# Prediction and Control of Broadband Noise Associated with Advanced Air Mobility--A Review
## 1 Introduction  
Advanced air mobility (AAM) encompasses a range of innovative air transportation systems designed to move people and goods in urban and rural areas using new, highly automated, and electric aircraft. AAM includes several types, such as urban air mobility (UAM); small, unmanned aircraft systems (sUAS); and regional air mobility (RAM).  
UAM operates within urban environments, with take-off and landing at a vertiport. UAM vehicles are powered by multiple electrical rotors or propellers, which we also call eVTOL. There are several configurations that have been tested, including multirotor, compound-wing VTOL, tilttor/propeller, tiltwing, and ducted fan [1], as shown in Figure 1. The sUAS is a small version of UAM with missions for aerial work or cargo delivery. RAM extends the UAM operation range to 500 miles and normally adopts electric conventional take-off and landing (eCTOL) and electric short take-off and landing (eSTOL) aircraft [2].  
AAM operates near populated communities, which will face two big obstacles: safety and noise. Noise pollution has significant implications for public acceptance, regulatory compliance, and environmental impact. Since AAM operates in populated areas, AAM noise needs to be addressed, particularly near vertiports, where the population is dense and close to the noise sources. The Federal Aviation Administration (FAA) has noise certification standards for AAM to avoid noise pollution [3]. AAM is propelled by distributed propellers, which are the dominant noise sources. The noise generated by propellers can be categorized into tonal noise and broadband noise (BBN). Tonal noise is characterized by discrete frequencies often associated with rotating components, while broadband noise encompasses a wide range of frequencies, resulting in a continuous noise spectrum. Tonal noise istypically divided into loading noise and thickness noise, characterized by tonal noise at the blade-passing frequency (BPF) and its harmonics. Broadband noise (BBN) is characterized by unsteady turbulence loading due to blade-wake interaction, turbulence in the boundary layer, and turbulence ingestion [4].  
AAM propellers have more blades and are smaller, with diameters that can be 20 times less than those of traditional helicopter rotors, which causes their significantly lower tip speeds. The noise signatures of AAM propellers differ from those of full-scale helicopter rotors due to their lower tip speeds. Figure 1 shows that the BBN becomes more important with a decrease in the tip Mach number, dominating below 0.5 Ma. Furthermore, AAM has a complicated structure and multiple rotors or propellers; the propellers interact and ingest more structure wake. Additionally, in an urban atmosphere and an environment dominated by buildings exists non-uniform flow compromising wakes, vortex, gust, and turbulence, among other irregularities. For these reasons, broadband noise may have a comparable amplitude to that of the blade passage frequency (BPF) and associated harmonics.  
This paper reviews broadband noise (BBN) resources, prediction methods, and passive and active control techniques for BBN reduction. To begin, we explore the available resources for understanding BBN, focusing on both theoretical foundations and empirical data. Following this, we examine various prediction methods, highlighting computational models and experimental approaches that have shown promise in accurately forecasting BBN levels. Then, we move to control strategies, focusing on passive control methods that are easy to apply. Throughout the paper, we emphasize the importance of these strategies in the context of AAM, particularly given the unique noise challenges posed by smaller, lower-tip-speed propellers. By leveraging recent advances in theory, computational methods, and experimental approaches, there are significant opportunities to further understand and reduce BBN in AAM, enhancing the sustainability and public acceptance of this emerging technology.