基于有限调查数据的顶板结构力学行为和失稳风险评估新方法

IF 6.5 3区 工程技术 Q1 ENGINEERING, GEOLOGICAL
Jiazeng Cao, Tao Wang, Yingying Huang, Bin Zhu, Ruilin Li, Guoqing Zhou
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引用次数: 0

摘要

摘要如何利用有限的调查数据对顶板工程失效进行分析是一个具有挑战性的问题。本文提出了一种新的顶板力学结构风险分析方法。首先介绍了Copula理论,给出了多维高斯Copula参数的构造方法。其次,提出了以E、ν、c、φ为不确定变量求解顶板结构力学特性和失稳风险的Copula方法。第三,基于全国192个顶板组的调查数据,分析讨论了Copula力学参数对顶板结构破坏概率的影响。该评价方法可以利用多种Copula函数模拟正、负相关结构,为利用有限的调查数据阐明顶板结构的力学特性和失稳风险提供了有效途径。结果表明:顶板结构的力学破坏主要发生在底部;随着力学参数相关性的增加,机械结构的失效概率显著降低。在正相关参数和负相关参数的模拟中,高斯Copula和No.16 Copula分别使顶板的破坏概率最小。关键词:基金资助:国家自然科学基金[批准号:42371133和42372329],煤炭开采与清洁利用国家重点实验室(中国煤炭科学研究院)开放基金[批准号:2021-CMCU-KF019],高寒干旱区矿山地质环境恢复技术创新中心开放基金[批准号:HHGCKK2205],自然资源部丘陵山区地质灾害防治重点实验室(福建省地质灾害防治重点实验室)开放基金[批准号:FJKLGH2023K003]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel evaluation methodology for mechanical behaviour and instability risk of roof structure using limited investigation data
ABSTRACTHow to use limited investigation data to analyse the failure of roof engineering is a challenging problem. In this paper, a novel risk analysis method for the mechanical structure of a roof is proposed. Firstly, the Copula theory is presented and the construction method of multidimensional Gaussian Copula parameters is given. Secondly, a Copula method of the mechanical characteristics and instability risk of roof structure with E, ν, c and φ as uncertain variables is proposed. Thirdly, based on the investigation data of 192 roof groups in China, the influence of Copula mechanical parameters on the failure probability of the roof structure is analysed and discussed. This new evaluation methodology can use various Copula functions to simulate the positive and negative correlation structures, which provides an effective way to clarify the mechanical characteristics and instability risk of roof structure using limited investigation data. The results show that the mechanical failure of the roof structure is mainly at the bottom. As the correlation of mechanical parameters increases, the failure probability of the mechanical structure decreases significantly. In the simulation of positive and negative correlation parameters, Gaussian Copula and No.16 Copula, respectively, make the roof have the smallest failure probability.KEYWORDS: Mechanical behaviourinstability riskroof structurereliabilityfailure probability Additional informationFundingThis research was supported by the National Natural Science Foundation of China [grant numbers 42371133 and 42372329], the Open Fund of State Key Laboratory of Coal Mining and Clean Utilization (China Coal Research Institute) [grant number 2021-CMCU-KF019], the Opening Fund of Technology Innovation Center for Mine Geological Environment Restoration in the Alpine and Arid Regions [grant number HHGCKK2205], and the Opening Fund of Key Laboratory of Geohazard Prevention of Hilly Mountains, Ministry of Natural Resources (Fujian Key Laboratory of Geohazard Prevention) [grant number FJKLGH2023K003].
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来源期刊
CiteScore
8.70
自引率
10.40%
发文量
31
期刊介绍: Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.
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