Barrett

Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Pumping Technologies for Additive Manufacturing Processes Using Chocolate

Description

Working with chocolate is a difficult endeavor. However, through the use of additive manufacturing technologies, the labor involved can be reduced. One difficulty is the pumping of the melted chocolate through the system onto the print bed of the printer. In this paper, three systems of transferring chocolate are investigated:…

Working with chocolate is a difficult endeavor. However, through the use of additive manufacturing technologies, the labor involved can be reduced. One difficulty is the pumping of the melted chocolate through the system onto the print bed of the printer. In this paper, three systems of transferring chocolate are investigated: A syringe system, a gear pump system, and an auger system. Each system is explained with a model of the proposed system and the pros and cons are discussed. Lastly, a system composed of parts of the syringe and auger system is proposed. The positive and negative aspects of this design are discussed, and a 3D model of the system is given as well. This system is suggested as a better option, and future research can be done to investigate and rate these systems in greater detail. In commercial food applications, these technologies can change the way chocolate is manipulated, and difficult practices can be simplified for home chefs.
ContributorsMester, Daniel (Author) / Chen, Xiangfan (Thesis director) / Gintz, Jerry (Committee member) / College of Integrative Sciences and Arts (Contributor, Contributor) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Capillary Action in Additive Manufactured Channels for Thermal Management

Description

Due to the vast increase in processing power and energy usage in computing, a need for greater heat dissipation is prevalent. With numerous applications demanding cheaper and more efficient options for thermal management, new technology must be employed. Through the use of additive manufacturing, designs and structures can be created…

Due to the vast increase in processing power and energy usage in computing, a need for greater heat dissipation is prevalent. With numerous applications demanding cheaper and more efficient options for thermal management, new technology must be employed. Through the use of additive manufacturing, designs and structures can be created that were not physically possible before without extensive costs. The goal is to design a system that utilizes capillary action, which is the ability for liquids to flow through narrow spaces unassisted. The level of detail required may be achieved with direct metal laser sintering (DMLS) and stereolithography (SLA) 3D printing.
ContributorsFechter, Andrew (Author) / Bhate, Dhruv (Thesis director) / Frank, Daniel (Committee member) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Surface Pattern Recognition for Image-Based Inference of Mechanical Properties

Description
A key aspect of understanding the behavior of materials and structures is the analysis of how they fail. A key aspect of failure analysis is the discipline of fractography, which identifies features of interest on fracture surfaces with the goal of revealing insights on the nature of defects and microstructure,…

A key aspect of understanding the behavior of materials and structures is the analysis of how they fail. A key aspect of failure analysis is the discipline of fractography, which identifies features of interest on fracture surfaces with the goal of revealing insights on the nature of defects and microstructure, and their interactions with the environment such as loading conditions. While fractography itself is a decades-old science, two aspects drive the need for this research: (i) Fractography remains a specialized domain of materials science where human subjectivity and experience play a large role in accurate determination of fracture modes and their relationship to the loading environment. (ii) Secondly, Additive Manufacturing (AM) is increasingly being used to create critical functional parts, where our understanding of failure mechanisms and how they relate to process and post-process conditions is nascent. Given these two challenges, this thesis conducted work to train convolutional neural network (CNN) models to analyze fracture surfaces in place of human experts and applies this to Inconel 718 specimens fabricated with the Laser Powder Bed Fusion (LPBF) process, as well as to traditional sheet metal specimens of the same alloy. This work intends to expand on previous work utilizing clustering methods through comparison of models developed using both manufacturing processes to demonstrate the effectiveness of the CNN approach, as well as elucidate insights into the nature of fracture modes in additively and traditionally manufactured thin-wall Inconel 718 specimens.
ContributorsVan Handel, Nicole (Author) / Bhate, Dhruv (Thesis director, Committee member) / Guo, Shenghan (Thesis director, Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor) / Dean, W.P. Carey School of Business (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05