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[HTML][HTML] Wind turbine blade trailing edge crack detection based on airfoil aerodynamic noise: An experimental study
Y Zhang, F Avallone, S Watson - Applied Acoustics, 2022 - Elsevier
In recent years, with the development of the wind power industry and the increase in the
number of wind turbines, the condition monitoring of blades and the detection of damage are …
number of wind turbines, the condition monitoring of blades and the detection of damage are …
The effect of boundary layer character on stochastic rotor blade vortex shedding noise
CS Thurman, NS Zawodny… - The Vertical Flight Society's …, 2022 - ntrs.nasa.gov
This work illustrates the effect of a rotor blade's boundary layer on the broadband LBL-VS
self-noise emitted from an optimum hovering rotor through experimental and multi-fidelity …
self-noise emitted from an optimum hovering rotor through experimental and multi-fidelity …
Influence of roughness trips on near-and far-field trailing-edge noise
FL Dos Santos, L Botero-Bolívar, C Venner… - AIAA journal, 2022 - arc.aiaa.org
Roughness trips are widely applied in wind-tunnel testing to hasten the laminar–turbulent
boundary-layer transition. It is well known that they influence the boundary-layer transition …
boundary-layer transition. It is well known that they influence the boundary-layer transition …
A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks
M Morelli, J Hauth, A Guardone, X Huan… - Structural and …, 2023 - Springer
This work develops a novel ice detection framework specifically suitable for rotorcraft using
computational aeroacoustics and Bayesian neural networks. In an offline phase of the work …
computational aeroacoustics and Bayesian neural networks. In an offline phase of the work …
Effect of surface roughness geometry on boundary-layer transition and far-field noise
Q Ye, F Avallone, D Ragni, M Choudhari, D Casalino - AIAA Journal, 2021 - arc.aiaa.org
Surface roughness elements are often used to force laminar to turbulent transition in
aerodynamic and aeroacoustic wind-tunnel experiments. The statistical features and …
aerodynamic and aeroacoustic wind-tunnel experiments. The statistical features and …
Noise reduction on low Reynolds number rotors by boundary layer transition
ER Gowree, T Jaroslawski, B Mellot, R Gojon - Applied Acoustics, 2023 - Elsevier
Following force balance and acoustic measurements in an anechoic chamber, we have
shown that promoting earlier boundary layer transition on an idealised low Reynolds …
shown that promoting earlier boundary layer transition on an idealised low Reynolds …
Influence of surface roughness geometry on trailing edge wall pressure fluctuations and noise
FL Dos Santos, NA Even, L Botero, C Venner… - AIAA Aviation 2021 …, 2021 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2021-2294. vid Surface roughness
elements are commonly used in wind tunnel testing to hasten the laminar-turbulent transition …
elements are commonly used in wind tunnel testing to hasten the laminar-turbulent transition …
Passive noise control for low reynolds number rotors
S Montoya-Ospina, F Simon, R Gojon… - 30th AIAA/CEAS …, 2024 - arc.aiaa.org
The use of passive noise control techniques for low Reynolds rotors, such as trip** of the
boundary layer, has provided evidence of a possible improvement of aerodynamic …
boundary layer, has provided evidence of a possible improvement of aerodynamic …
Effect of surface roughness on boundary layer transition and far field noise
Q Ye, F Avallone, D Ragni, MM Choudhari… - 25th AIAA/CEAS …, 2019 - arc.aiaa.org
2 u'= streamwise velocity fluctuations x= Cartesian coordinate axes aligned with the airfoil
chord xt= chordwise location of transition front y= Cartesian coordinate axes normal to airfoil …
chord xt= chordwise location of transition front y= Cartesian coordinate axes normal to airfoil …
Advances in Intuitive Priors and Scalable Algorithms for Bayesian Deep Neural Network Models in Scientific Applications
J Hauth - 2024 - deepblue.lib.umich.edu
In recent years, deep learning (DL) algorithms have gained widespread use in scientific and
engineering fields, promising insights into complex trends within extensive datasets …
engineering fields, promising insights into complex trends within extensive datasets …