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In this case study, we explore techniques for the purpose of visualizing isolated flow structures in time-dependent data. Our primary industrial application is the visualization of the vortex rope, a rotating helical structure which builds up in the draft tube of a water turbine. The vortex rope can be characterized by high values of normalized helicity, which is a scalar field derived from the given CFD velocity data. In two related applications, the goal is to visualize the cavitation regions near the runner blades of a Kaplan turbine and a water pump, respectively. Again, the flow structure of interest can be defined by a scalar field, namely by low pressure values. We propose a particle seeding scheme based on quasi-random numbers, which minimizes visual artifacts such as clusters or patterns. By constraining the visualization to a region of interest, occlusion problems are reduced and storage efficiency is gained.