Department of Electrical Energy, Metals, Mechanical Constructions and Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium.
Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam.
Sci Rep. 2021 Dec 10;11(1):23809. doi: 10.1038/s41598-021-03097-y.
In this paper, a new method in forecasting the horizontal displacement of diaphragm wall (D.W.) for high-rise buildings is introduced. A new stochastic optimizer, called Planet Optimization Algorithm (P.O.A.), is employed to assess how proper finite element (F.E.) simulation is against field data. The process is adopted for a real phased excavation measured at the field. To automatically run the iterative optimization tasks, a source code is constructed directly in the Geotechnical Engineering Software (PLAXIS) by using Python to ensure that the operation between optimization algorithm and F.E. simulations are smooth to guarantee the accuracy of the complex calculation for the soil problem. The proposed process consists of two steps. (1) The parameters will be optimized at the early phases of the excavation. (2) The responses of D.W. displacements are forecasted at the subsequent phases. The aim of the process is to predict the displacements of D.W. of the building from the result of the nearby excavation or to provide early warning about the risks of excavation that may happen under vital phases. The proposed procedure also provides an effective method for optimization-based soil parameters updating in real engineering practice.
本文提出了一种预测高层建筑地下连续墙水平位移的新方法。引入了一种新的随机优化器，称为行星优化算法（Planet Optimization Algorithm，P.O.A.），用于评估有限元（FE）模拟与现场数据的吻合程度。该方法适用于现场实测的真实分阶段开挖过程。为了自动运行迭代优化任务，通过使用 Python 在岩土工程软件（PLAXIS）中直接构建源代码，确保优化算法和 FE 模拟之间的操作顺畅，以保证对复杂土壤问题计算的准确性。所提出的过程包括两个步骤。（1）在开挖的早期阶段优化参数。（2）预测后续阶段地下连续墙位移的响应。该过程的目的是根据附近的开挖结果预测建筑物地下连续墙的位移，或对关键阶段可能发生的开挖风险发出预警。所提出的程序还为实际工程中基于优化的土壤参数更新提供了一种有效的方法。
