矿山地质力学设计中的不确定性量化

M. Dunn
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引用次数: 5

摘要

采矿地质力学和岩土工程中的不确定性是一个广义的术语,它解释了自然变化,缺乏数据和缺乏知识。减少不确定性是采矿研究过程和管理地质力学/岩土工程风险的关键组成部分。理解和减少不确定性也是设计过程中的关键活动,以确保设计是稳健和有弹性的。地质力学设计中使用了多种方法,包括经验、分析和数值模拟。所有设计方法都需要输入,这些输入基于岩心测井、测绘、实验室测试、现场观察和监测的数据。然后必须对这些数据进行编译和解释,以便得出与设计水平(从范围到操作)相称的有意义和可靠的设计输入。这包括地质力学或岩土工程模型的发展。岩土模型的不确定性通常用置信度或可靠性来描述。目前,在评估岩土工程研究和设计的置信水平方面,文献中很少有定量指导,尽管许多作者已经进行了尝试(Haile 2004;海恩斯等人,2006;读2009;Dunn et al. 2011)定性地描述需要什么水平的岩土数据。几位作者概述了可用于评估岩土工程数据可靠性的方法(Read 2013;Fillion & hadjigeorgou 2013;邓恩2015)。对来自一系列项目的数据进行审查和总结,并尝试量化一些数据的不确定性,并说明这可能对设计和常用设计验收标准产生的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying uncertainty in mining geomechanics design
Uncertainty in mining geomechanics and geotechnical engineering is a broad term that accounts for natural variability, lack of data, and lack of knowledge. Reducing uncertainty is a key component of the mining study process and in managing geomechanical/geotechnical risk. Understanding and reducing uncertainty is also a key activity in the design process to ensure that designs are robust and resilient. A variety of methods are used in geomechanical design including empirical, analytical and numerical modelling. All design methods require inputs, and these are based on data from core logging, mapping, laboratory testing, field observations, and monitoring. This data then must be compiled and interpreted so that meaningful and reliable design inputs with a reliability that is commensurate with the level of design (scoping through to operational) can be derived. This includes the development of the geomechanical or geotechnical model. The uncertainty of the geotechnical model is often described in terms of confidence or reliability. Currently, very little quantitative guidance exists in the literature on assessing the confidence level of geotechnical studies and design, although there have been attempts by various authors (Haile 2004; Haines et al. 2006; Read 2009; Dunn et al. 2011) to qualitatively describe what level of geotechnical data is required. Several authors have outlined methods that could be applied to assess the reliability of geotechnical data (Read 2013; Fillion & Hadjigeorgiou 2013; Dunn 2015). Data from a range of projects are reviewed and summarised and an attempt made to quantify the uncertainty for some data, and illustrate the impact this can have on designs and commonly used design acceptance criteria.
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