首页> 外文期刊>KSCE journal of civil engineering >Risk Assessment Model for Water and Mud Inrush in Deep and Long Tunnels Based on Normal Grey Cloud Clustering Method
【24h】

Risk Assessment Model for Water and Mud Inrush in Deep and Long Tunnels Based on Normal Grey Cloud Clustering Method

机译:基于正常灰云聚类法的深长隧道水,泥浆涌入风险评估模型

获取原文
获取原文并翻译 | 示例
       

摘要

In terms of the frequent occurrence and much trouble in governance of the disaster caused by water and mud inrush in deep and long tunnels, the risk assessment model based on normal grey cloud clustering method was proposed. Taking the Jigongling Tunnel of Fanba Expressway as an example, firstly the evaluation target was divided into 8 clustering indices and 4 grey categories according to the grey clustering method. In order to avoid the defects that the traditional whitenization weight functions could not give a good description of system's randomness and ambiguity, the cloud model was introduced to improve it. Then the whitenization weight values were discretized by using the one-dimensional forward cloud generator to simulate the uncertainties in engineering, and the normal grey cloud whitenization weight functions were established. Afterwards, combined with the engineering data of Jigongling Tunnel collected on site, the clustering weight of each clustering index was analyzed under specific engineering and the clustering coefficient of the target was determined. Lastly the risk of water and mud inrush in Jigongling Tunnel was evaluated using the model. The results, which showed that the risk of water and mud inrush in target D-1, D-2 and D-3 was respectively medium, extremely high and high, were compared with the excavation data. The two coincided with each other well which indicated that the model had a certain engineering value and could provide reference for related engineering.
机译:针对深长隧道水,泥突水灾害的频发和治理中的麻烦,提出了一种基于常规灰云聚类的风险评估模型。以范坝高速公路鸡公岭隧道为例,首先根据灰色聚类方法将评价指标分为8个聚类指标和4个灰色类别。为了避免传统的白化权重函数不能很好地描述系统的随机性和歧义性的缺陷,引入了云模型对其进行了改进。然后使用一维前向云发生器模拟工程中的不确定性,离散化白化权重值,并建立了正常的灰云白化权重函数。然后结合现场采集的鸡公岭隧道工程数据,根据具体工程对各聚类​​指标的聚类权重进行分析,确定目标的聚类系数。最后,利用该模型对鸡公岭隧道水,泥浆涌入的风险进行了评估。结果表明,与开挖数据相比,目标D-1,D-2和D-3分别发生水和泥石流的风险中等,极高和极高。两者吻合得很好,表明该模型具有一定的工程价值,可为相关工程提供参考。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号