Litcius/Paper detail

Prediction-Based Auralization of a Multirotor Urban Air Mobility Vehicle

Siddhartha Krishnamurthy, Stephen A. Rizzi, Rui Cheng, D. Douglas Boyd, Andrew Christian

2021AIAA Scitech 2021 Forum14 citationsDOI

Abstract

View Video Presentation: https://doi.org/10.2514/6.2021-0587.vid Recent advances in auralization methods applicable to rotary wing vehicles have made it possible to undertake a prediction-based auralization of a representative multirotor urban air mobility vehicle. These advances include a new capability for synthesizing loading and thickness noise directly from the prediction method and a new capability for predicting and synthesizing modulating broadband self noise within a unified system noise prediction-auralization framework. These capabilities are demonstrated for a six-passenger quadrotor reference vehicle design using collective-pitch control. Propagation of the source noise to a ground observer completes the auralization process. The demonstrated capability serves as the basis for future work directed at perception-influenced design of low noise urban air mobility vehicles.

Topics & Concepts

MultirotorNoise (video)Computer scienceObserver (physics)Automotive engineeringProcess (computing)Noise controlBroadbandAcousticsEngineeringAerospace engineeringArtificial intelligenceNoise reductionTelecommunicationsQuantum mechanicsPhysicsOperating systemImage (mathematics)Aerodynamics and Acoustics in Jet FlowsAcoustic Wave Phenomena ResearchVehicle Noise and Vibration Control