Research on dynamic variable evaluation model of geological risk assessment for rail transit

WU Zhiyi; GAO Yan; YUAN Quan; LI Wenlong

doi:10.13471/j.cnki.acta.snus.2020.02.005

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Research on dynamic variable evaluation model of geological risk assessment for rail transit

更新时间：2023-12-11

- Research on dynamic variable evaluation model of geological risk assessment for rail transit
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 59, Issue 2, Pages: 34-47(2020)
- 作者机构：
  
  1. 中山大学地球科学与工程学院,广东,广州,510275
  2. ．广东省地球动力作用与地质灾害重点实验室,广东,广州,510275
  3. 广州地铁设计研究院股份有限公司,广东,广州,510010
- 作者简介：
- 基金信息：
- DOI：10.13471/j.cnki.acta.snus.2020.02.005
  CLC：
- Published：2020，
  
  Published Online：25 March 2020，
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WU Zhiyi, GAO Yan, YUAN Quan, et al. Research on dynamic variable evaluation model of geological risk assessment for rail transit. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 59(2):34-47(2020)
DOI：

WU Zhiyi, GAO Yan, YUAN Quan, et al. Research on dynamic variable evaluation model of geological risk assessment for rail transit. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 59(2):34-47(2020) DOI： 10.13471/j.cnki.acta.snus.2020.02.005.

摘要

轨道交通作为城市交通的生命线，其健康状态评价日益重要。近年来，隧道工程健康状态评价模型多针对于公路隧道、山岭隧道或者轨道交通隧道的运营阶段，尚缺少轨道交通隧道设计、施工阶段的地质风险评价。针对轨道交通隧道地质风险评价，通过调查研究，辨析出11个一级地质风险源与40个二级风险辨识因子，以及各因子的风险判定标准，将风险分为了微、弱、中、强四个等级；并基于BP神经网络赋权法和乘积标度赋权法对风险因子进行了组合赋权，进而建立了针对轨道交通隧道不良地质风险的模糊可变评价模型；将时间因素集加入模糊可变评价模型，实现了轨道交通隧道全生命周期的地质风险动态评估。最后，利用广州某拟建轨道交通线路初步的勘察数据进行了模型检验，验证了模型的可靠性。

Abstract

As the lifeline of urban traffic

the health evaluation of rail transit has become increasingly important. In recent years

the models to estimate the health of tunnel engineering was mainly concentrated on highway tunnels

mountain tunnels or the operation stage of rail transit tunnel. It is still lack of models to assess the geological risk in the design and construction stages of rail transit. Based on a large number of literatures and standards

a risk criteria including 11 geological risk sources and 40 identification indexes was set up

in which four risk levels

i.e.

small

weak

medium and strong

was utilized to evaluate the overall geological risk. The weights of each index were determined by BP neural network and more flexible multiplication scale method. Then

a fuzzy variable evaluation model for geological risk in rail transit tunnel was established. The time factor set was also added into the fuzzy variable evaluation model to realize the dynamic evaluation of geological risk which can help to estimate the risk during the whole life of rail transit. Finally

the model was proved by the calculating results based on the preliminary geological data of a proposed rail transit line in Guangzhou. The risk levels evaluated by the model were consistent with the insitu measurement and geological survey.

关键词

轨道交通隧道动态模糊可变评价模型BP神经网络乘积标度法地质风险

Keywords

rail transit tunneldynamic fuzzy variable evaluation modelBP neural networkmultiplication scale methodgeological risk

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