Physics Guided Neural Networks Based Model for Predicting Cycloidal Rotor Performance

What is it about?

In this paper, a novel Physics-Guided Neural Network (PGNN) has been developed which can predict the cyclorotor academic performance such as thrust and power. This model combines with machine learning and physics based aerodynamic model where physics guided information was incorporated into a Neural Network architecture. This PGNN model can accurately predict the cyclorotor performance. This study compares this approach with conventional Neural Network and physics based aerodynamic model to show its superior performance.

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