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Harnessing Legacy Data to Educate Data-Enabled Structural Materials Engineers

Published online by Cambridge University Press:  24 February 2020

Jennifer L.W. Carter ,
Amit K. Verma  and
Nishan M. Senanayake
Jennifer L.W. Carter*
Affiliation:
Case Western Reserve University, Department of Materials Science and Engineering, Cleveland OH, 44106, USA, jwc137@case.edu
Amit K. Verma
Affiliation:
Case Western Reserve University, Department of Materials Science and Engineering, Cleveland OH, 44106, USA, jwc137@case.edu Carnegie Mellon University, Department of Materials Science and Engineering, Pittsburgh, PA, 15213, USA
Nishan M. Senanayake
Affiliation:
Case Western Reserve University, Department of Materials Science and Engineering, Cleveland OH, 44106, USA, jwc137@case.edu
*
*(Email: jwc137@case.edu)
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Abstract

Data-driven materials design informed by legacy data-sets can enable the education of a new workforce, promote openness of the scientific process in the community, and advance our physical understanding of complex material systems. The performance of structural materials, which are controlled by competing factors of composition, grain size, particle size/distribution, residual strain, cannot be modelled with single-mechanism physics. The design of optimal processing route must account for the coupled nature of the creation of such factors, and requires students to learn machine learning and statistical modelling principles not taught in the conventional undergraduate or graduate level Materials Science and Engineering curricula. Therefore, modified curricula with opportunities for experiential learning are paramount for workforce development. Projects with real-world data provide an opportunity for students to establish fluency in the iterative steps needed to solve relevant scientific and engineering process design questions.

Keywords

educationinformaticsalloysteel
Type
Articles
Information
MRS Advances , Volume 5 , Issue 7: BROADER IMPACT , 2020 , pp. 319 - 327
Copyright
Copyright © Materials Research Society 2020

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