistication of the constitutive model adopted. This finding contradicts current practice in modeling of sheet metal forming, where the thin-walled assumption is customarily adopted. / text