Response Analysis of Deep Foundation Excavation and Dewatering on Surface Settlements
Autor(en): |
Xian Li
Tingguo Zhou Yixian Wang Junling Han Yanqiao Wang Fang Tong Delong Li Jinmei Wen |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Advances in Civil Engineering, Januar 2020, v. 2020 |
Seite(n): | 1-10 |
DOI: | 10.1155/2020/8855839 |
Abstrakt: |
Accurate prediction of surface settlements is a primary concern when deep excavations were carrying out under the water table in urban environments for the safety of the work site. The sedimentation deformation due to deep excavation of foundation pit and dewatering occurs as a result of coupling action of the two factors. The study is aimed at revealing the coupling ground response to the two factors and developing empirical correlations for estimating ground deformations. Taking a deep foundation pit of a metro station as an example, surface settlement estimations were calculated by analytical formulas and numerical models. The settlement results by analytical formulas under excavation and dewatering conditions were added linearly to the total settlements. And three-dimensional coupling numerical models were established by applying commercial software (GMS and MIDAS) to investigate the interaction impact of excavation and dewatering on the sedimentation deformation. Comparing with monitoring data, numerical simulation results match well with the monitoring data. Furthermore, an empirical surface subsidence correlation equation was developed by the polynomial fitting to illustrate the effect contribution on the total surface settlement of foundation excavation and dewatering. |
Copyright: | © Xian Li et al. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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