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Full-Text Articles in Engineering
Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy
Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy
College of Engineering Summer Undergraduate Research Program
High-entropy alloys (HEA) are a very new development in the field of metallurgical materials. They are made up of multiple principle atoms unlike traditional alloys, which contributes to their high configurational entropy. The microstructure and properties of HEAs are are not well predicted with the models developed for more common engineering alloys, and there is not enough data available on HEAs to fully represent the complex behavior of these alloys. To that end, we explore how the use of machine learning models can be used to model the complex, high dimensional behavior in the HEA composition space. Based on our …
Characterization Of Ground Albedo Materials For Bifacial Solar Farms, Fernanda De Los Angeles Garcia, Benny Tam, Jean Lee, James Vance
Characterization Of Ground Albedo Materials For Bifacial Solar Farms, Fernanda De Los Angeles Garcia, Benny Tam, Jean Lee, James Vance
College of Engineering Summer Undergraduate Research Program
Bifacial photovoltaics can collect solar energy from both sides, unlike regular one-sided solar panels. With the ability to collect energy from both sides, the energy production of bifacial photovoltaic farms is about 2-6% more efficient than typical solar farms. However, the increase in efficiency is highly dependent on the reflectivity of the ground material. This project explores six different materials to determine which material would be best to implement as a ground material for a bifacial photovoltaic farm, based on their mechanical properties and albedo value. Albedo refers to the ratio between the reflected solar radiation to the incident solar …
Additive Manufacturing For Medical Education, Michael Noon
Additive Manufacturing For Medical Education, Michael Noon
College of Engineering Summer Undergraduate Research Program
A growing body of evidence is suggesting that anatomical knowledge, the keystone of many medical specialties, is suffering among new graduates. While a host of reasons are provided, one common thread that many point to is the decline of cadaver dissections in the classroom. Many virtual audio-visual tools are used to address this gap, yet evidence has shown their ineffectiveness. Given this gap, the high degree of flexibility found in additive manufacturing (AM), and the many uses AM has already found in the medical field, we propose its use to fill this gap, allowing for students to learn with touch …