Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization
Arrieta, Marco; Zhang, Zong-Xian (2024-04-01)
Springer
01.04.2024
Arrieta, M., Zhang, ZX. Particle size distribution (PSD) estimation using unmanned aerial vehicle (UAV) photogrammetry for rockfill shear strength characterization. Acta Geotech. 19, 6239–6258 (2024). https://doi.org/10.1007/s11440-024-02315-x
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© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202406104325
https://urn.fi/URN:NBN:fi:oulu-202406104325
Tiivistelmä
Abstract
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.
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.
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