结算(财务)
组分(热力学)
可靠性(半导体)
工程类
标杆管理
发掘
控制(管理)
土木工程
岩土工程
计算机科学
人工智能
付款
业务
营销
功率(物理)
万维网
物理
热力学
量子力学
作者
Limao Zhang,Xianguo Wu,Wenli Liu,Mirosław J. Skibniewski
出处
期刊:Journal of Performance of Constructed Facilities
[American Society of Civil Engineers]
日期:2019-10-01
卷期号:33 (5)
被引量:15
标识
DOI:10.1061/(asce)cf.1943-5509.0001322
摘要
A simulation-hybrid approach that incorporates artificial intelligence (AI), simulation, and experiment components is proposed to cope with the excessive surface settlement induced by tunneling excavation for the discovery of the optimal strategy. The AI component aims to predict the tunnel-induced surface settlement to detect whether the estimated settlement exceeds the control standard. The simulation component aims to investigate the complex tunnel–soil interaction for benchmarking multiple response alternatives. The experiment component aims to validate the effectiveness of the identified optimal response strategy in a natural setting environment. A shallow tunnel case in China is used to testify the effectiveness of the proposed approach. Results indicate that (1) the continuous grouting scheme for ground treatment is identified as the optimal strategy to deal with the excessive settlement potential and (2) the implementation in the actual practice further confirms that the continuous grouting scheme can reduce the surface settlement by 48.75%. The novelty of this approach lies in (1) the body of knowledge by developing a proactive approach to simulate, predict, and mitigate tunnel-induced settlement under uncertainty and (2) the state of practice by providing new insight into the control of excessive settlement potential with high accuracy and reliability.
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