lamm-mit/FieldCompleter

GAN/convolutional and Transformer models to predict missing mechanical information given limited known data in part of the domain, and further characterize the composite geometries from the recovered mechanical fields for 2D and 3D complex microstructures

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Experimental

This project helps materials engineers and scientists analyze complex microstructures even when mechanical field data is incomplete. You input partial 2D or 3D mechanical field measurements, such as stress or strain, and it outputs a complete map of the physical field, along with a characterization of the underlying composite geometry. This allows for efficient material design and analysis, especially when only boundary information is available.

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Use this if you need to understand the full mechanical behavior and internal structure of materials from limited or partial measurement data, particularly in complex 2D or 3D microstructures.

Not ideal if you have complete mechanical field data or are working with simple, homogeneous materials where traditional analysis methods suffice.

materials-science mechanical-engineering materials-characterization microstructure-analysis inverse-design
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 15 / 25

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Language

Python

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Last pushed

Apr 23, 2023

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