富水砂卵石深基坑承压水预测及突涌评估研究  

Study on Intelligent Prediction and Surge Warning of Confined Water in Deep Foundation Pit with Pebble Sand Rich in Water

作　　者：赵勇博 马永政 ZHAO Yongbo;MA Yongzheng(School of Architecture and Traffic Engineering,Ningbo University of Technology,Ningbo 315211,China)

机构地区：[1]宁波工程学院建筑与交通工程学院,浙江宁波315211

出　　处：《宁波工程学院学报》2024年第3期70-77,共8页Journal of Ningbo University of Technology

基　　金：岩土力学与工程国家重点实验室开放基金课题项目(Z020020);国家自然科学基金项目(52008214)。

摘　　要：为探究富水砂卵石深基坑承压水量测定及抗突涌能力,以福州地铁2号线金屿站深基坑为研究对象,通过理论解析和现场降水实验,对基坑抗突涌水参数进行估计,并引入人工智能算法对未能试验测定的部分进行预测;同时,基于预测值、实测值以及理论计算参数,构建多元信息融合突涌评估模型。研究结果表明:基于理论解析和降水试验提出的涌水量智能预测方法的计算精度满足要求;多个指标融合评估突涌风险等级为I级,基坑处于安全状态。该方法可以为类似工程问题提供有益借鉴。In order to explore the water bearing capacity measurement and surge resistance ability of the deep foundation pit with water-rich sand and gravel,the deep foundation pit of Jinyu Station of Fuzhou Metro Line 2 was taken as the research object,and the anti-surge water parameters of the foundation pit were estimated through theoretical analysis and on-site precipitation experiment.The artificial intelligence algorithm is introduced to predict the untested part.In addition,based on the predicted value,measured value and theoretical calculation parameters,the multi-information fusion surge evaluation model is constructed.The results show that the calculation accuracy of the intelligent prediction method based on theoretical analysis and precipitation test meets the requirements.The result of fusion of multiple indexes evaluated the risk level of surge as level I,and the foundation pit was in a safe state.This method can provide useful reference for similar engineering problems.

关 键 词：突涌水 深基坑 智能预测 富水砂卵石地层 预警方法 

分 类 号：U231[交通运输工程—道路与铁道工程]