应用H-S模型进行巨型深基坑的开挖优化分析

杜佐龙; 王士峰; 刘祥勇; 郭锋效

应用H-S模型进行巨型深基坑的开挖优化分析 English Version

(1. 中国建筑第八工程局有限公司技术中心上海 200120；2. 同济大学土木工程博士后流动站，上海 200092；3. 中国建筑第八工程局有限公司土木公司路桥分公司，上海 200120；4. 无锡市轨道交通发展有限公司，江苏无锡 214131；5. 中国建筑第八工程局有限公司天津公司，天津 310450）

详细信息

作者简介:
杜佐龙 (1979– )，男，湖北仙桃人，博士后，从事地下深基础工程的研究。

中图分类号: TU473
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出版历程
- 收稿日期: 2012-11-12
- 发布日期: 2012-11-12

Optimization of earthwork for a super-large deep excavation based on hardening-soil constitutive model

(1. Technology Center, China Construction Eighth Engineering Division, Shanghai 200120, China; 2. The Postdoctoral Research Station of Civil Engineering, Tongji University, Shanghai 200092, China; 3. Road & Bridge Branch Division, China Construction Eighth Engineering Division, Shanghai 200120, China; 4 Wuxi Rail Transit Development Co., Ltd. Wuxi 214131, China; 5 TianJin Branch Division, China Construction Eighth Engineering Division, Tianjin 310450, China)

摘要

摘要: 天津滨海新区于家堡金融起步区一期工程，基坑面积约为11万m2，普遍开挖深度约为13-14m，只使用了一道钢筋混凝土支撑，这对整个基坑支护体系的稳定性控制提出了很高的要求，在开挖前就需要对基坑在开挖过程中的变形性状进行预测，判定其对周边环境的影响。本文使用基于Hardening-Soil模型的有限元方法，对比不同开挖步时基坑开挖对周边环境的影响，分析证实了优化方案的可行性，得到的结论可供类似工程参考。
- 单支撑巨型深基坑 /
- Hardening-soil本构模型 /
- 有限元法 /
- 开挖优化
Abstract: The first planning excavation of Yujiapu Financial Zone in Binhai New District of Tianjin has an area of about 110000 m2, and the depth of the excavation is commonly 13～14 m. In this excavation, only one level of concrete internal bracing is applied, so it has high requirements for the control of stability. The prediction of deformation is necessary to determine the impact of the surrounding environment during the process of excavation. Based on the hardening-soil constitutive model and the finite element method, the influence of different steps of excavation on the environment is analyzed. The conclusions show the validity of this optimization and have certain reference value for the relevant excavation projects.
- super-large deep excavation with single internal bracing /
- hardening-soil constitutive model /
- finite element method /
- excavation optimization.

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参考文献(11)

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