DSO: Dual-Scale Neural Operators for Stable Long-term Fluid Dynamics Forecasting

1. 1Identify the limitations of existing neural operator architectures in fluid dynamics forecasting
2. 2Develop a dual-scale approach to capture both fine-scale and large-scale structures
3. 3Implement the DSO model to mitigate local detail blurring and spectral leakage
4. 4Evaluate the performance of DSO in long-term fluid dynamics forecasting tasks

Researchers and engineers working on fluid dynamics and neural operator models can benefit from DSO, as it enhances the accuracy and stability of long-term forecasts

💡 DSO improves long-term stability and precision in fluid dynamics forecasting by addressing local detail blurring and spectral leakage

💡 DSO: Dual-Scale Neural Operators for stable long-term fluid dynamics forecasting