盾构掘进模式影响下地层位移与掘进参数演变规律及智能控制方法

Improper control of shield operation will cause large ground deformation or collapse which lead to stoppage of shield machine or endanger the adjacent structures. Except reinforcing the ground, how to minimize the ground deformation through adjusting the shield boring mode and optimizing the boring parameters is a critical unsolved problem in the field of shield tunnelling. Based on scaled model test and coupled analysis of discrete element-finite difference method, this project will fist investigate the effect of shield boring mode on the performance of advancing parameters and ground movement. The tunneling mechanics and the characteristics of critical supporting pressure at the excavation face will be studied when the shield heading through different boring modes (full chamber or partial empty chamber). The effects of different shield cutter patterns on the earth pressure balance mechanism and ground movement will be examined as well. Then, by collecting comprehensive shield advancing parameters in the field, deep learning will be used to mining the multilayer nonlinear correlation between the shield advancing parameters and ground movements, considering the effects of EPB shield boring modes, the neural network will be optimized by a genetic algorithm to obtain a best solution. Furthermore, an intelligent method for predicting the EPB advancing parameters will be proposed based on the allowable settlement controlling theory. This work will provide theoretical basis for intelligent control of advancing parameters and ground movement and hence it has wide application prospect for the safety of tunnelling in complex ground with EPB.

土压平衡盾构掘进控制不当易引起地层变形过大或沉陷，导致盾构停机或损害邻近建（构）构物。除加固地层外如何通过调整掘进模式与优化掘进参数实现地层变形控制仍是尚未解决的盾构施工关键科学问题。本项目结合模型试验和离散元-有限差分耦合数值模拟研究土压平衡盾构掘进模式影响下掘进参数与地层位移的演变规律，揭示满仓与非满仓不同掘进模式下土压平衡盾构掘进力学传递机制，明确不同土舱渣土比例下的开挖面临界支护压力特征，探究不同掘进模式影响下盾构刀盘形式对土压平衡机理和地层位移的影响。结合工程实例大数据，采用深度学习神经网络算法挖掘不同掘进模式影响下盾构掘进参数与地层位移之间的多层网络非线性关联规则，基于遗传算法进行优化获取全局最优解，建立基于容许沉降控制理论的土压平衡盾构掘进参数智能预测方法。预期成果可为复杂环境下土压平衡盾构掘进参数与地层位移智能控制提供理论依据，对指导土压平衡盾构安全掘进具有广泛应用前景。

城市盾构隧道施工诱发地表塌陷、临近结构物损伤与盾构掘进模式选择、掘进参数控制息息相关。本项目针对土压平衡盾构掘进控制不当引起地层变形过大或沉降方面的关键问题，开发了基于离散元-有限差分(PFC3D-FLAC3D)的耦合分析，建立了考虑刀盘切削和出渣过程的盾构隧道掘进精细化分析模型，系统研究了不同掘进模式下全断面均匀地层和上软下硬地层条件下开挖面稳定性规律，探讨了渣土改良对土仓压力传递性和开挖面地层响应的影响；构建了包含地层与地表环境信息的精细化地质模型与数值模型，通过数值模拟与现场测试，建立了隧道几何参数、地层参数、盾构掘进参数和地表最大沉降之间的非线性网络关系，提出不同掘进模式下盾构关键掘进参数和地层响应特征；在长沙地铁3号线烈士公园站~丝茅冲站区间盾构精细化地质模型的构建基础上，厘清了盾构掘进参数与其影响因素的非线性特征，构建了盾构施工各影响因素与地表沉降以及掘进参数之间的人工智能特征网络关系，提出了基于目标沉降控制的复杂环境下土压平衡盾构掘进参数的非线性优化控制方法。项目成果可为规避城市盾构隧道施工引发的地面塌陷安全事故提供理论依据，提升人们对城市地下工程的安全认识。