Fast Neural Network Predictions from Constrained Aerodynamics Datasets

@inproceedings{White2019FastNN,
  title={Fast Neural Network Predictions from Constrained Aerodynamics Datasets},
  author={Cristina White and D. Ushizima and C. Farhat},
  year={2019}
}
  • Cristina White, D. Ushizima, C. Farhat
  • Published 2019
  • Mathematics, Physics, Computer Science
  • Incorporating computational fluid dynamics in the design process of jets, spacecraft, or gas turbine engines is often challenged by the required computational resources and simulation time, which depend on the chosen physics-based computational models and grid resolutions. An ongoing problem in the field is how to simulate these systems faster but with sufficient accuracy. While many approaches involve simplified models of the underlying physics, others are model-free and make predictions based… CONTINUE READING
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