Performance Optimization of Forward-Flight and Lift-Up Phases in a Cycloidal Rotor Using an Active Control Mechanism

摘要

Cycloidal rotors have revealed a noticeable potential to be further enhanced when running at different operating conditions. The present work demonstrates the active control methodology in order to achieve improved performances in cycloidal rotors operating in forward-flight and lift-up phases. The proposed optimization analysis comprises computational fluid dynamics (CFD) simulations for the numerical database and an artificial neural network (ANN) to propose optimum operating states in each of the mentioned flying phases instead of the hover state under ground effects. CFD predictions were conducted for various operating conditions of pitching oscillations and rotating speeds at each forward or lift-up speed. By training the ANN algorithm using the database attained from CFD simulations, the optimization process was further surveyed for each corresponding flying mode. The targeting concept is to operate with an active mode of employing pitching angles rather than using constant oscillations at all rotation speeds. The ANN approach effectively proposed an optimized pitching schedule for both forward and lift-up phases after analyzing a wide range of parameters in order to reach an optimum aerodynamic efficiency. Because the blade and flow properties are all considered at each specific point on the continuous azimuth of the circular (360 degrees) trajectory, the mutual collaboration of CFD and ANN analysis showed to be advantageous for enhanced operations. (C) 2021 American Society of Civil Engineers.