尾矿坝溃坝的一种基于联结关系的表示

4open Pub Date : 2020-01-01 DOI:10.1051/fopen/2020011
Laura Maria Canno Ferreira Fais, V. González-López, D. S. Rodrigues, Rafael Rodrigues de Moraes
{"title":"尾矿坝溃坝的一种基于联结关系的表示","authors":"Laura Maria Canno Ferreira Fais, V. González-López, D. S. Rodrigues, Rafael Rodrigues de Moraes","doi":"10.1051/fopen/2020011","DOIUrl":null,"url":null,"abstract":"In this article, we model the dependence between dam factor and D max, where dam factor is an indicator of risk of a tailings dam failure, which involves the height H of the tailings dam, the volume of material housed by the tailings dam VT and the volume dispensed by the tailings dam, VF, when the dam breaks. And, Dmax is the maximum distance traveled by the material released by the tailings dam, after the collapse. With the dependence found via copula models and Bayesian estimation, given a range of dam factor, we estimate the probability of the released material to exceed a certain threshold. Since the dam factor involves the released volume VF (unknown before the dam break), we present a naive way to estimate it using VT and H. In this way, it is possible to estimate the dam factor of a tailings dam and with such a value to identify the probability of the tailings dam to show a Dmax that exceeds a certain threshold.","PeriodicalId":6841,"journal":{"name":"4open","volume":"47 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A copula based representation for tailings dam failures\",\"authors\":\"Laura Maria Canno Ferreira Fais, V. González-López, D. S. Rodrigues, Rafael Rodrigues de Moraes\",\"doi\":\"10.1051/fopen/2020011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, we model the dependence between dam factor and D max, where dam factor is an indicator of risk of a tailings dam failure, which involves the height H of the tailings dam, the volume of material housed by the tailings dam VT and the volume dispensed by the tailings dam, VF, when the dam breaks. And, Dmax is the maximum distance traveled by the material released by the tailings dam, after the collapse. With the dependence found via copula models and Bayesian estimation, given a range of dam factor, we estimate the probability of the released material to exceed a certain threshold. Since the dam factor involves the released volume VF (unknown before the dam break), we present a naive way to estimate it using VT and H. In this way, it is possible to estimate the dam factor of a tailings dam and with such a value to identify the probability of the tailings dam to show a Dmax that exceeds a certain threshold.\",\"PeriodicalId\":6841,\"journal\":{\"name\":\"4open\",\"volume\":\"47 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"4open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1051/fopen/2020011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"4open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1051/fopen/2020011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在本文中,我们建立了坝系数与Dmax之间的关系模型,其中坝系数是衡量尾矿库溃坝风险的一个指标,它涉及尾矿库高度H、尾矿库所容纳的物料体积VT和溃坝时尾矿库所分配的体积VF。其中,Dmax为尾矿坝崩塌后释放的物料所移动的最大距离。根据copula模型和贝叶斯估计的相关性,给定一定范围的大坝因子,我们估计了释放物质超过某一阈值的概率。由于坝因子涉及到溃坝前未知的释放体积VF,我们提出了一种利用VT和h来估计坝因子的朴素方法,这样就可以估计出尾矿坝的坝因子,并利用这个值来识别尾矿坝出现Dmax超过某一阈值的概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A copula based representation for tailings dam failures
In this article, we model the dependence between dam factor and D max, where dam factor is an indicator of risk of a tailings dam failure, which involves the height H of the tailings dam, the volume of material housed by the tailings dam VT and the volume dispensed by the tailings dam, VF, when the dam breaks. And, Dmax is the maximum distance traveled by the material released by the tailings dam, after the collapse. With the dependence found via copula models and Bayesian estimation, given a range of dam factor, we estimate the probability of the released material to exceed a certain threshold. Since the dam factor involves the released volume VF (unknown before the dam break), we present a naive way to estimate it using VT and H. In this way, it is possible to estimate the dam factor of a tailings dam and with such a value to identify the probability of the tailings dam to show a Dmax that exceeds a certain threshold.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A review on Quantum Dots (QDs) and their biomedical applications Post-synthetic modification of semiconductor nanoparticles can generate lanthanide luminophores and modulate the electronic properties of preformed nanoparticles Adaptability of polyurea microcapsules loaded with octyl salicylate for sunscreen application: influence of shell thickness of microfluidic-calibrated capsules on UV absorption efficiency Investigation of the link between the human skin relief and the dermal fibers network by coupling topographic analysis and LC-OCT imaging before and during folding tests Dwell time in contact-free creep tests plays an age-dependent role in the viscoelastic behavior of in vivo human skin
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1