d5ffba099e
Permanently integrates the Atomizer-Field GNN surrogate system: - neural_models/: Graph Neural Network for FEA field prediction - batch_parser.py: Parse training data from FEA exports - train.py: Neural network training pipeline - predict.py: Inference engine for fast predictions This enables 600x-2200x speedup over traditional FEA by replacing expensive simulations with millisecond neural network predictions. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
11 lines
263 B
Python
11 lines
263 B
Python
"""
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AtomizerField Neural Models Package
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Phase 2: Neural Network Architecture for Field Prediction
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This package contains neural network models for learning complete FEA field results
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from mesh geometry, boundary conditions, and loads.
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"""
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__version__ = "2.0.0"
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