2d microstructure datadoi:10.18419/darus-1151DaRUS2020-11-192Lißner, Julian, 2020, "2d microstructure data", https://doi.org/10.18419/darus-1151, DaRUS, V22d microstructure datadoi:10.18419/darus-1151Lißner, JulianDaRUSLißner, JulianFelix FritzenLißner, Julian2021-02-08Computer and Information ScienceEngineeringmicrostructurerepresentative volume element (RVE)homogenizationeffective propertiesregressionThe hdf5 file contains image data of inclusion based microstructured material and the homogenized effective heat conductivity thereof. The microstructure is defined with a representative volume element with periodic boundary conditions.
30.000 images are contained and split into two inclusion subclasses of circular and rectangular inclusions.
Features computed via the 2-point correlation function can be found. The features and effective properties have been used for a regression problem in the related paper. Example code to access the data and recreate the features is attached.<a href="https://github.com/J-lissner/image-property-linkage">Surrogate model - application GUI</a> [100 MiB]Lißner, Julian, and Felix Fritzen. "Data-Driven Microstructure Property Relations." Mathematical and Computational Applications 24.2 (2019): 57.10.3390/mca24020057Lißner, Julian, and Felix Fritzen. "Data-Driven Microstructure Property Relations." Mathematical and Computational Applications 24.2 (2019): 57.2d_microstructures.h5hdf5 file containing all the dataapplication/x-h5compute_regression_data.pycode to recompute/reproduce the data used for the regression problemtext/x-pythonexample_data_access.pyan example on how to access data stored in the hdf5 filetext/x-pythonprocessing_functions.pydependency file for 'compute_regression_data.py'text/x-python