Suspending particles in liquids is an important and versatile case for industrial stirring processes. By using advanced optical, non‐invasive measurement techniques like particle image velocimetry (PIV), it is possible to gain deep insights into the involved fluid dynamics without affecting the flow. However, for suspensions, the application of PIV is not trivial since both, suspended and tracer particles are present and need to be discerned during experiments. The here presented method development solves this problem and thus leads to a better insight into turbulent kinetic energy distribution, which can be utilized for process optimization through improved stirred vessel design.

Hydrates of natural gases like methane have become subject of great interest over the last few decades, mainly because of their potential as energy resource. The exploitation of these natural gases from gas hydrates is seen as a promising mean to solve future energetic problems. Furthermore, gas hydrates play an important role in gas transportation and gas storage: in pipelines, particularly in tubes and valves, gas hydrates are formed and obstruct the gas flow. This phenomenon is called “plugging” and causes high operational expenditure as well as precarious safety conditions. In this work, research on the formation of gas hydrates under pipeline-like conditions, with the aim to predict induction times as a mean to evaluate the plugging potential, is described.

The results of measurements using two different particle image velocimetry (PIV) systems (2D-PIV versus stereo-PIV) are compared and the obtained data with a coupled CFD simulation are also correlated. A stirred vessel with internal helical coil as additional heat exchanger is analyzed with these settings. Results for the velocity fields and turbulent kinetic energy distribution are shown and the feasibility of stereo-PIV measurements by using refractive index matching fluid is proven. This investigation provides a good accordance and consistency between the different PIV systems and the related CFD.

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