2022 WSU Annual CGRS Abstracts

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    Design and synthesis of bismuth sulfide and exploring its application as a photo electrodematerial in third generation solar cells
    (Wichita State University, 3/29/2022) Saket, Mathur; Wei, Wei
    Solar energy has become one of the major sources of renewable energy and is a viable economic option in areas which receive a large amount of sunlight around the year, such as the state of Kansas. However, it currently relies on ultra-pure silicon ingots to produce commercial silicon photovoltaics, which prevents the cost of electricity being produced to compete with nonrenewable energy production. A viable low cost alternative for silicon based cells would be dyesensitized solar cells (DSSC), which are easier and cheaper to manufacture as they do not require expensive and delicate raw materials to make, while they could be made semi-flexible which allows for a greater variety of applications for these cells. A DSSC consists three components, a photoelectrode, an electrolyte and a counter-electrode. When exposed to incident light, the photoelectrode releases an electron which is transported to the external load, leaving the photoelectrode in an oxidized state. The electrons are collected by the counter electrode and used to reduce the electrolyte. This charged electrolyte then reduces the positively charged photoelectrode, allowing the process to begin again. To improve the efficiency of this process, we explore the use of Bismuth Sulfide and Titanium Oxide composite as photo-electrode material by testing it in varying ratios and studying their impact on the efficiency of DSSC.
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    Small scale energy devices using vortex induced vibration
    (Wichita State University, 3/29/2022) Matheswaran, Vijay; Miller, L. Scott
    Small-scale off-grid energy devices are an increasingly important part of the energy mix today, as seen in small solar panels and micro wind turbines that power road signs or heat livestock water troughs. Solar panels are the most commonly used solutions. However, a device that uses Vortex Induced Vibration (VIV) as its basis can provide a low-cost alternative. Flow of air around a bluff body leads to vortex shedding in its wake. Asymmetric shedding of vortices can result in oscillatory forces on the body, and cause large amplitude oscillations (VIV). Vortex shedding frequency and oscillations amplitude is primarily dependent on body geometry and flow velocity. In this study, the design methodology for a device that extracts energy from VIV is presented. A semi-empirical model is developed to predict shedding frequency and forces due to vortex shedding for the canonical case of flow around a circular cylinder. Shedding behavior of different geometries is related to that of a cylinder through conformal mapping. In this manner, forces due to vortex shedding for various geometries and their applicability in energy devices can be quickly predicted. Validation is done through water table and wind tunnel tests. Emphasis is laid on ensuring the device is low-cost and constructed from readily available or repurposed material, and require no specialized knowledge to maintain. Such a device can find use in rural communities and regions throughout Kansas. Wichita
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    Computer vision techniques for fire detection and localization
    (Wichita State University, 3/29/2022) Haridasan, Smitha; Rattani, Ajita
    From droughts, earthquakes, tornadoes, winter storms and wildfires, communities in Kansas have weathered significant damage over the past. During 2016, 2017 and 2021, record breaking wildfires burned thousands of acres in Kansas and placed significant demands on state's local fire department. In December 2021, Four County Fire had burned an area approximately close to 96,000 acres. Strong winds in Kansas made these wildfires uncontrollable burning down houses and businesses on its path. Strikes, arson, sparks from vehicles, or prescribed burns escaping control are causes for wildfires to burn down houses, barns and fences resulting in both human and animal deaths. Many wildfires remain small and are easily contained, but some grow rapidly and require significant suppression efforts and resources. While fire fighters try to control fast spreading fires, smoke travels miles causing health concerns. Windstorm and wildfires cause millions worth of damage in Kansas. As global climate gets warmer, probability and intensity of forest fires will gradually increase, therefore it is important to intelligently monitor forest fires. To meet the needs of hazard monitoring drones and helicopters, multi-spectral light weight deep learning algorithms have proven to be very effective in early detection of fire in images captured from drones with an accuracy of 97.70%.
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    Neural network assisted trajectory planning for space missions
    (Wichita State University, 3/29/2022) Dasyam, Amrutha; Chadalavada, Pardhasai; Dutta, Atri
    A critical aspect of space mission analysis is spacecraft trajectory optimization, which is a challenging problem involving nonlinear dynamics, multiple phases, nonconvex objectives, and complex constraints. State-of-the-art trajectory optimization solvers are primarily meant for use by personnel on the ground; however, onboard trajectory planning capability can enhance mission flexibility and responsiveness to uncertain situations. Our research focuses on applying machine learning techniques to improve the performance of our in-house trajectory planning tool on two fronts: (1) accurate prediction of atmospheric density for Mars aerobraking maneuvers, and (2) improvement of quality of orbit-raising trajectories to Geostationary Earth Orbit (GEO). These applications are important for reducing the cost of space missions through significant reduction of fuel expenditure, which in turn allows for stacking multiple satellites in a single launch vehicle and lowering launch costs. Consequently, given new emphasis on GEO applications (GOES-T mission enhancing tornado warning lead time and GeoCarb mission monitoring vegetation stress), the benefits of mission cost reduction are important for Kansas. Additionally, recent years have witnessed an enhanced involvement of private industry (notably SpaceX, Boeing, Lockheed Martin and Blue Origin) in near-Earth and deep space missions. This also means new business opportunities for Kansas companies that already have a strong aeronautical infrastructure. In this context, our research on mission planning for spacecraft with solar-electric propulsion has provided a new platform for engaging Kansas stakeholders (multiple universities) with NASA and private industry. Wichita
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    The relationship between preference and performance using three passive exoskeletons during simulated aircraft manufacturing tasks
    (Wichita State University, 3/29/2022) Alqahtani, Haifa; Jorgensen, Michael J.; Jaeger, Adam; Hakansson, Nils A.
    Work-related musculoskeletal disorders (WMSDs) are the top workplace risk factors that impact the health of workers. In Kansas, there were 45,253 reported injuries/illnesses during the 2020 fiscal year. The main contributors to shoulder WMSDs are lifting one’s arms and handling heavy tools at or above shoulder level. Passive shoulder exoskeletons are designed to support the arms during overhead work tasks and may aid in reducing the risk of WMSDs. However, exoskeletons are only effective if workers choose to wear them. Therefore, the objectives of this study were to quantify participants’ upper-extremity muscle activity reductions as participants performed simulated aircraft manufacturing tasks using three passive exoskeletons and assess correlations between the exoskeleton efficacy and user exoskeleton preferences. To fulfill these objectives, 16 experienced local aircraft manufacturers were recruited to participate in the study. A wireless electromyography (EMG) system was used to record muscle activity levels as the participants performed the simulated work tasks with the exoskeletons. The muscle activity and exoskeleton preference data were analyzed using a multinomial logistic regression model to identify the relationship between participants’ muscle activity reduction and exoskeleton preference rankings. The results indicate that the exoskeleton preferences correlated with muscle activity reductions for an overhead level task, but not for a shoulder-level task. Overall, participants preferred the exoskeleton that provided the least reduction in muscle activity. This study demonstrated that a correlation between preference and exoskeleton muscle reduction is task dependent, and, therefore, task factors in addition to user preference should be considered in exoskeleton selection.