Statistical Analysis of the Effective Friction Angle of Sand Tailings from Germano Dam
Auteur(s): |
Leonardo De Bona Becker
(Department of Civil Construction-Geotechnics, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil)
Maria do Carmo Reis Cavalcanti (Department of Civil Construction-Geotechnics, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil) Alfredo Affonso Monteiro Marques (Department of Civil Construction-Geotechnics, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil) |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Infrastructures, mars 2023, n. 3, v. 8 |
Page(s): | 61 |
DOI: | 10.3390/infrastructures8030061 |
Abstrait: |
Tailings dam accidents emphasize the importance of an adequate understanding of the strength parameters of tailings to improve the efficiency and effectiveness of the design, construction, and operation of such structures. Usually, the tailings strength is addressed in a deterministic manner. However, a statistical approach would better represent their behavior due to its inherent heterogeneity. The literature about tailings strength distribution is relatively rare or superficial, which impairs the probabilistic analyses which are essential for risk management. Therefore, this article focuses on the probability density function (PDF) of the effective friction angle (ϕ′) of iron ore tailings from the reservoir of Germano dam, Mariana, Brazil, based on data from publicly available CPTu tests. The influence of the relative density (Dr), and the presence of plastic layers amidst the sand tailings on the strength of the sand are also discussed herein. Several correlations were employed to estimate ϕ’ and Dr. According to the results, the presence of plastic layers influences the estimated properties, and the relative density has a log-normal distribution. The effective friction angle, on the other hand, presents a normal distribution. |
Copyright: | © 2023 the Authors. Licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10722710 - Publié(e) le:
22.04.2023 - Modifié(e) le:
10.05.2023