Identify Binder (AI)
The separation between solid and pores of a structure, can usually be done using image processing methods during the import of the scanned data sets (see the ImportGeo-Vol user guide for more details). However, the separation of binder from fibers is often not possible, since they have the same gray values in the scan.
With GeoDict's Identify Binder (AI) functionality the binder can be identified and seperated from fibers automatically prior to the identification of separate fibers.
Please refer to the AI approach to identify binder and fibers for more details on the theory.
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Important! Since FiberFind ships with a limited number of neural networks for fiber and binder identification, currently some constraints on the input data exist:
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Note! Besides this user guide, two tutorials showing the possibilities of the AI based FiberFind approach for different application cases are available on the GeoDict Learning Center. The first tutorial, Digital analysis of fibers and binder content of a carbon paper GDL, analyzes a carbon paper gas diffusion layer samples used in proton-exchange membrane fuel cells. It includes provided synchrotron scan data and covers data import, preprocessing, AI-based identification of fibers and binder, and postprocessing of the results. The second tutorial, Digital Analysis of a glass fiber-reinforced polymer and generation of a digital twin, guides you step by step through importing 3D scans of an engine mount, analyzing fiber distribution and mechanical properties using AI-based tools, and post-processing the results. It also shows how to create a statistical digital twin of the microstructure and validate its properties by comparing simulation results with the original scan. |
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