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#aerodynamics News & Analysis

2 articles tagged with #aerodynamics. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AINeutralarXiv – CS AI · May 276/10
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FLUIDSPLAT: Reconstructing Physical Fields from Sparse Sensors via Gaussian Primitives

Researchers introduce FLUIDSPLAT, a neural network model that reconstructs continuous flow fields from sparse sensor data using anisotropic Gaussian primitives. The approach provides theoretical guarantees on approximation rates and demonstrates 11-28% error improvements over existing methods across multiple aerodynamic benchmarks.

AIBullisharXiv – CS AI · Mar 36/109
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Data-Free PINNs for Compressible Flows: Mitigating Spectral Bias and Gradient Pathologies via Mach-Guided Scaling and Hybrid Convolutions

Researchers developed a data-free Physics-Informed Neural Network (PINN) that can solve compressible flows around circular cylinders at extreme speeds up to Mach 15. The system uses hybrid convolutions and Mach-guided scaling to overcome traditional limitations and successfully captures shock waves without requiring training data.