Higher-Order Localization Relationships Using the MKS Approach Tony Fast
Presentation on a parallelizable, effective models technique to replace costly simulation techniques (e.g. Finite Element Models or Phase Field Simulation). This presentation was given at the ASME 2011 Applied Mechanics and Materials Conference In Chicago, IL.
Data Science Solutions by Materials Scientists: The Early Case StudiesTony Fast
Improvements in algorithms, technology, and computation are directly impacting the landscape of information use in materials science. The 3 V’s of Big Data (volume, velocity, and variety) are becoming evermore apparent within all sectors of the field. Novel approaches will be required to confront the emerging data deluge and extract the richest knowledge from simulated and empirical information in complex evolving 3-D spaces. Microstructure Informatics (μInformatics) is an emerging suite of signal processing techniques, advanced statistical tools, and data science methods tailored specifically for this new frontier. μInformatics curates and transforms large collections of materials science information using efficient workflows to extract knowledge of bi-directional structure-property/processing connections for most material classes.
In this talk, a few early case studies in data-driven methods to solve materials science problems will be explored. Emerging spatial statistics tools will be explored that enable an objective comparison of static and evolving 3-D material volumes from molecular dynamics simulation, micro-CT, and Scanning Electron Microscopy. Also, the statistics will provide a foundation to create improved bottom-up homogenization relationships in fuel cell materials. Lastly, applications of the Materials Knowledge System, a data-driven meta-model to create top-down localization relationships will be explored for phase field model and finite element model information.
Dream3D and its Extension to Abaqus Input FilesMatthew Priddy
This presentation is an overview of our current usage of Dream3D for generating digital microstructures from 2D EBSD scan data, particularly grain size distribution, misorientation distribution, and pole figures.
This presentation also mentions our plan for harnessing the Dream3D output formats to generate Abaqus input files (.inp).
A talk for the Institute of Data Analytics and High Performance Computing Chalk and Talk lunch series on Thursday April 25, 2014.
This high level talk discusses materials science on the grounds of the information that drive new discoveries in materials science. Understanding the nature of the data that encompasses the landscape of materials science is important for the next generation workforce and the emerging discipline of Materials Data Scientist
Higher-Order Localization Relationships Using the MKS Approach Tony Fast
Presentation on a parallelizable, effective models technique to replace costly simulation techniques (e.g. Finite Element Models or Phase Field Simulation). This presentation was given at the ASME 2011 Applied Mechanics and Materials Conference In Chicago, IL.
Data Science Solutions by Materials Scientists: The Early Case StudiesTony Fast
Improvements in algorithms, technology, and computation are directly impacting the landscape of information use in materials science. The 3 V’s of Big Data (volume, velocity, and variety) are becoming evermore apparent within all sectors of the field. Novel approaches will be required to confront the emerging data deluge and extract the richest knowledge from simulated and empirical information in complex evolving 3-D spaces. Microstructure Informatics (μInformatics) is an emerging suite of signal processing techniques, advanced statistical tools, and data science methods tailored specifically for this new frontier. μInformatics curates and transforms large collections of materials science information using efficient workflows to extract knowledge of bi-directional structure-property/processing connections for most material classes.
In this talk, a few early case studies in data-driven methods to solve materials science problems will be explored. Emerging spatial statistics tools will be explored that enable an objective comparison of static and evolving 3-D material volumes from molecular dynamics simulation, micro-CT, and Scanning Electron Microscopy. Also, the statistics will provide a foundation to create improved bottom-up homogenization relationships in fuel cell materials. Lastly, applications of the Materials Knowledge System, a data-driven meta-model to create top-down localization relationships will be explored for phase field model and finite element model information.
Dream3D and its Extension to Abaqus Input FilesMatthew Priddy
This presentation is an overview of our current usage of Dream3D for generating digital microstructures from 2D EBSD scan data, particularly grain size distribution, misorientation distribution, and pole figures.
This presentation also mentions our plan for harnessing the Dream3D output formats to generate Abaqus input files (.inp).
A talk for the Institute of Data Analytics and High Performance Computing Chalk and Talk lunch series on Thursday April 25, 2014.
This high level talk discusses materials science on the grounds of the information that drive new discoveries in materials science. Understanding the nature of the data that encompasses the landscape of materials science is important for the next generation workforce and the emerging discipline of Materials Data Scientist
