Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. This workflow consists of four main steps:...

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Veröffentlicht in:	Integrating materials and manufacturing innovation 2017-03, Vol.6 (1), p.54-68
Hauptverfasser:	Popova, Evdokia, Rodgers, Theron M., Gong, Xinyi, Cecen, Ahmet, Madison, Jonathan D., Kalidindi, Surya R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Additive manufacturing Additives Analysis Characterization and Evaluation of Materials Chemistry and Materials Science Communities Computer simulation Data science Datasets Evolution Informatics Knowledge Laboratories Linkages MATERIALS SCIENCE MATHEMATICS AND COMPUTING Metallic Materials Microstructure microstructure quantification Monte Carlo simulation Nanotechnology Process parameters PSP linkages Structural Materials Studies Surfaces and Interfaces Thin Films Workflow Workflow software workflows
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