A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Three-dimensional quantification and classification approach for angularity and surface texture based on surface triangulation of reconstructed aggregates
https://orcid.org/0000-0003-4004-9346
https://orcid.org/0000-0003-3916-0303
https://orcid.org/0000-0001-5983-7305
Highlights Three-dimensional angularity and texture indices of the aggregate were proposed and quantified. Statistical indices were proposed to compare the similarity of aggregates by the angularity and texture. Adaptive classification of aggregates by angularity and texture was conducted.
Abstract Angularity and surface texture of aggregates are important morphological characteristics, which have significant effects on the micromechanical responses of asphalt composites. A novel approach to quantify and classify the complexity of aggregate angularity and surface texture is proposed from a statistical perspective in this study. The methodology consists of three main steps, as follows: 1) the aggregate is three-dimensional (3D) reconstructed, and the model surface is triangulated into facets to conduct clustering for aggregate angles evaluation; 2) consequently, a reference plane is determined for each facet cluster to quantify the surface texture of a surface area which overlaps the cluster, and thus the surface texture is quantified; and 3) aggregates are classified by using the distribution characteristics of the angularity and surface texture respectively. Based on the quantification with the presented approach, 275 grains were classified by the angularity and surface texture. Results indicate the benefit of the proposed method in accurate quantification and classification of aggregate angularity and surface texture, which facilitate the bridging of the gap between aggregate morphology and micromechanical performance of asphalt composites.
Three-dimensional quantification and classification approach for angularity and surface texture based on surface triangulation of reconstructed aggregates
https://orcid.org/0000-0003-4004-9346
https://orcid.org/0000-0003-3916-0303
https://orcid.org/0000-0001-5983-7305
Highlights Three-dimensional angularity and texture indices of the aggregate were proposed and quantified. Statistical indices were proposed to compare the similarity of aggregates by the angularity and texture. Adaptive classification of aggregates by angularity and texture was conducted.
Abstract Angularity and surface texture of aggregates are important morphological characteristics, which have significant effects on the micromechanical responses of asphalt composites. A novel approach to quantify and classify the complexity of aggregate angularity and surface texture is proposed from a statistical perspective in this study. The methodology consists of three main steps, as follows: 1) the aggregate is three-dimensional (3D) reconstructed, and the model surface is triangulated into facets to conduct clustering for aggregate angles evaluation; 2) consequently, a reference plane is determined for each facet cluster to quantify the surface texture of a surface area which overlaps the cluster, and thus the surface texture is quantified; and 3) aggregates are classified by using the distribution characteristics of the angularity and surface texture respectively. Based on the quantification with the presented approach, 275 grains were classified by the angularity and surface texture. Results indicate the benefit of the proposed method in accurate quantification and classification of aggregate angularity and surface texture, which facilitate the bridging of the gap between aggregate morphology and micromechanical performance of asphalt composites.
Three-dimensional quantification and classification approach for angularity and surface texture based on surface triangulation of reconstructed aggregates
https://orcid.org/0000-0003-4004-9346
https://orcid.org/0000-0003-3916-0303
https://orcid.org/0000-0001-5983-7305
Highlights Three-dimensional angularity and texture indices of the aggregate were proposed and quantified. Statistical indices were proposed to compare the similarity of aggregates by the angularity and texture. Adaptive classification of aggregates by angularity and texture was conducted.
Abstract Angularity and surface texture of aggregates are important morphological characteristics, which have significant effects on the micromechanical responses of asphalt composites. A novel approach to quantify and classify the complexity of aggregate angularity and surface texture is proposed from a statistical perspective in this study. The methodology consists of three main steps, as follows: 1) the aggregate is three-dimensional (3D) reconstructed, and the model surface is triangulated into facets to conduct clustering for aggregate angles evaluation; 2) consequently, a reference plane is determined for each facet cluster to quantify the surface texture of a surface area which overlaps the cluster, and thus the surface texture is quantified; and 3) aggregates are classified by using the distribution characteristics of the angularity and surface texture respectively. Based on the quantification with the presented approach, 275 grains were classified by the angularity and surface texture. Results indicate the benefit of the proposed method in accurate quantification and classification of aggregate angularity and surface texture, which facilitate the bridging of the gap between aggregate morphology and micromechanical performance of asphalt composites.
Three-dimensional quantification and classification approach for angularity and surface texture based on surface triangulation of reconstructed aggregates
Jin, Can (author) / Zou, Feilong (author) / Yang, Xu (author) / Liu, Kai (author) / Liu, Pengfei (author) / Oeser, Markus (author)
2020-01-06
Article (Journal)
Electronic Resource
English
Imaging Indices for Quantification of Shape, Angularity, and Surface Texture of Aggregates
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Imaging Indices for Quantification of Shape, Angularity, and Surface Texture of Aggregates
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Investigation of the shape, size, angularity and surface texture properties of coarse aggregates
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