硅酸盐通报2025，Vol.44Issue(1)：81-89,9.DOI:10.16552/j.cnki.issn1001-1625.2024.0817
基于数字图像技术的UHPC-NC界面特征识别及粘结性能研究
UHPC-NC Interface Feature Recognition and Bonding Performance Based on Digital Image Technology
摘要
Abstract
In order to more accurately analyze the influences of ultra high performance concrete-normal concrete(UHPC-NC)interface features on bonding strength,this paper quantitatively characterized the three-dimensional feature information of the substrate surface based on digital image technology,and studied the influences of different substrate surface roughness and coarse aggregate area on the interface bonding strength.The results indicate that there is a strong correlation between the substrate surface roughness and the area of coarse aggregate,and the correlation coefficients between the contour arithmetic mean deviation Ra and standard deviation Std of the obtained profiles and the coarse aggregate area Sc are 0.838 and 0.855,respectively.The substrate surface roughness increases with the increase of coarse aggregate area.The failure load of the interface group specimen treated with high-pressure water jet on the substrate surface increases by 143.0％to 240.0％compared to the smooth interface group specimen,while the high-pressure water jetting treatment interface group specimen could obtain 53.4％to 89.6％of the overall specimen failure load.The surface characteristics of NC substrate are key factors affecting the interface bonding strength.The characteristic parameters of the substrate surface roughness,the profile arithmetic mean deviation Ra,standard deviation Std and coarse aggregate area Sc,are positively correlated with the interface bonding strength,and their correlation coefficients are 0.935,0.927 and 0.959,respectively.The interface bonding strength increases with the increase of substrate surface roughness and coarse aggregate area.关键词
UHPC-NC/数字图像技术/特征识别/定量化表征/粘结强度Key words
UHPC-NC/digital image technology/feature recognition/quantitative characterisation/bonding strength分类
水利科学引用本文复制引用
张江江,孙文,鲜雪蕾,李瑞泽,展淑敏,王甲泽..基于数字图像技术的UHPC-NC界面特征识别及粘结性能研究[J].硅酸盐通报,2025,44(1):81-89,9.基金项目
国家自然科学基金(51868041,52360031,22JR5RA338) （51868041,52360031,22JR5RA338）
