Prediction of Jacking Force in Vertical Tunneling Projects Based on Neuro-Genetic Models

Xin-Jiang Wei,Gang Wei,Yu Shi,Xiao Wang,Cheng-Wei Zhu

doi:10.3390/jmse9010071

Abstract

The vertical tunneling method is an emerging technique to build sewage inlets or outlets in constructed horizontal tunnels. The jacking force used to drive the standpipes upward is an essential factor during the construction process. This study aims to predict the jacking forces during the vertical tunneling construction process through two intelligence systems, namely, artificial neural networks (ANNs) and hybrid genetic algorithm optimized ANNs (GA-ANNs). In this paper, the Beihai hydraulic tunnel constructed by the vertical tunneling method in China is introduced, and the direct shear tests have been conducted. A database composed of 546 datasets with ten inputs and one output was prepared. The effective parameters are classified into three categories, including tunnel geometry factors, the geological factor, and jacking operation factors. These factors are considered as input parameters. The tunnel geometry factors include the jacking distance, the thickness of overlaying soil, and the height of overlaying water; the geological factor refers to the geological conditions; and the jacking operation factors consist of the dead weight of standpipes, effective overburden soil pressure, effective lateral soil pressure, average jacking speed, construction hours, and soil weakening measure. The output parameter, on the other hand, refers to the jacking force. Performance indices, including the coefficient of determination (R2), root mean square error (RMSE), and the absolute value of relative error (RE), are computed to compare the performance of the ANN models and the GA-ANN models. Comparison results show that the GA-ANN models perform better than the ANN model, especially on the RMSE values. Finally, parametric sensitivity analysis between the input parameters and output parameter is conducted, reaching the result that the height of overlaying water, the average jacking speed, and the geological condition are the most effective input parameters on the jacking force in this study.

Highlights

The vertical tunneling method (VTM) is an emerging approach to build vertical hydraulic tunnels to the inlets or outlets in sewage systems in China
There are only a few studies related to the jacking force of the VTM available to date [1,2,3]
To gain insight into the effective factors that influence the jacking force, Wang et al have conducted case research about the vertical tunneling project, concluding that the jacking force is affected by factors such as the average jacking speed, the jacking distance, the geological conditions, and the effective overburden soil pressure [3]

Summary

Introduction

The vertical tunneling method (VTM) is an emerging approach to build vertical hydraulic tunnels to the inlets or outlets in sewage systems in China. In the VTM construction process, the standpipes are jacked upward from the horizontal tunnel to the seabed by applying jacking force through four jacks in the constructed horizontal tunnel. It is crucial to predict the jacking force during the VTM construction. There are only a few studies related to the jacking force of the VTM available to date [1,2,3]. To calculate the jacking force during the vertical tunneling process in advance, Wang et al regarded standpipes as reverse piles and utilized the Meyerhof foundation theory to compute the maximum jacking force [1,2]. To gain insight into the effective factors that influence the jacking force, Wang et al have conducted case research about the vertical tunneling project, concluding that the jacking force is affected by factors such as the average jacking speed, the jacking distance, the geological conditions, and the effective overburden soil pressure [3]

Objectives

Methods

Results

Conclusion