# Prediction and Control of Broadband Noise Associated with Advanced Air Mobility--A Review
## 3 Methods for Prediction of BBN
### Numerical Methods
To delve deeper into the BBN analysis, the spectral proper orthogonal decomposition (SPOD) technique [64] was applied. They found that at low frequencies, blade self-noise and wake noise are comparable sources of broadband noise. However, at higher frequencies, blade self-noise became the dominant contributor to the noise spectrum. The same approach was applied to the case of two counter-rotating propellers by [PERSON] and [PERSON] [65]. In this scenario, the increased broadband noise was attributed to the close proximity of the rotors and the effects of wake mixing. A large eddy simulation (LES) resolves large-scale eddies through the filtered Navier-Stokes equations and models small-scale eddies through subgrid-scale (SGS) models. LES is one of the higher accuracy numerical methods and is suitable for rotor noise source simulations but is expensive. The more efficient method is the implicit large eddy simulation (IILES), which does not use an explicit subgrid-scale (SGS) model replaced by numerical dissipation. Although it may not capture very small-scale turbulence with high accuracy, it offers advantages in terms of computational cost and implementation. [PERSON] et al. [66] utilized this solver to predict the propeller BBN at hover and forward flight conditions by Formulation 1A. Despite the discrepancies between the numerical and experimental curves that may be caused by ignoring the nonlinear quadrupole noise terms of the FW-H formulation, Figure 17 demonstrates a good agreement between the experimental and numerical results for both hovering and forward flight conditions. However, in the forward case, the numerical analysis exhibited greater variation at higher frequencies and underpredicted the sound pressure level (SPL) in the low-to-mid-frequency range below 1 kHz, as shown in Figure 17b. They attributed this discrepancy to higher frequency contamination from the motor and background noise, which was clearly observed in the experimental data. Additionally, the low-to-mid-frequency contamination from interactions with the fairing could not be simulated by the simplified isolated propeller model used in the numerical analysis. Figure 16: Power spectral density compared with experiment [63]. The lattice Boltzmann method (LBM) is a computational fluid dynamics (CFD) technique used to simulate fluid flows. It is based on microscopic models and mesoscopic kinetic equations, rather than the macroscopic Navier-Stokes equations traditionally used in CFD. [PERSON] et al. [67] studied the lattice Boltzmann method-very-large-eddy simulation (LBM-VLES) using PowerFLOW software to predict the BBN of a DJI-9450 propeller. The far-field noise was computed using F1A formulation. Figure 18 illustrates a good agreement between the experimental and numerical results in the BBN curve trends. However, it overpredicted below 1.5 kHz and over 10 kHz. They explained the discrepancy below 1.5 kHz as turbulence generated by the rotor itself in the simulation having the spatial difference from the real experiment. The error above 10 kHz was attributed to the mesh size, as demonstrated by the grid sensitivity analysis. Additionally, they investigated the broadband noise sources in more detail by calculating the SPL\({}_{1/3}\) values of the unsteady pressure perturbations on the rotor blade suction surface. Figure 19 illustrates higher SPL\({}_{1/3}\) values at the trailing edge and tip of the blade, indicating that trailing-edge noise and tip vortex formation noise dominated in hovering conditions. This suggests that blade self-noise is the primary contributor to BBN. The lower SPL\({}_{1/3}\) values around the leading edge indicated that blade-wake interaction (BWI) noise could be ignored in hovering conditions, which was corroborated by the experimental test [68]. They explored more details for the BBN of a rotor by LBM simulation, such as broadband noise source identification [69] and blade vortex shedding noise [70].