水下隧道涌水灾害风险评价与预测  

Assessment and Prediction of Water Gushing Disaster Risk in Underwater Tunnel

作　　者：江时雨 陈建宏[1] 李涛[1] 高玉翠[1] 

机构地区：[1]中南大学资源与安全工程学院,湖南长沙410083

出　　处：《中国安全科学学报》2013年第12期101-106,共6页China Safety Science Journal

基　　金：国家自然科学基金资助(51374242);中南大学自由探索计划项目(2012QNZT028)

摘　　要：为减小水下隧道涌水对人员安全及隧道施工的不利影响,需要对水下隧道涌水进行风险评价和预测。基于文献调查和专家评价方法,结合工程实际,利用层次分析法(AHP)构建水下隧道涌水灾害评价体系,从地质因素、水文条件及隧道工程3个方面提出11个评价指标。采用物元分析法和AHP法,进行合成确定各评价指标权重。以BP神经网络作为评价工具,构建涌水灾害综合评价预测模型。以某水下隧道为例,进行评价和预测分析。结果表明,基于物元分析和AHP的BP神经网络评价模型预测误差不大于3.2%。To reduce the influence of underwater tunnel water gushing on personnel saiety and tunnel construction, the risk of underwater tunnel water gushing should be valuated and predicted. Based on liter- ature investigation and expert evaluation, combined with engineering practice, an evaluation of system wa- ter gushing disaster risk in underwater tunnel was established, 11 evaluation indexes were put forward from the geological factors, hydrological conditions and tunnel engineering three aspects. Index weights of syn- thesis were determined using AHP. With BP neural network as assessment tool, a comprehensive evalua- tion of water disaster prediction model was built. The model was applied to a certain underwater tunnel taken as an example. The results show that prediction error of BP neural network evaluation model based on matter-element analysis and AHP is not greater than 3.2%.

关 键 词：水下隧道 涌水 物元分析法 层次分析法(AHP) BP网络 风险评价 

分 类 号：X913.4[环境科学与工程—安全科学]