Study on the Bearing Characteristics of a Novel Inner Support Structure for Deep Foundation Pits Based on Full-Scale Experiments

Traditional internal support systems for deep foundation pits often suffer from issues such as insufficient stiffness, excessive displacement, and large support areas. To address these problems, the authors developed a novel spatial steel joist internal support system. Based on a large-scale field model test, this study investigates the bearing characteristics of the proposed system in deep foundation pits. A stiffness formulation for the novel support system was analytically derived and experimentally validated through a calibrated finite element model. After validation with test results, the effects of different vertical prestressing forces on the structure were analyzed. The results indicate that the proposed system provides significant support in deep foundation pits. The application of both horizontal and vertical prestressing increases the internal forces within the support structure while reducing overall displacement. The numerical predictions of horizontal displacement, bending moment, and the axial force distribution of the main support, as well as their development trends, align well with the model test results. Moreover, increasing the prestressing force of the steel tie rods effectively controls the deformation of the vertical arch support and enhances the stability of the spatial structure. The derived stiffness formula shows a small error compared with the finite element results, demonstrating its high accuracy. Furthermore, the diagonal support increases the stiffness of the lower chord bar support by 28.24%.

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Publication Details

Journal
Buildings
Published
2025-08-15
DOI
https://doi.org/10.3390/buildings15162887
Citations
1
Primary Topic
Geotechnical Engineering and Analysis
Type
article
Field-Weighted Citation Impact
1.30

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article

Study on the Bearing Characteristics of a Novel Inner Support Structure for Deep Foundation Pits Based on Full-Scale Experiments

H. Zhang, Wei Guo, Xingui Zhang, Jianhang Liang et al.
1 citations
Buildings
Geotechnical Engineering and Analysis
1.30
article

Study on the Bearing Characteristics of a Novel Inner Support Structure for Deep Foundation Pits Based on Full-Scale Experiments

H. Zhang, Wei Guo, Xingui Zhang, Jianhang Liang, Wei Han, Yidan Zhang, C. Liang, Yiping Tian, Li’e Yan
article en
1 citations

Abstract

Traditional internal support systems for deep foundation pits often suffer from issues such as insufficient stiffness, excessive displacement, and large support areas. To address these problems, the authors developed a novel spatial steel joist internal support system. Based on a large-scale field model test, this study investigates the bearing characteristics of the proposed system in deep foundation pits. A stiffness formulation for the novel support system was analytically derived and experimentally validated through a calibrated finite element model. After validation with test results, the effects of different vertical prestressing forces on the structure were analyzed. The results indicate that the proposed system provides significant support in deep foundation pits. The application of both horizontal and vertical prestressing increases the internal forces within the support structure while reducing overall displacement. The numerical predictions of horizontal displacement, bending moment, and the axial force distribution of the main support, as well as their development trends, align well with the model test results. Moreover, increasing the prestressing force of the steel tie rods effectively controls the deformation of the vertical arch support and enhances the stability of the spatial structure. The derived stiffness formula shows a small error compared with the finite element results, demonstrating its high accuracy. Furthermore, the diagonal support increases the stiffness of the lower chord bar support by 28.24%.

BuildingsVol. 15(16)
Guangxi University (CN), Technology Holding (United States) (US)
Division of Graduate Education
Openalex Percentile: Top 18%
Geotechnical Engineering and Analysis
1.30
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