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采用刚性聚脲加固的钢筋混凝土柱抗震性能的数值评估

Numerical Evaluation of Seismic Performance of RC Columns Strengthened with Stiff-Type Polyurea.

作者信息

Lee Tae-Hee, Han Soo-Ho, Kim Jang-Ho Jay

机构信息

School of Civil and Environmental Engineering, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.

Foresys Co., Ltd., 26, Seongmisan-ro 1-gil, Mapo-gu, Seoul 03971, Republic of Korea.

出版信息

Materials (Basel). 2025 Apr 17;18(8):1839. doi: 10.3390/ma18081839.

DOI:10.3390/ma18081839
PMID:40333484
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12028632/
Abstract

After developing the experimental database of RC column specimens retrofitted with stiff-type polyurea (STPU), this study implemented STPU in finite-element (FE) modeling. The numerical analysis aimed to evaluate seismic performance factors by establishing a structural analysis model based on the experimental data. The model was calibrated and validated against experimental results, showing consistency in maximum displacement and strain within acceptable deviations. The key findings indicate that the dissipation energy and crack propagation were significantly reduced in reinforced specimens compared to unreinforced ones, demonstrating the effectiveness of STPU and glass fiber-reinforced polyurea (GFPU). The FE model further confirmed that circular specimens exhibited superior reinforcement effects compared to rectangular specimens due to their continuous surface geometry. These results enhance the understanding of STPU's seismic reinforcement capabilities and provide a foundation for its practical application. The study results are discussed in detail in the paper.

摘要

在建立了采用刚性聚脲（STPU）加固的钢筋混凝土柱试件的实验数据库之后，本研究在有限元（FE）建模中应用了STPU。数值分析旨在通过基于实验数据建立结构分析模型来评估抗震性能因素。该模型根据实验结果进行了校准和验证，在可接受的偏差范围内，最大位移和应变表现出一致性。关键研究结果表明，与未加固试件相比，加固试件的耗能和裂缝扩展显著减少，证明了STPU和玻璃纤维增强聚脲（GFPU）的有效性。有限元模型进一步证实，圆形试件由于其连续的表面几何形状，与矩形试件相比表现出更好的加固效果。这些结果加深了对STPU抗震加固能力的理解，并为其实际应用提供了基础。本文详细讨论了研究结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/4e5d85f7ad87/materials-18-01839-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/49de842cf761/materials-18-01839-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/87690951d4ad/materials-18-01839-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/26abdc0fb487/materials-18-01839-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/87bf92ec5171/materials-18-01839-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/cb8f1c59fb35/materials-18-01839-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/a8ce93fcae15/materials-18-01839-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/9489e34c579f/materials-18-01839-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/4e5d85f7ad87/materials-18-01839-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/49de842cf761/materials-18-01839-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/98b346acefc1/materials-18-01839-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/10df053ca6c4/materials-18-01839-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/c8f5d445ffa7/materials-18-01839-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/760e7229a0f2/materials-18-01839-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/87690951d4ad/materials-18-01839-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/26abdc0fb487/materials-18-01839-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/87bf92ec5171/materials-18-01839-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/cb8f1c59fb35/materials-18-01839-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/a8ce93fcae15/materials-18-01839-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/9489e34c579f/materials-18-01839-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/22d3b51e3579/materials-18-01839-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2244/12028632/4e5d85f7ad87/materials-18-01839-g013.jpg

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本文引用的文献

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Predicting the Lateral Load Carrying Capacity of Reinforced Concrete Rectangular Columns: Gene Expression Programming.预测钢筋混凝土矩形柱的侧向承载能力：基因表达式编程
Materials (Basel). 2022 Apr 5;15(7):2673. doi: 10.3390/ma15072673.