UHPC空心方桩抗弯性能及承载力预测研究_《混凝土与水泥制品》杂志社

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UHPC空心方桩抗弯性能及承载力预测研究

Study on the prediction of flexural performance and bearing capacity of UHPC hollow square piles

2024年第7期

超高性能混凝土（UHPC）；空心方桩；抗弯性能；有限元分析

Ultra-high performance concrete(UHPC); Hollow square pile; Flexural property; Finite element analysis

2024年第7期

10.19761/j.1000-4637.2024.07.048.06

江苏省自然科学基金资助项目（BK20210925）；江苏省重点研发计划（社会发展）资助项目（BE2021681）。

高子晴1，宗钟凌1，2，3，*，谢青海1，2，骆辉1，王卓群1，卢浩宇1，赖斌1

1.江苏海洋大学土木与港海工程学院，江苏连云港 222005；2.江苏省海洋工程基础设施智能建造工程研究中心，江苏连云港 222002；3.江苏省海洋资源开发研究院，江苏连云港 222002

高子晴1，宗钟凌1，2，3，*，谢青海1，2，骆辉1，王卓群1，卢浩宇1，赖斌1

高子晴,宗钟凌,谢青海,等.UHPC空心方桩抗弯性能及承载力预测研究[J].混凝土与水泥制品,2024(7):48-53.

GAO Z Q,ZONG Z L,XIE Q H,Study on the prediction of flexural performance and bearing capacity of UHPC hollow square piles[J].China Concrete and Cement Products,2024(7):48-53.

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摘要：采用超高性能混凝土（UHPC）制备了空心方桩试件，研究了不同钢纤维掺量（1.5%、2.0%、2.5%）及空腔灌注C30普通混凝土对试件抗弯性能的影响，并基于2.0%钢纤维掺量，建立了有限元模型，在此基础上开发了APPM参数化插件，通过改变试件的长径比、壁厚比得到了大量样本数据，预测了不同长径比及壁厚比对试件抗弯承载力的影响。结果表明：随着钢纤维掺量的增加，试件的抗弯性能提高，空腔灌注C30普通混凝土对试件的极限抗弯承载力具有提高作用；随着长径比与壁厚比的增加，试件的抗弯承载力呈下降趋势；有限元模拟结果与试验结果一致性较好；训练的机器学习模型可有效预测试件的抗弯极限承载力；长径比对试件的抗弯承载力影响，最大占比达到了81.7%。 Abstract: The hollow square pile was prepared by using ultra-high performance concrete (UHPC), and the effects of different steel fiber content (1.5%, 2.0%, 2.5%) and hollow poured C30 ordinary concrete on the flexural performance of specimens were studied, and the finite element model of specimens was established based on the content of 2.0% steel fiber. A large number of sample datas were obtained by changing the wall-to-thickness ratio and the length-diameter ratio, and the effects of which on the flexural bearing capacity of pile foundation were studied and predicted. The results show that with the increase of steel fiber content, the bending performance of the specimens improves, and the injection of C30 ordinary concrete into the cavity has an improving effect on the ultimate bending bearing capacity of the specimens. With the increase of the ratio of length to diameter and wall thickness, the flexural bearing capacity of the specimen decreases. The simulation results are in good agreement with the test results. The trained machine learning model can effectively predict the ultimate bending capacity of the specimens, and the influence of the length-diameter ratio on the flexural bearing capacity of specimens is more significant, accounting for 81.7%.

英文名 : Study on the prediction of flexural performance and bearing capacity of UHPC hollow square piles

刊期 : 2024年第7期

关键词 : 超高性能混凝土（UHPC）；空心方桩；抗弯性能；有限元分析

Key words : Ultra-high performance concrete(UHPC); Hollow square pile; Flexural property; Finite element analysis

刊期 : 2024年第7期

DOI : 10.19761/j.1000-4637.2024.07.048.06

文章编号 :

基金项目 : 江苏省自然科学基金资助项目（BK20210925）；江苏省重点研发计划（社会发展）资助项目（BE2021681）。

作者 : 高子晴1，宗钟凌1，2，3，*，谢青海1，2，骆辉1，王卓群1，卢浩宇1，赖斌1

单位 : 1.江苏海洋大学土木与港海工程学院，江苏连云港 222005；2.江苏省海洋工程基础设施智能建造工程研究中心，江苏连云港 222002；3.江苏省海洋资源开发研究院，江苏连云港 222002

高子晴1，宗钟凌1，2，3，*，谢青海1，2，骆辉1，王卓群1，卢浩宇1，赖斌1

高子晴,宗钟凌,谢青海,等.UHPC空心方桩抗弯性能及承载力预测研究[J].混凝土与水泥制品,2024(7):48-53.

GAO Z Q,ZONG Z L,XIE Q H,Study on the prediction of flexural performance and bearing capacity of UHPC hollow square piles[J].China Concrete and Cement Products,2024(7):48-53.

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摘要

参数

结论

参考文献

引用本文

Abstract: The hollow square pile was prepared by using ultra-high performance concrete (UHPC), and the effects of different steel fiber content (1.5%, 2.0%, 2.5%) and hollow poured C30 ordinary concrete on the flexural performance of specimens were studied, and the finite element model of specimens was established based on the content of 2.0% steel fiber. A large number of sample datas were obtained by changing the wall-to-thickness ratio and the length-diameter ratio, and the effects of which on the flexural bearing capacity of pile foundation were studied and predicted. The results show that with the increase of steel fiber content, the bending performance of the specimens improves, and the injection of C30 ordinary concrete into the cavity has an improving effect on the ultimate bending bearing capacity of the specimens. With the increase of the ratio of length to diameter and wall thickness, the flexural bearing capacity of the specimen decreases. The simulation results are in good agreement with the test results. The trained machine learning model can effectively predict the ultimate bending capacity of the specimens, and the influence of the length-diameter ratio on the flexural bearing capacity of specimens is more significant, accounting for 81.7%.

关键词:

the

试件

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specimens

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