基于粒子群算法的深基坑支撑轴力优化研究

doi:10.13722/j.cnki.jrme.2023.0825

Abstract
Figure/Table
References (0)
Related Citation (15)

Download: PDF (611 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Currently，the effect of the axial force servo(compensation) system on the deformation control of soft soil foundation pits is inconsistent，and its advantages have not been fully exerted. Therefore，based on the active control method of the lateral deformation of the foundation pit，the particle swarm algorithm based on swarm intelligence is innovatively applied to solve the optimization problem of the supporting axial force，and the optimization method of the supporting axial force considering the construction process of the foundation pit is established. In addition，the calculation program of the vertical elastic foundation beam method based on the particle swarm algorithm is developed to obtain the reasonable supporting axial force that can meet the strength and stiffness requirements of the supporting structure in the dynamic and multi-condition changing foundation pit construction. The results show that the particle swarm algorithm introduced in this paper can simply and efficiently solve the optimization problem of the supporting axial force under dynamic and multiple constraint conditions involving the internal force and deformation of the retaining structure and the bearing capacity of the support，providing a reference for the design of deep foundation pits based on active control in the future.

Key words： foundation pit engineering active control particle swarm optimization axial force optimization

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	SUN Jiuchun
	WU Shengwei
	CAO Hong

Cite this article:

SUN Jiuchun,WU Shengwei,CAO Hong. Research on optimization of support axial force of deep foundation pit based on particle swarm optimization algorithm[J]. , 2024, 43(S2): 4000-4008.

URL:

https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2023.0825 OR https://rockmech.whrsm.ac.cn/EN/Y2024/V43/IS2/4000

[1]	孙九春，白廷辉. 地铁基坑钢支撑轴力伺服系统设置方式研究[J]. 地下空间与工程学报，2019，15(增1)：195-204.(SUN Jiuchun，BAI Tinghui. Study on the setting method of steel supporting axial force servo system for subway foundation pit[J]. Chinese Journal of Underground Space and Engineering，2019，15(Supp.1)：195-204.(in Chinese))
[2]	孙九春，白廷辉，廖少明. 基于支撑轴力相干性的深基坑变形主动控制[J]. 地下空间与工程学报，2021，17(2)：12.(SUN Jiuchun，BAI Tinghui，LIAO Shaoming. Active control of deep foundation pit deformation based on coherence of supporting axial force[J]. Chinese Journal of Underground Space and Engineering，2021，17(2)：12.(in Chinese))
[3]	周勇，杨红坡. 基坑主动变形控制-轴力伺服系统应用探讨[J]. 山西建筑，2023，49(1)：96-100.(ZHOU Yong，YANG Hongpo. Discussion on the application of active deformation control and axial force servo system in foundation pit[J]. Shanxi Architecture，2023，49(1)：96-100.(in Chinese))
[4]	徐煌华. 地铁车站深基坑土方开挖及支撑优化设计研究[硕士学位论文][D]. 包头：内蒙古科技大学，2022.(XU Huanghua. Research on optimization design of earth excavation and support for foundation pit of subway station[M. S. Thesis][D]. Baotou：Inner Mongolia University of Science and Technology，2022.(in Chinese))
[5]	曹虹，孙九春. 软土基坑钢支撑伺服系统轴力的确定方法研究[J]. 建筑施工，2019，41(5)：754-758.(CAO Hong，SUN Jiuchun. Study on determination method of axial force of steel support servo system in soft soil foundation pit[J]. Building Construction，2019，41(5)：754-758.(in Chinese))
[6]	董如意. 元启发式优化算法研究与应用[博士学位论文][D]. 吉林：吉林大学，2019.(DONG Ruyi. Research and application of meta-heuristic optimization algorithms[Ph. D. Thesis][D]. Jilin：Jilin University，2019.(in Chinese))
[7]	KENNEDY J，EBERHART R C. Particle swarm optimization[C]// Proceedings of ICNN'95-nternational Conference on Neural Networks. [S. l.]：[s. n.]，1995：1 942-1 948.
[8]	JABEEN H，JALIL Z，BAIG A R. Opposition based initialization in particle swarm optimization(O-PSO)[C]// Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference. [S. l.]：[s. n.]，2009：2 047-2 052.
[9]	PLEVRIS V，PAPADRAKAKIS M. A hybrid particle swarm—gradient algorithm for global structural optimization[J]. Computer-Aided Civil and Infrastructure Engineering，2011，26(1)：48-68.
[10]	CHEN Z，CAO H，YE K，et al. Improved particle swarm optimization- based form-finding method for suspension bridge installation analysis[J]. Journal of Computing in Civil Engineering，2015，29(3)：04014047.