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OpenOAT: A Massive Large Minimum Compliance Topology Optimization Dataset
OpenOAT is a dataset of random FEA problems solved using a SIMP optimizer and includes fully random resolution and aspect ratio problems. The dataset has three parts:
- Pre-Training Data: 2M sample topologies without labeled boundary condition and loads.
- Labeled Data: 700K samples(also in the pre-training) with labeled boundary conditions and loads and volume fraction:
- Test Data: 15K labeled samples not present in either prior datasets for testing.
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