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Software repository for the paper: Thanheiser, S.; Haider, M. Particle Mass Diffusion Model for Level Control of Bubbling Fluidized Beds with Horizontal Particle Flow Powder Technology 2023

The depository contains tools to test the ATS method for wake identification and characterization on the provided sample lidar data. The thresholding result can be further compared to the manual threshold (also provided) and a threshold based on the wake deficit (calculated by the script). The script includes procedure to fit the Gaussian function to wake deficit profiles and perform wake identification and characterization. The result of the Gaussian and ATS method are also compared. The provided scripts require Python 3.0 with Jupyter notebook support. Additional libraries required to calculate and plot the result are mostly standard: numpy, matplotlib, scipy, pandas, sklearn (for linear regression), scikit-image (for preprocessing). Jupyter notebook dashboard for the manual threshold selection requires few more libraries: holoviews, panel, param. {"references": ["Bakhoday-Paskyabi, M., Reuder, J. and Fl\u00fcgge, M.: Automated measurements of whitecaps on the ocean surface from a buoy-mounted camera, Methods Oceanogr., 17, 14\u201331, doi:10.1016/j.mio.2016.05.002, 2016.", "Krishnamurthy, R., Reuder, J., Svardal, B., Fernando, H. J. S. J. S. and Jakobsen, J. B. B.: Offshore Wind Turbine Wake characteristics using Scanning Doppler Lidar, Energy Procedia, 137, 428\u2013442, doi:10.1016/j.egypro.2017.10.367, 2017."]} The code is work in progress. Further improvements for the centerline search are planned.

Dataset and Calculation Models