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This study introduces a deep learning surrogate model designed to predict the evolution of the mean pressure coefficient on the back face of a Windsor body across a range of yaw angles from 2. 5 ∘ to 10 ∘ . Utilizing a variational autoencoder (VAE), the model effectively compresses snapshots of back pressure taken at yaw angles of 2. 5 ∘ , 5 ∘ , and 10 ∘ into two latent vectors. These snapshots are derived from wall-modeled large eddy simulations (WMLESs) conducted at a Reynolds number of R e L = 2.9 × 10 6 . The frequencies that dominate the latent vectors correspond closely with those observed in both the drag's temporal evolution and the dynamic mode decomposition. The projection of the mean pressure coefficient to the latent space yields an increasing linear evolution of the two latent variables with the yaw angle. The mean pressure coefficient distribution at a yaw angle of 7. 5 ∘ is predicted with a mean error of e ¯ = 3.13 % when compared to the WMLESs results after obtaining the values of the latent space with linear interpolation. [ABSTRACT FROM AUTHOR]

The noise radiated by the flow around a cylinder in the subcritical regime at R e D = 1 × 10 4 and at a subsonic Mach number of M = 0.5 is here studied. The aerodynamic sound radiated by a cylinder has been studied with a wide range of Reynolds numbers, but there are no studies about how the Mach number affects the acoustic field in the subsonic regime. The flow field is resolved by means of large-eddy simulations of the compressible Navier–Stokes equations. For the study of the noise propagation, formulation 1C of the Ffowcs Williams–Hawkings analogy is used. The fluid flow results show good agreement when comparing the surface pressure coefficient, the recirculation length, the vortex shedding frequency and the force coefficients against other studies performed under similar conditions. The dynamic mode decomposition of the pressure fluctuations is used to relate them with the far-field noise. It is shown that, in contrast to what happens for low Mach numbers, quadrupoles have a significant impact mainly in the observers located in the streamwise direction. This effect leads to a global monopole directivity pattern as the shear fluctuations compensate for the lower value of the aeolian tone away from the cross-stream direction. [ABSTRACT FROM AUTHOR]

This paper analyzes the behavior of a miniature 3D wind sensor designed for Mars atmosphere. The sensor is a spherical structure of 10 mm diameter divided in four sectors. By setting all the sectors to constant temperature, above that of the air, the 3D wind velocity vector can be measured. Two sets of experiments have been performed. First, an experimental campaign made under typical Mars conditions at the Aarhus Wind Tunnel Simulator is presented. The results demonstrate that both wind speed and angle can be efficiently measured, using a simple inverse algorithm. The effect of sudden wind changes is also analyzed and fast response times in the range of 0.7 s are obtained. The second set of experiments is focused on analyzing the performance of the sensor under extreme Martian wind conditions, reaching and going beyond the Dust Devil scale. To this purpose, both high-fidelity numerical simulations of fluid dynamics and heat transfer and experiments with the sensor have been performed. The results of the experiments, made for winds in the Reynolds number 1000–2000 range, which represent 65–130 m/s of wind speed under typical Mars conditions, further confirm the simulation predictions and show that it will be possible to successfully measure wind speed and direction even under these extreme regimes. [ABSTRACT FROM AUTHOR]