Novel wind-energy harvesting device
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Throughout the winter and spring of 2024, I developed an understanding of the electrical and aerospace science behind the normal oscillatory wind energy harvesting device. I began by preparing several presentations to document the initial system design ideas that I derived both independently and conjointly with Dr. Masroor. In these presentations, I also recorded independently researched topics such as Strouhal numbers, piezoelectric materials, Faraday’s Law, and ViscousFlow. For instance, for a few weeks at the end of last semester, I simulated fluid flow around various simple shapes and analyzed the resultant vortex-shedding patterns like the ones in the figure to the right. I also used Faraday’s Law to predict induced voltage as a function of the frequency with which a neodymium magnet oscillates linearly through a coil of various turn lengths (N). After returning from winter break, Dr. Masroor and I continued brainstorming designs to test in a wind tunnel. Simultaneously, I began creating three-dimensional CAD models that we could use to simulate magnet oscillations through a coil. I built a variation of the scotch-yoke mechanism to power a linear oscillator using a motor whose frequency we varied using an Arduino Motor Shield. I then used MATLAB in tandem with Arduino to convert my laptop into a makeshift oscilloscope which we used to record electromagnetically induced voltage over time as the magnet oscillated through the coil. We then swapped the coil’s position for the magnet’s and oscillated the coil around the fixed magnet, which allowed us to create faster oscillations using less power. I then spent several weeks gathering voltage/time data for dozens of frequency-amplitude combinations to analyze the relationship between voltage, amplitude, and oscillatory frequency–which affects magnetic flux (Φ). I then created a MATLAB data analysis script with which I ran a Fourier Transform to extract the frequency compositions from the time series data and ultimately clean the data. After cleaning the data’s noise, I found the dominant electrical frequency, which corresponded to the coil’s oscillation frequency. I then used the relationship between power and resistance to determine the approximate power from the system (we previously measured the coil’s resistance to be approximately 3𝛀). I then used this script to create a heatmap-type table–albeit very coarse–of power as a function of frequency and amplitude. For the final weeks of the spring semester, I attended wind tunnel experiments during which our group attempted to achieve oscillatory motion from various cylinder-spring combinations.