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.
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.
One answer to the lack of general knowledge for alternative energy and integration topics is seen in the workforce development content Laboratory of Energy and Power Solutions has generated for the past 6 years. LEAPS is a world-changing organization that provides both technical and business solutions in areas of grid modernization, workforce development, and global energy access that facilitates the global transition to a resilient, low-carbon economy. This paper will aim to explain the contributions of David Hobgood, an Arizona State University senior, to LEAPS workforce development content through the course of the Spring 2022 semester. This paper goes into detail on the process of completing this educational content, amplifies key aspect, and presents the results of a two week pilot that presented the generated content.
This study measure the effect of temperature on a neural network's ability to detect and classify solar panel faults. It's well known that temperature negatively affects the power output of solar panels. This has consequences on their output data and our ability to distinguish between conditions via machine learning.
This is a test plan document for Team Aegis' capstone project that has the goal of mitigating single event upsets in NAND flash memory caused by space radiation.
This project examines the dynamics and design of control systems for a rocket in propulsive ascent and descent using a simplified model with motion constrained to a vertical plane. The governing differential equations are analyzed. They are then linearized, after which transfer functions are derived relating controllable input variables to controlled output variables. The effect of changes in various parameters as well as other aspects of the system are examined. Methods for controller design based on the derived transfer functions are discussed. This will include the discussion of control of the final descent and landing of the rocket. Lastly, there is a brief discussion about both the successes and limitations of the model analyzed.