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Rock mass redefined: integrating discrete fracture network models and rock mass classification systems

Rock mass redefined: integrating discrete fracture network models and rock mass classification systems
重新定义岩体:集成离散裂缝网络模型和岩体分类系统
批准号:
RGPIN-2019-03925
负责人:
Elmo, Davide
金额:
$2.62万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
翻译
1963年,现代岩土工程之父Karl Terzaghi写道:“我们正在超越我们预测行为后果的能力极限”。55年后,岩石工程设计仍然依赖于经验方法,通过观察得出结论并产生理论。使岩石工程设计具有挑战性的是节理、层面和断层形式的物理不连续的存在,这些物理不连续可能影响斜坡、地下开挖和大坝基础的稳定性。有几种分类系统可以量化岩体的质量,并说明这些不连续面的影响。然而,这些分类系统大多是在20世纪60年代至70年代开发出来的,当时岩石工程项目的规模非常有限。随着大型露天开采接近其经济极限,矿山正在地下更深的地方开发,需要一种新的设计方法,不受对经验表的主观解释和对岩体性质的定性评估的限制。我们相信,我们的研究可以通过更好地了解地质变异性以及岩体行为与不连续面强度/性质之间的关系,从而有助于降低“不可预见”事件的发生程度。离散裂隙网络(DFN)方法将传统的不连续面填图与资源岩土工程和自然灾害调查的新的远程遥感技术相结合,日益成为辅助岩石工程设计的有效工具。与先进的数值分析相结合,基于DFN的岩石工程可以支持更高效的矿山设计,提高作业安全性。我的研究小组介绍了一种分析DFN模型特性的新方法,并提供了网络连通性的度量,这是实现基于DFN的岩体分类和设计方法的关键要素。加拿大的几家岩土咨询公司现在正在使用DFN方法进行岩石工程设计。在这一应用中,我们提出了一项研究计划,以改进和更新岩石分类系统,取消定性测量,并专注于使用新技术来绘制更适合统计分析的关键地质参数(例如,裂缝频率和块体体积)。如果我们想要岩石工程得到发展,并支持现代设计框架,如失败概率分析和风险评估,这是一个关键要求。为了实现这些目标,该提案将寻求为5名高素质人员(HQP)提供资金。这项研究将对改善工程边坡和地下开挖的设计,以及增加DFN工具和概率方法在岩石工程设计中的使用产生重大影响。
英文摘要
In 1963 Karl Terzaghi, the father of modern geotechnical engineering, wrote "we are overstepping the limits of our ability to predict the consequences of our actions". 55 years later, rock engineering design still depends on empirical methods, whereby observations are used to reach conclusions and generate theories. What makes rock engineering design challenging is the presence of physical discontinuities in the form of joints, bedding planes, and faults, which may affect the stability of slopes, underground excavations, and dam foundations. Several classification systems exist to quantify the quality of the rock mass and account for the effects of those discontinuities. However, most of those classification systems were developed in the 1960s-1970s, at a time when the scale of rock engineering projects was much limited. As large open pit operations are approaching their economic limits and mines are being developed deeper underground, a new approach to design is required that is not limited by a subjective interpretation of empirical tables and qualitative assessments of rock mass properties. We believe our research can contribute to reduce the degree of occurrence of "unforeseeable" events, by providing a better understanding of geological variability and the relationship between rock mass behaviour and intensity/nature of the discontinuities. Integrating conventional discontinuities mapping with new long-range remote sensing techniques for resource geotechnics and natural hazard investigations, discrete fracture network (DFN) methods have increasingly become an effective tool to assist with rock engineering design. Coupled with advanced numerical analyses, DFN-based rock engineering can support more efficient mine design and improve operational safety. My research group has introduced a new method that analyse the properties of DFN models, and provides a measure of the network connectivity, which is the key element for implementing a DFN-based approach to rock mass classification and design. Several geotechnical consulting companies in Canada are now using DFN methods for rock engineering design. In this application, we propose a research program to advance and update rock mass classification systems, removing qualitative measurements, and focusing on the use of new technologies to map key geological parameters that are more appropriate for statistical analysis (e.g. fracture frequency and blocks volumes). This is a key requirement if we want rock engineering to evolve and to support modern design frameworks such as the analysis of probability of failure and risk assessment. To meet these objectives, the proposal will seek funding for 5 Highly Qualified Personnel (HQP). The research will have a significant impact with respect to improving the design of engineered slopes and underground excavations, and increasing the use of DFN tools and probability methods in rock engineering design.
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Rock mass redefined: integrating discrete fracture network models and rock mass classification systems
  • 批准号:
    RGPIN-2019-03925
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2022
  • 负责人:
    Elmo, Davide
  • 依托单位:
Rock mass redefined: integrating discrete fracture network models and rock mass classification systems
  • 批准号:
    RGPIN-2019-03925
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2020
  • 负责人:
    Elmo, Davide
  • 依托单位:
A connectivity approach to stochastically simulate physical distancing and to make more accurate predictions of its effectiveness to reduce the spread of the COVID-19 outbreak
  • 批准号:
    554430-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $3.22万
  • 财政年份:
    2020
  • 负责人:
    Elmo, Davide
  • 依托单位:
Rock mass redefined: integrating discrete fracture network models and rock mass classification systems
  • 批准号:
    RGPIN-2019-03925
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2019
  • 负责人:
    Elmo, Davide
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