基于贝叶斯理论的钢筋再生混凝土梁受剪承载力预测模型

(1.东莞职业技术学院 商贸学院,广东 东莞 523808; 2.东莞理工学院 生态环境与建筑工程学院,广东 东莞 523808; 3.南京工业大学 土木工程学院,江苏 南京 211816; 4.中建七局(上海)有限公司,上海 201800)

再生混凝土无腹筋梁; 受剪承载力; 贝叶斯模型修正

Prediction model for shear capacity of reinforced recycled aggregate concrete beam based on Bayesian theory
TUO Su1, YU Yong2, CHEN Wenguang3, GUO Xiongwei4, WANG Zhongdong4, XU Jinjun3

(1.School of Commerce and Trade, Dongguan Polytechnic, Guangdong Dongguan 523808, China; 2.School of Environment and Civil Engineering, Dongguan Univ. of Tech., Guangdong Dongguan 523808, China; 3.College of Civil Engineering, Nanjing Tech University, Nanjing 211816, China; 4.China Construction Seventh Engineering Division(Shanghai)Co., Ltd., Shanghai 201800, China)

reinforced recycled aggregate concrete beam without stirrups; shear capacity; Bayesian model updating

DOI: 10.15986/j.1006-7930.2022.02.011

备注

受剪承载力是开展钢筋再生混凝土结构设计和修复加固所依据的重要性能指标之一,发展其计算理论具有较强的科学与实践意义.然而受制于有限的试验数据及再生混凝土材性离散较大等原因,现行规范在预估此类构件受剪承载力时,往往简单对混凝土强度进行折减,套用普通钢筋混凝土构件的计算公式.该法通常存在精度低和稳定性差等问题.为此,首先尝试建立包含206根再生混凝土无腹筋梁的抗剪试验数据库,用以评估现存规范与经验计算公式的准确性及可靠性; 紧接着,选定预测效果较好的ACI318-2014规范和学者Zsutty建议公式为先验模型,基于贝叶斯统计理论对先验模型和试验信息进行统计推断,构建起无箍筋钢筋再生混凝土梁受剪承载力计算概率模型; 随后通过未知参数的筛选剔除,修正得到后验模型.研究结果表明:贝叶斯方法充分融合了先验模型的完备性及大量试验数据的准确性,能更精准地预测再生混凝土无腹筋梁的受剪强度.
Shear capacity is one of the important performance indicators for the design and repair of reinforced recycled aggregate concrete(RAC)structures, so it is of great scientific and practical significance to develop its calculation method. At present stage, due to the shortage of test results and the high variability for the RAC's mechanical property, most specifications still applies calculation formulas of conventional concrete beam to estimate that capacity by simply reducing the RAC's strength, which usually has problems such as low accuracy and poor stability. In view of this, a shear test database containing 206 reinforced RAC beams without stirrups was first established to evaluate the accuracy and reliability of existing specifications and empirical formulas. Then, the ACI318-2014 code with good prediction effect and the formula suggested by scholar Zsutty were selected as the prior model, and the prior model and test information were statistically inferred based on Bayesian statistical theory to build the probability model for calculating shear capacity of reinforced RAC beams without stirrups. Finally, Bayesian parameter culling process was adopted to eliminate the secondary influential factors, and new predictive expressions were acquired. The results showed that the Bayesian method fully integrated the completeness of the prior model and the accuracy of a large number of test data, and could predict the reinforced RAC beam's shear strength more accurately.