Center for Industrial Mathematics and Statistics » REU 2019

Julianna Bernardi

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Vincent Filardi

Malorie Finch

Tanvi Shinkre

Jeffrey Zhang

Overview

Industrial Sponsor: General Electric Aviation

Industrial Liaisons: Dr. Ming Fu

Faculty Advisors: Randy Paffenroth, Burt S. Tilley

Our project with General Electric Aviation focused on extracting the features of materials data that were most critical to the overall wear of the materials. We wished to predict specific properties of materials based on existing data. We employed predictive analysis to find trends among the deepest and average block and shoe wear. The features focused on in the analysis were the base alloy families, ambient target temperature, contact stress target, initial sliding friction coefficient, stroke, initial driver load, and total cycles. After much collaboration and analysis, we constructed models to predict the most effective and efficient material combinations and provided more insight on future experimental procedures.