WITHDRAWN: Determination of the statistical distribution of drag and lift coefficients of refuse derived fuel by computer vision

Abstract

This research investigates the flight behavior of refuse-derived fuel (RDF) in a drop shaft using Computer Vision to obtain statistical data on the aerodynamic properties of the particles. Methods to determine 3D geometry models of complex-shaped particles by photogrammetry and to obtain time resolved particle positions and velocities are described. Furthermore, an approach to obtain the frequency distribution of drag and lift coefficients from photogrammetric analysis and drop shaft experiments is presented. The image evaluation is based on algorithms of the open-source libraries OpenCV, COLMAP as well as MeshLab and Open3D. The precision of the system is validated employing model particles with known geometry. The 3D particle models overestimate the particle surface area by 4.58 %, the position detection works with a mean deviation of 2.73 %. The average sink rate is calculated with an accuracy of 4.87 % and the drag coefficient with an accuracy of 2.08 %. Finally, the frequency distribution of four RDF fractions, namely, textiles, cardboard, 3D plastic particles and plastic foils are presented.