Abstract

Fluid–structure interactions (FSI) on highly flexible structures involve large deformations and require specific techniques for a thorough investigation of the flow field and structural deformation. To this purpose, a physics-informed method is introduced that allows for simultaneous determination of the flow fields and the structural deformation by using Particle Image Velocimetry (PIV) raw images. The method combines apriori knowledge of the mechanical characteristics of the flexible structure with classical image processing techniques for segmentation. PIV recordings of an actively pitched, highly deformable hydrodynamic profile experiment in a closed water tunnel serve as an example case. To achieve accurate results, the contour obtained from image segmentation is further defined under the assumption that its flexure can be described with the Euler–Bernoulli beam theory model. This makes it possible to determine the neutral fiber of the structure and the final reconstruction becomes possible from knowledge of the original geometry. The resulting procedure allows for a recognition of the structure itself and is suitable for cross-section deformation measurements and for masking of the structure in the raw images to improve the PIV processing. A test case comprising synthetic data similar to the application with a modeled profile geometry of known shape is used to investigate the accuracy of the method and its validity for deformation measurements. Under conditions of cyclic dynamic stall, a mean absolute error of 0.84° could be reached, with a deterioration up to 2° mean absolute error under static stall. The method has a major advantage compared to other technically more sophisticated and complex methods, such as the combination of Laser interferometers combined with Laser-Doppler Anemometry: the method allows for the usage of a single data source for both, fluid and solid in a unified measurement method. Therefore a direct comparison of instantaneous flow field and deformation is possible. In consequence it is in particular useful for highly dynamic multi-physical processes involving extreme deformations, such as passive flow control and soft actuated or flexible under water robotics.

Full Text
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