Abstract
Turbulent flow segmentation from image data is a challenging problem. This is due to the un-defined edge and the complex flow nature of turbulence. In this paper, an image-based technique is proposed for turbulent flow segmentation from image. The proposed technique segments the flow region based on enhancing the input image intensity at flow edges and by defining a thresholding value to differentiate between flow region and image background. To test the image-based segmentation technique, a turbulent buoyant jet was experimentally simulated at different nozzle flow rates which have a Reynolds numbers of 960, 1560, and 3210. Then, a video camera was used to record the jet flow data. Then, the image-based technique was applied to segment the flow region and estimate the jet penetration area. As a result, the turbulent flow region was segmented well for all cases of nozzle flow rates. Moreover, application of the image-based technique for jet penetration estimation showed a good agreement with the previous work, in which the jet propagated linearly over time.
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Acknowledgments
The authors would like to express their appreciation to Universiti Teknologi PETRONAS for supporting this work under YUTP 0153AA-E85.
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Osman, A.B., Ovinis, M., Faye, I., Hashim, F.M. (2018). Image-Based Technique for Turbulent Flow Segmentation. In: Alfred, R., Iida, H., Ag. Ibrahim, A., Lim, Y. (eds) Computational Science and Technology. ICCST 2017. Lecture Notes in Electrical Engineering, vol 488. Springer, Singapore. https://doi.org/10.1007/978-981-10-8276-4_12
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DOI: https://doi.org/10.1007/978-981-10-8276-4_12
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