# Prediction and Control of Broadband Noise Associated with Advanced Air Mobility--A Review
## 3 Methods for Prediction of BBN
### Low-Fidelity Methods  
The low-fidelity models of no turbulence ingestion normally employ the blade element momentum theory (BEMT) and XFOIL or 2D RANS in conjunction with one of the above-established noise prediction models or codes. [PERSON] et al. [50] investigated a low-fidelity benchmark study by two-bladed APC-96 with 0.3 m diameter. They used XFOIL and BEMT to determine the aerodynamic performance, then applied the [PERSON] and Moreau [51] model that is the corrected form of [PERSON]'s trailing-edge noise model to predict the BBN. Figure 10 shows that the low-fidelity approach demonstrated good agreement with the experiment and high-fidelity results at mid-to-high frequencies, despite some underpredictions, particularly at low frequencies. Similarly, [PERSON] et al. [52] performed a study using the same methodology to explore the noise characteristics of 5-blade and 7-blade propellers, further validating the effectiveness of low-fidelity models in predicting propeller noise.  
[PERSON] and [PERSON] [53] performed validations on a NASA ideally twisted rotor, an SUI Endurance rotor, and a DJI-CF propeller using noise code UCD-QuietFly, with BEMT and  
Figure 10: Noise power spectral density at \(J=0.6\)[50].  
XFOIL as the aerodynamic inputs. Various rotational speeds and surface roughness conditions were considered in the hovering and forward flight conditions. The predictions from UCD-QuietFly agreed well with the experiments in various small-scale rotor conditions at mid-to-high frequencies, as shown in Figure 11.  
[PERSON] et al. [54] utilized the blade element momentum theory (BEMT) to evaluate three empirical broadband noise (BBN) equations specifically designed for helicopters, applying them to small propellers. The models were validated using data from APC and DJI propellers. As illustrated in Table 2 and Figure 12, the DH and SG models were overpredicted, while the SKM model provided the closest results to the experimental data. Additionally, the discrepancies vary significantly when applied to propellers of different diameters, indicating that the three models lack robustness. Therefore, a new empirical model specifically designed for AAM propeller/rotor needs to be developed.  
Serval low-fidelity turbulence ingestion studies have been developed recently. [PERSON] et al. [55] studied the turbulence boundary layer ingestion BBN of a fan with the [PERSON] [7] model. They employed [PERSON]'s [56] model for the boundary layer turbulence, which was validated by the experiment. They validated the model against the experiment by three different advanced ratios, as shown in Figure 13. The results show that they overpredicted haystacking at the first BPF at \(J\) = 0.87, as well as at the second BPF at all the advance ratios. Conversely, they underpredicted the high-frequency noise, particularly at \(J\) = 1.44 and \(J\) = 1.05, likely due to the limitations of the turbulence model's accuracy. Despite these discrepancies, the model showed good agreement with the experimental data.  
Similar work was conducted by [PERSON] and [PERSON] [57]. They revised [PERSON]'s [7] model and compared the original model and experimental data by applying them to an open rotor. They reported that [PERSON]'s [7] model is the most effective model to predict the TIN of rotors, given its accuracy and lower computational cost.