The influence caused by grouting defects to the anchoring performance and failure mode of large-diameter grouting sleeve connections
编号:99 访问权限:仅限参会人 更新:2025-08-07 19:27:42 浏览:58次 口头报告

报告开始:2025年08月15日 19:40(Asia/Shanghai)

报告时间:10min

所在会场:[S1] 8月15日晚上 研究生分会 [S1-5] 研究生分会场五

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摘要
To study the influence of grouting defects on the anchoring performance and failure modes of large-diameter grouting sleeves, defect size (40 mm, 60 mm, and 80 mm) and defect location (middle, end) were selected as influencing factors for combination. Twenty-four grouting sleeve connectors with diameter 40 mm HRB400E steel bars as anchoring bars were designed and fabricated. Uniaxial tensile tests were conducted. A finite element model of large-diameter grouting sleeves was established based on the tests. The simulation results were verified with the test results. A Support Vector Machine (SVM) model database with steel bar diameter, defect size, and defect location as variables was established. The SVM algorithm was used to predict the failure modes. The results show that the specimens mainly exhibit two failure modes: steel bar fracture and steel bar pull-out. When the defect length is 40 mm, the steel bar pull-out failure occurs in large-diameter grouting sleeves with diameter 40 mm steel bars. The increase in defect length leads to a reduction in the ultimate bearing capacity and ultimate displacement of the specimens. When the defect length is within 60 mm, the reduction in both is small. When the defect length reaches 80 mm, both decrease significantly. Under the same defect size, end defects have a greater impact on the anchoring performance of large-diameter grouting sleeves than middle defects. The finite element model can effectively simulate the test results. The model exhibits the same failure mode as the specimens. The maximum error in ultimate load is 5.9%. The load-displacement curves show good agreement. The prediction accuracy of the SVM algorithm for the failure modes of grouting sleeves with middle defects and end defects both reaches about 90%. Meanwhile, the algorithm performs better in predicting the failure modes of grouting sleeves with middle defects than those with end defects. This algorithm provides an intelligent diagnostic tool for predicting the failure modes of grouting sleeves.
关键词
bridge engineering; large diameter grouting sleeve; uniaxial tensile tests; grouting defects; numerical simulation; support vector machine
报告人
代雨漫
硕士研究生 长安大学

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重要日期
  • 会议日期

    08月15日

    2025

    08月17日

    2025

  • 08月08日 2025

    初稿截稿日期

  • 08月16日 2025

    报告提交截止日期

  • 08月17日 2025

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