L-SplineFNO: Neural Operator for Irregular Meshes in Engineering
In brief
- L-SplineFNO merges FNO with learnable B-splines to process irregular meshes efficiently.
- It cuts memory and compute by 50% while preserving high accuracy on six 3D benchmarks.
- Enables zero-shot super-resolution and efficient computation of spatial derivatives.
Researchers introduce L-SplineFNO, a neural operator combining an FNO backbone with learnable B-splines to handle irregular meshes in engineering simulations. The model reduces memory and compute requirements while maintaining high accuracy across six 3D benchmarks.
What it changes for you
- Industry & ManufacturingEngineering simulations on complex meshes become faster and less resource-intensive.
- EnergyTokamak models and other large-scale energy systems gain in precision and scalability.
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