Physics-informed neural initialization for robust multi-fidelity coupled simulation of advanced propulsion systems

Key Points

• Robustness in coupled simulation of propulsion systems is achieved through neural network initialization.
• Key evidence shows a significant improvement in accuracy by utilizing multi-fidelity data.
• The approach involves physics-informed neural networks to enhance simulations across different fidelity levels.
• Highlighting the need for further exploration in advanced propulsion models with external validation.