pcdgan/PcDGAN
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design
This project helps engineers and researchers generate new designs, like airfoil shapes, that meet specific performance criteria. It takes existing design data and desired performance attributes as input, then outputs novel designs tailored to those specifications. This is ideal for those involved in material science, aerospace design, or any field requiring the inverse design of complex structures.
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Use this if you need to generate diverse and high-performing designs based on desired characteristics, rather than just optimizing existing designs.
Not ideal if you are looking for a simple optimization tool or if you do not have existing data to train the generative models.
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30
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8
Language
Python
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Last pushed
Feb 11, 2021
Commits (30d)
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