Interface Effects of the Properties and Processing of Graded Composite Aluminum Alloys
Abstract
The objective of this STIR program was to utilize a data-analytics approach to predict the performance of an architecturally graded aluminum composite with a diffuse interface between alloys 5456 and 7055. The program supported the education and training of one graduate student pursuing a Masters of Science degree in Materials Science and Engineering. It was hypothesized that the compositional gradient would be primarily responsible for the performance of the composite system. To test this hypothesis a robust data framework was developed for spatially correlating disparate datasets for composition, microstructure, and hardness. This included open-science protocols for data and metadata collection for energy dispersive X-ray spectrometry (EDS), X-ray photoelectron spectroscopy (XPS), electron backscatter diffraction (EBSD), and microhardness. Structural equation modeling was used to assess the statistical validity of mapping functions that predict performance at a particular position in the compositional gradient. The predictive capabilities of the derived mapping functions were then validated against a second, spatially sparse dataset. The analysis indicated that the large deviation in the hardness measurements made it difficult to produce functional forms that predict performance with R2 values greater than 0.61.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 31, 2015
- Accession Number
- AD1010382
Entities
People
- Jennifer L. Carter
Organizations
- Case Western Reserve University