Three models have been created to visualize and characterize the voltage response of a standing wave accelerating cavity system. These models are generalized to fit any cavity with known values of the quality factor, coupling factor, and resonant frequency but were applied to the Arizona State Universities Compact X-ray Free Electron Laser. To model these systems efficiently, baseband I and Q measurements were used to eliminate the modeling of high frequencies. The three models discussed in this paper include a single standing wave cavity, two cavities coupled through a 3dB quadrature hybrid, and a pulse compression system. The second model on two coupled cavities will demonstrate how detuning will impact two cavities with the same RF source split through a hybrid. The pulse compression model will be used to demonstrate the impact of feeding pulse compression into a standing wave cavity. The pulse compressor will demonstrate more than a 50\% increase of the voltage inside the cavity.

We present in this paper a method to compare scene classification accuracy of C-band Synthetic aperture radar (SAR) and optical images utilizing both classical and quantum computing algorithms. This REU study uses data from the Sentinel satellite. The dataset contains (i) synthetic aperture radar images collected from the Sentinel-1 satellite and (ii) optical images for the same area as the SAR images collected from the Sentinel-2 satellite. We utilize classical neural networks to classify four classes of images. We then use Quantum Convolutional Neural Networks and deep learning techniques to take advantage of machine learning to help the system train, learn, and identify at a higher classification accuracy. A hybrid Quantum-classical model that is trained on the Sentinel1-2 dataset is proposed, and the performance is then compared against the classical in terms of classification accuracy.

My honors thesis took the form of a creative project. My final deliverables are my research presentation (pdf attachment) and solar powered electric scooter (image attachment). The goal of my project was to fix a second-hand electric scooter and create a solar-powered charger for its battery. The research portion of my creative project focused on exploring the circuit elements in a solar charging schematic and their relationships to power output. First, I explored methods of maximizing power output of the basic solar charging schematic. To find the maximum power output based on different settings of photocurrent (sunlight), I wrote a MATLAB code to calculate maximum power based on its derivative with respect to voltage set equal to zero. Finding this maximum power point in MATLAB allowed me to find its corresponding current and voltage output to produce that exact power. With these max current and voltage values, I was able to solve for an ideal resistor value to set in series with the solar panel in order to achieve these values. In doing so, I designed a maximum power point tracker (MPPT). This became an essential component in my charger’s final design. Next, I explored the microcircuit level of a solar panel schematic. In order to do so, I had to break my single diode model into several diodes in series, resulting in the overall solar panel voltage drop (aka the voltage rating of the solar panel) being divided N times. To find what this N value for a given solar panel is, I performed a lab experiment using a small solar panel and a floodlight to gather the panel’s turn on current and open circuit voltage. These two values helped me find the solar panel’s N value after linearizing the lab data. Now, with a much deeper understanding of solar charging circuitry, I was able to move forward with the design and implementation phase. The design and implementation portion of my creative project included the physical assembly of the solar-powered scooter. First, I analyzed the efficiency differences between having an AC coupled vs. DC coupled system. Due to the added complexity of AC conversions, I deemed it unnecessary to use an inverter in the charger. The charging schematic I designed only called for a charge controller and MPPT, both parts that could easily DC couple the system. Keeping the system in DC from solar panel to battery was definitely the most efficient method, so DC coupling was my final selection. Next, I calculated the required current and voltage output of my charger to meet the specs of the battery and the requirements I set for my project. Finally, I designed a solar array based on these ratings. The final design includes one 30 W panel in parallel with two series-connected 5W panels. The two series panels are affixed on the scooter neck for a built in charge design so that the scooter can be charged anywhere (outside while not in use). The big panel can be connected using a parallel branch in the charging cord that I spliced for added current if charging is set up in a stationary setting (by a window at home). The final design serves the need for sustainable micro mobility in a daily 50% depletion use case kept above 20% charged at all times.

This project explores the optimization of HVAC and renewable energy systems of new, modular and portable off grid systems like the Recycling Microfactory, a joint project between Arizona State University and the Department of Defense (DOD). There has been a growing push for innovative solutions to address the underlying deficiencies in United States supply chains and energy infrastructure. This paper seeks to elaborate on the proposed solutions of portable and modular infrastructure to support neglected sectors of the economy: energy grid modernization and waste management specifically. This will be done by analyzing the Microfactory’s operations and optimizing the site’s energy efficiency. Background knowledge and context behind the current state of supply chains and of both energy and waste management sectors are briefly explained in the introduction followed by a high-level overview of the concept of modular infrastructure such as the Recycling Microfactory. The body of the thesis is organized into two sections. The first section focuses on the methods for planning the structure, layout, and workflow of the Recycling Microfactory for when it is out for transport and organized for operation. A series of 3D parametric models were used for the high-fidelity layouts of the Microfactory and was developed in conjunction with user experience gained from evaluating the custom-built processing equipment. The second section further expands the initial energy simulation models of the Microfactory generated from the first simulations of the project. Utilizing the building energy modeling (BEM) software EnergyPlus/OpenStudio, more advanced models accounting for HVAC sizing requirements, climate building standards (i.e., building insulation), and human comfort standards for workspaces are generated. A more realistic simulation of the energy requirements of the Microfactory to maintain temperature and humidity standards is presented through a comprehensive review of the OpenStudio building model design flow.

This project seeks to mitigate the reduced video quality from data compression due to bandwidth limits, which hinders the transmission of emotional information. The project applies selective compression to a prerecorded video to produce a modified video that compresses the background and preserves important emotional information. The effect of this selective compression was assessed through data collection of user emotional and visual response. The final goal was to publish a paper summarizing the conclusions drawn from all of the lab data that was collected.