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Abstract
OOF is designed to help materials scientists calculate macroscopic properties from images of real or simulated microstructures. It reads an image, assigns material properties to features in the image, and conducts virtual experiments to determine the macroscopic properties of the microstructure.
OOF3D generalizes the popular but two-dimensional OOF2 to three dimensions, using a stack of 2D images to create a three dimensional microstructure. It includes a basic subset of the features of OOF2.
The programs are written in C++ and Python and benefit from an object-oriented design. The underlying numerical solutions rely on finite element technology. Hence the name OOF, for object-oriented finite element analysis.
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python, C++, swig
Credits
Principal Developers
Steve Langer
Applied and Computational Mathematics Division
Information Technology Laboratory
NIST
Andrew Reid
Materials Science and Engineering Division
Material Measurement Laboratory
NIST
Günay Doğan
Applied and Computational Mathematics Division
Information Technology Laboratory
NIST
R. Edwin García
School of Materials Engineering
Purdue University
Developers Emeritus
Yannick Congo
Applied and Computational Mathematics Division
Information Technology Laboratory
NIST
Valerie R. Coffman
Applied and Computational Mathematics Division
Information Technology Laboratory
NIST
Rhonald Lua
Department of Materials Science and Engineering
Penn State University
NIST MSEL guest researcher
Seung-Ill Haan
Department of Mechanical Engineering
University of Maryland, Baltimore County
NIST CTCMS guest researcher
Andy Roosen
Materials Science and Engineering Laboratory
NIST
Students
Lucianna Kiffer
Tulane University
NIST SURF program
Kyle Stemen
Kent State University
NIST SURF program
Olga Kuznetsova
University of Maryland
NIST SURF program
Daniel Vlacich
Kang-Xing Jin
Kevin Chang
Eric Ma Science Magnet Program
Montgomery Blair High School
Silver Spring, MD
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Submitter
Purdue University