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Computational materials is a field that utilizes modeling, simulations, and technology to study how materials behave. This honors thesis is a presentation discussing computational materials, our study of packing theory using the Monte Carlo (MC), and how our research can be related to real materials we use.
In the last two decades, fantasy sports have grown massively in popularity. Fantasy football in particular is the most popular fantasy sport in the United States. People spend hours upon hours every year building, researching, and perfecting their teams to compete with others for money or bragging rights. One problem, however, is that National Football League (NFL) players are human and will not perform the same as they did last week or last season. Because of this, there is a need to create a machine learning model to help predict when players will have a tough game or when they can perform above average. This report discusses the history and science of fantasy football, gathering large amounts of player data, manipulating the information to create more insightful data points, creating a machine learning model, and how to use this tool in a real-world situation. The initial model created significantly accurate predictions for quarterbacks and running backs but not receivers and tight ends. Improvements significantly increased the accuracy by reducing the mean average error to below one for all positions, resulting in a successful model for all four positions.
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The goal of this experiment was to examine the energy absorption properties of origami-inspired honeycomb and standard honeycomb structures. These structures were 3D printed with two different materials: thermoplastic polyurethane (TPU) and acrylonitrile butadiene styrene (ABS). Quasi-static compression testing was performed on these structures for both types and materials at various wall thicknesses. The energy absorption and other material properties were analyzed for each structure. Overall, the results indicate that origami-inspired structures perform best at energy absorption at a higher wall thickness with a rigid material. The results also indicated that standard honeycomb structures perform better with lower wall thickness, and also perform better with a rigid, rather than a flexible material. Additionally, it was observed that a flexible material, like TPU, better demonstrates the folding and recovery properties of origami-inspired structures. The results of this experiment have applications wherever honeycomb structures are used, mostly on aircraft and spacecraft. In vehicles with structures of a sufficiently high wall thickness with a rigid material, origami-inspired honeycomb structures could be used instead of current honeycomb structures in order to better protect the passengers or payload through improved energy absorption.
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