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Scalco, Leonardo; Tonietto, Leandro; Velloso, Raquel Quadros; Racolte, Graciela; Gonzaga, Luiz; Veronez, Mauricio Roberto
Scientific reports, 06/2022, Letnik: 12, Številka: 1Journal Article
Abstract The roughness property of rocks is significant in engineering studies due to their mechanical and hydraulic performance and the possibility of quantifying flow velocity and predicting the performance of wells and rock mass structures. However, the study of roughness in rocks is usually carried out through 2D linear measurements (through mechanical profilometer equipment), obtaining a coefficient that may not represent the entire rock surface. Thus, based on the hypothesis that it is possible to quantify the roughness coefficient in rock plugs reconstructed three-dimensionally by the computer vision technique, this research aims to an alternative method to determine the roughness coefficient in rock plugs. The point cloud generated from the 3D model of the photogrammetry process was used to measure the distance between each point and a calculated fit plane over the entire rock surface. The roughness was quantified using roughness parameters ( $$R_a$$ R a ) calculated in hierarchically organized regions. In this hierarchical division, the greater the quantity of division analyzed, the greater the detail of the roughness. The main results show that obtaining the roughness coefficient over the entire surface of the three-dimensional model has peculiarities that would not be observed in the two-dimensional reading. From the 2D measurements, mean roughness values ( $$R_a$$ R a ) of $$0.35\,\upmu \hbox {m}$$ 0.35 μ m and $$0.235\,\upmu \hbox {m}$$ 0.235 μ m were obtained for samples 1 and 2, respectively. By the same method, the results of the $$R_a$$ R a coefficient applied three-dimensionally over the entire rocky surface were at most $$0.165\,\upmu \hbox {m}$$ 0.165 μ m and $$0.166\,\upmu \hbox {m}$$ 0.166 μ m , respectively, showing the difference in values along the surface and the importance of this approach.
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