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A generalized computational methodology for reduced order acoustic-structural coupled modeling of the aeroacoustics of a wind turbine blade is presented. This methodology is used to investigate the acoustic pressure distribution in and around airfoils to guide the development of a passive damage detection approach for structural health monitoring of wind turbine blades for the first time. The output of a k − ε turbulence model computational fluid dynamics simulation is used to calculate simple acoustic sources on the basis of model tuning with published experimental data. The methodology is then applied to a computational case study of a 0.3048-m chord NACA 0012 airfoil with two internal cavities, each with a microphone placed along the shear web. Five damage locations and four damage sizes are studied and compared with the healthy baseline case for three strategically selected acoustic frequencies: 1, 5, and 10 kHz. In 22 of the 36 cases in which the front cavity is damaged, the front cavity microphone measures an increase in sound pressure level (SPL) above 3 dB, while rear cavity damage only results in six out of 24 cases with a 3-dB increase in the rear cavity. The 1-and 5-kHz cases show a more consistent increase in SPL than the 10-kHz case, illustrating the spectral dependency of the model. The case study shows how passive acoustic detection could be used to identify blade damage, while providing a template for application of the methodology to investigate the feasibility of passive detection for any specific turbine blade. K E Y W O R D Sacoustic sensing, aeroacoustics, flow noise, passive damage detection, structural health monitoring, wind turbine blade | INTRODUCTIONThe amount of electricity generated by wind farms in the United States has grown from 34.4 × 10 6 MWh (0.83% of generated electricity) in 2007 to 25.4 × 10 7 MWh (6.3% of generated electricity) in 2017. 1 One quarter of electric power capacity additions in the United States in 2017 were wind farms, and $11 billion was invested in wind power, making it the third fastest growing source of electricity behind solar and natural gas. 2 The worldwide capacity reached 539 GW in 2017, an increase of 52.5 GW from 2016, and is expected to surpass 840 GW by the end of 2022. 3 As the wind energy industry continues to grow, it becomes increasingly important to reduce the levelized cost of energy (LCOE) for wind energy. The operation and maintenance (O&M) costs are a significant contributor to the overall LCOE and can account for between 11% and 30% LCOE of an onshore wind project with higher projected values for offshore projects. 4-6 Consequently, the LCOE can be mitigated by reducing the O&M costs.

Over the past three decades, Integral Boundary Layer Methods (IBL) have generated significant research interest in aerodynamics design and analysis, in particular for twodimensional airfoils. Recently Drela extended the analysis to three-dimensions in the IBL3 solver. In this paper we extend the IBL3 methodology for aerodynamics analysis of rotors including wind turbines and helicopters. We present IBL method results for rotating reference frames to illustrate the rotating boundary layer flow model. Nomenclature ρ = density τ = shear stress q = velocity η = normalized wall coordinate (0 = w, 1 = e) ( )e = edge quantity ( )i = inviscid quantity ( )w = wall quantity ( )' = planar quantity

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