Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization
https://orcid.org/http://orcid.org/0000-0003-0524-1623
The strength of rockfills and waste materials is significantly influenced by their particle size distribution (PSD). For large waste rockfills, PSD is fundamental to determine the shear behavior. Traditionally, PSD for rockfill, used in materials like coarse-grained aggregates, has been obtained through physical sieving. However, the particle sizes in hard rockfills can vary significantly from small particles (< 20 cm diameter) to large blocks or boulders over 100 cm, with the maximum size limited by the in situ ground conditions and blasting performance. Essentially, the sieving process is impractical, considering the scale of the mine waste dumps and the time required. Therefore, in this study, a workflow using digital detection to estimate the PSD is presented, aiming to quantify the waste dump shear strength using Barton–Kjaernsli empirical criterion. PSD from UAV is validated using manual field measurements of individual boulders. The error for coarse characteristic size prediction ranges within ± 4 mm, and the increase in the data collection frequency, area covered, and resolution of fragmentation measurement for rockfills and waste dumps using UAV allows to improve the statistical reliability of the PSD and fragmentation measurement.
Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization
https://orcid.org/http://orcid.org/0000-0003-0524-1623
The strength of rockfills and waste materials is significantly influenced by their particle size distribution (PSD). For large waste rockfills, PSD is fundamental to determine the shear behavior. Traditionally, PSD for rockfill, used in materials like coarse-grained aggregates, has been obtained through physical sieving. However, the particle sizes in hard rockfills can vary significantly from small particles (< 20 cm diameter) to large blocks or boulders over 100 cm, with the maximum size limited by the in situ ground conditions and blasting performance. Essentially, the sieving process is impractical, considering the scale of the mine waste dumps and the time required. Therefore, in this study, a workflow using digital detection to estimate the PSD is presented, aiming to quantify the waste dump shear strength using Barton–Kjaernsli empirical criterion. PSD from UAV is validated using manual field measurements of individual boulders. The error for coarse characteristic size prediction ranges within ± 4 mm, and the increase in the data collection frequency, area covered, and resolution of fragmentation measurement for rockfills and waste dumps using UAV allows to improve the statistical reliability of the PSD and fragmentation measurement.
Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization
https://orcid.org/http://orcid.org/0000-0003-0524-1623
The strength of rockfills and waste materials is significantly influenced by their particle size distribution (PSD). For large waste rockfills, PSD is fundamental to determine the shear behavior. Traditionally, PSD for rockfill, used in materials like coarse-grained aggregates, has been obtained through physical sieving. However, the particle sizes in hard rockfills can vary significantly from small particles (< 20 cm diameter) to large blocks or boulders over 100 cm, with the maximum size limited by the in situ ground conditions and blasting performance. Essentially, the sieving process is impractical, considering the scale of the mine waste dumps and the time required. Therefore, in this study, a workflow using digital detection to estimate the PSD is presented, aiming to quantify the waste dump shear strength using Barton–Kjaernsli empirical criterion. PSD from UAV is validated using manual field measurements of individual boulders. The error for coarse characteristic size prediction ranges within ± 4 mm, and the increase in the data collection frequency, area covered, and resolution of fragmentation measurement for rockfills and waste dumps using UAV allows to improve the statistical reliability of the PSD and fragmentation measurement.
Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization
Acta Geotech.
Arrieta, Marco (Autor:in) / Zhang, Zong-Xian (Autor:in)
Acta Geotechnica ; 19 ; 6239-6258
01.09.2024
20 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Barton–Kjaernsli shear strength criterion , Particle size distribution (PSD) , Photogrammetry , Slope stability , Unmanned aerial vehicle (UAV) , Waste dumps and rockfill shear strength Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
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