Abstract
We introduce a complex image processing scheme for the simultaneous application of liquid crystal thermometry (LCT), in addition to the previously established method in Anders et al. (Exp Fluids 60(4):68, 2019. https://doi.org/10.1007/s00348-019-2703-8) for particle tracking velocimetry and particle image velocimetry. This scheme was developed for an experimental study on the double-diffusive convection in an aqueous ammonium chloride solution NH4Cl(aq) during crystallization. The use of thermochromic liquid crystals (TLC) enables to visualize the flow and temperature field simultaneously. We present a color interpolation method that enhances the accuracy of the LCT by yielding RGB images only representative of the TLC’s coloration. An artificial neural network (ANN) which processes RGB triplets and spatial color dependencies transforms these images into temperature fields. The combination of the ANN system and a corresponding calibration procedure enhances the accuracy and measurable temperature range of the LCT compared to state-of-the-art procedures. By using the here established measurement scheme, quantitative global studies of the mutual influence between solidification and convection are enabled and exemplary results are presented.Graphic abstract
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