A study of flow fields during filling of a sampler

Sammanfattning: More and more attention has been paid to decreasing the number and size of non-metallic inclusions existing in the final products recently in steel industries. Therefore, more efforts have been made to monitor the inclusions' size distributions during the metallurgy process, especially at the secondary steelmaking period. A liquid sampling procedure is one of the commonly applied methods that monitoring the inclusion size distribution in ladles, for example, during the secondary steelmaking. Here, a crucial point is that the steel sampler should be filled and solidified without changing the inclusion characteristics that exist at steel making temperatures. In order to preserve the original size and distributions in the extracted samples, it is important to avoid their collisions and coagulations inside samplers during filling. Therefore, one of the first steps to investigate is the flow pattern inside samplers during filling in order to obtain a more in-depth knowledge of the sampling process to make sure that the influence is minimized.The main objective of this work is to fundamentally study the above mentioned sampler filling process. A production sampler employed in the industries has been scaled-up according to the similarity of Froude Number in the experimental study. A Particle Image Velocimetry (PIV) was used to capture the flow field and calculate the velocity vectors during the entire experiment. Also, a mathematical model has been developed to have an in-depth investigate of the flow pattern in side the sampler during its filling. Two different turbulence models were applied in the numerical study, the realizable k-? model and Wilcox k-? model. The predictions were compared to experimental results obtained by the PIV measurements. Furthermore, it was illustrated that there is a fairly good agreement between the measurements obtained by PIV and calculations predicted by the Wilcox k-? model. Thus, it is concluded that the Wilcox k-? model can be used in the future to predict the filling of steel samplers.