The onset of fluid-elastic instability in cylinder arrays is usually thought to depend primarily on the mean flow velocity, the Scruton number and the natural frequency of the cylinders. Currently, there is considerable evidence from experimental measurements and computational fluid dynamic (CFD) simulations that the Reynolds number is also an important parameter. However, the available data are not sufficient to understand or quantify this effect. In this study we use a high resolution pseudo-spectral scheme to solve 2-D penalized Navier-Stokes equations in order to accurately model turbulent flow past cylinder array. To uncover the Reynolds number effect we perform simulations that vary Reynolds number independent of flow velocity at a fixed Scruton number, and then analyze the cylinder responses. The computational complexity of our algorithm is a function of Reynolds number. Therefore, we developed a high performance parallel code which allows us to simulate high Reynolds numbers at a reasonable computational cost. The simulations reveal that increasing Reynolds number has a strong de-stabilizing effect for staggered arrays. On the other hand, for the in-line array case Reynolds number still affects the instability threshold, but the effect is not monotonic with increasing Reynolds number. In addition, our findings suggest that geometry is also an important factor since at low Reynolds numbers critical flow velocity in the staggered array is considerably higher than the in-line case. This study helps to better predict how the onset of fluid-elastic instability depends on Reynolds number and reduces uncertainties in the experimental data which usually do not consider the effect of Reynolds number. / Thesis / Master of Science (MSc)

Background. Several methods have been used to simulate soft body deformation, such as mass-spring systems and position-based dynamics. This has been done using tetrahedral mesh models for preservation of shape and volume. In real-time applications however, there is a limitation to how high resolution the model can be, creating the need for optimizations. Objectives. To achieve better performance for high resolution models, tetrahedral deformation is used, making it possible for the tetrahedral mesh and triangle mesh to use different resolutions. In combination with this, the GPU is used to execute the simulation in parallel, improving performance further. Methods. For evaluation of performance and accuracy, an implementation was created to simulate soft body deformation using extended position-based dynamics and the Vulkan graphics API, with the option to use tetrahedral deformation. By experimentation, comparisons are made between using different resolutions on the tetrahedral mesh to the full resolution in terms of performance and accuracy. Results. The results show that performance and accuracy are altered when using tetrahedral deformation on lower resolution tetrahedral mesh. The performance is improved based on the decrease in workload, such as with higher base resolution models or multiple soft bodies. The accuracy is however not correlated to the reduction of resolution, but instead dependant on the rest shape of the model used. Conclusions. The implementation created demonstrates a new optimization that can be used to simulate soft body deformation in parallel on the GPU, with a smaller change in accuracy. Improvements exist in areas of usability, features and other optimizations that can be further explored in future research.

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