Document Type
Article
Publication Date
1-2-2018
Abstract
Functional graded materials (FGM) allow for reconciliation of conflicting design constraints at different locations in the material. This optimization requires a priori knowledge of how different architectural measures are interdependent and combine to control material performance. In this work, an aluminum FGM was used as a model system to present a new network modeling approach that captures the relationship between design parameters and allows an easy interpretation. The approach, in an un-biased manner, successfully captured the expected relationships and was capable of predicting the hardness as a function of composition.
Keywords
metal design, network models, optimization, functional gradient materials
Publication Title
Integrating Materials and Manufacturing Innovation
Volume
6
Issue
4
First Page
279
Last Page
287
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Verma, Amit K.; French, Roger H.; and Carter, Jennifer L. W., "Physics-Informed Network Models: A Data Science Approach to Metal Design" (2018). Faculty Scholarship. 72.
https://commons.case.edu/facultyworks/72