基于随机森林算法的盾构改良渣土渗透系数预测及工程应用

张文涛; 龚振宇; 令凡琳; 王树英

doi:10.3973/j.issn.2096-4498.2022.11.005

隧道建设 >

2022 , Vol. 42 >Issue 11: 1863 - 1870

DOI: https://doi.org/10.3973/j.issn.2096-4498.2022.11.005

研究与探索

基于随机森林算法的盾构改良渣土渗透系数预测及工程应用

张文涛 ,
龚振宇 ,
令凡琳 ,
王树英

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（1. 云南省滇中引水工程建设管理局昆明分局，云南昆明 650051； 2. 中铁五局集团电务城通工程有限责任公司，湖南长沙 410205； 3. 中南大学土木工程学院，湖南长沙 410075）

张文涛（1978—），男，陕西洋县人，2003年毕业于华北水利水电学院，水利水电工程专业，本科，高级工程师，现从事水利工程技术管理工作。E-mail： 919736277@qq.com。*通信作者：令凡琳， Email： lotusling@csu.edu.cn。

网络出版日期: 2022-12-05

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Prediction and Engineering Application of Permeability Coefficients in Improved Muck of Shield Based on Random Forest Algorithm

ZHANG Wentao ,
GONG Zhenyu ,
LING Fanlin ,
WANG Shuying

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(1.Kunming Branch of Central Yunnan Provincial Water Diversion Project Construction Administration,Kunming 650051,Yunnan, China;2.Electricity Engineering Co.,Ltd. of CREC No.5 Group,Changsha 410205,Hunan,China;3.School of Civil Engineering, Central South University,Changsha 410075,Hunan,China)

Online published: 2022-12-05

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摘要

为解决土压平衡盾构在富水粗粒土地层掘进时，由于盾构渣土渗透性较高而引起螺旋输送机出口处易出现喷涌等风险问题，基于随机森林算法，选取渣土改良参数包括含水率、泡沫注入比、膨润土泥浆注入比以及掘进地层参数土体有效粒径、水力梯度作为模型输入参数，提出一套适用于盾构渣土渗透系数预测的模型。研究结果表明：该模型预测精度较高，渣土渗透系数预测值与实测值均位于同一数量级，且均方误差仅为2.4×10-9 cm/s，拟合决定系数可达0.981 9。依托滇中引水龙泉倒虹吸盾构隧洞工程进行应用，对下穿盘龙江喷涌风险源进行判定，并基于该预测模型给出推荐改良参数。在采用推荐改良参数后，盾构下穿过程中渣土渗透系数满足要求，土舱压力稳定，且对上部桥梁结构影响较小，保障了盾构安全、高效掘进。

关键词： 土压平衡盾构; 渣土改良; 渗透系数; 随机森林; 预测模型

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张文涛 , 龚振宇 , 令凡琳 , 王树英 . 基于随机森林算法的盾构改良渣土渗透系数预测及工程应用[J]. 隧道建设, 2022 , 42(11) : 1863 -1870 . DOI: 10.3973/j.issn.2096-4498.2022.11.005

Abstract

When earth pressure balance shields tunneling in waterrich coarsegrained grounds, muck spewing often occurs due to the high permeability of the muck. As a result, a model for predicting the permeability coefficient of shield muck is proposed based on the random forest algorithm. First, conditioning parameters, such as the water content, foam injection ratio, bentonite slurry injection ratio, the effective particle size of soil, and the hydraulic gradient are collected as input paraters of the model. The results reveal that while the predicted and the measured values are in the same order of magnitude, the root mean square error is 2.4×10-9 cm/s, and the fitting determination coefficient reaches 0.981 9, indicating good prediction accuracy of the model. Then, the model was applied to the Longquan shield tunnel project in Central Yunnan, China, to determine the risk of water spewing during the shield undercrossing the Panlong river. Consequently, recommended conditioning parameters were provided, which accounted for the recorded achievements like the relativelylow permeability coefficient of improved muck, stable chamber pressure, small influence on the upper bridge structure, and safe/efficient shield tunneling.

Key words： earth pressure balance shield; soil conditioning; permeability coefficient; random forest; prediction model

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