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Fibre streaks are observed in experiments with fibre suspensions in a turbulent half-channel flow. The preferential concentration methods, most commonly used to quantify preferential particle concentration, are in one dimension found to be concentration dependent. Two different new streak quantification methods are evaluated, one based on Voronoi analysis and the other based on artificial particles with an assigned fixed width. The width of the particle streaks and a measure of the intensity of the streaks, i.e. streakiness, are sought. Both methods are based on the auto-correlation of a signal, generated by summing images in the direction of the streaks. Common for both methods is a severe concentration dependency, verified in experiments keeping the flow conditions constant while the (very dilute) concentration of fibres is altered. The fixed width method is shown to be the most suitable method, being more robust and less computationally expensive. By assuming the concentration dependence to be related to random noise, an expression is derived, which is shown to make the streak width and the streakiness independent of the concentration even at as low concentrations as 0.05 particles per pixel column in an image. The streakiness is obtained by applying an artificial particle width equal to 20 % of the streak width. This artificial particle width is in this study found to be large enough to smoothen the correlation without altering the streakiness nor the streak width. It is concluded that in order to make quantitative comparisons between different experiments or simulations, the evaluation has to be performed with care and be very well documented. [ABSTRACT FROM AUTHOR]

Steerable filters are concluded to be useful in order to determine the orientation of fibers captured in digital images. The fiber orientation is a key variable in the study of flowing fiber suspensions. Here, digital image analysis based on a filter within the class of steerable filters is evaluated for suitability of finding the position and orientation of fibers suspended in flowing suspensions. In sharp images with small noise levels, the steerable filter succeeds in determining the orientation of artificially generated fibers with well-defined angles. The influence of reduced image quality on the orientation has been quantified. The effect of unsharpness and noise is studied and the results show that the error in orientation is less than 1° for moderate levels. Images from two flow cases, one laminar shear flow and one turbulent, are also analyzed. The fiber orientation distribution is determined in the flow-vorticity plane. For the laminar case a comparison is made to a robust, but computationally more expensive, method involving convolutions with an oriented elliptic filter. A good agreement is found when comparing the resulting fiber orientation distributions obtained with the two methods. For the turbulent case, it is demonstrated that correct results are obtained and that the method can handle overlapping fibers. [ABSTRACT FROM AUTHOR]