欢迎访问《硅酸盐通报》官方网站,今天是
分享到:

硅酸盐通报 ›› 2022, Vol. 41 ›› Issue (9): 3091-3099.

• 水泥混凝土 • 上一篇    下一篇

考虑材料参数和应力水平的氯离子扩散系数多因素预测模型

余波1, 黄俊辉1, 汪加梁1, 秦荷成1,2   

  1. 1.广西大学土木建筑工程学院,南宁 530004;
    2.广西建设职业技术学院, 南宁 530007
  • 收稿日期:2022-04-28 修回日期:2022-07-03 出版日期:2022-09-15 发布日期:2022-09-27
  • 通讯作者: 秦荷成,副教授。E-mail:544724379@qq.com
  • 作者简介:余 波(1982—),男,博士,教授。主要从事混凝土耐久性、结构可靠度与结构抗震研究。E-mail:gxuyubo@gxu.edu.cn
  • 基金资助:
    国家自然科学基金(51668008);广西杰出青年科学基金(2019GXNSFFA245004);广西自然科学基金(2018GXNSFAA281344);广西研究生教育创新计划(YCSW2021026)

Multi-Factor Prediction Model for Chloride Diffusion Coefficient Considering Material Parameters and Stress Level

YU Bo1, HUANG Junhui1, WANG Jialiang1, QIN Hecheng1,2   

  1. 1. School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China;
    2. Guangxi Polytechnic of Construction, Nanning 530007, China
  • Received:2022-04-28 Revised:2022-07-03 Online:2022-09-15 Published:2022-09-27

摘要: 针对传统氯离子扩散系数预测模型无法综合考虑材料参数和外荷载影响而导致预测精度不高的缺陷,建立了综合考虑材料参数和应力水平的氯离子扩散系数多因素预测模型。首先基于311组快速氯离子迁移测试法的试验数据,定量分析了水胶比、砂率、矿物掺合料(粉煤灰、矿粉、硅灰)掺量等材料参数以及应力水平对氯离子扩散系数的影响规律;然后结合两阶段分析方法和逐步回归分析方法,建立了综合考虑材料参数和应力水平的氯离子扩散系数多因素预测模型;最后通过与传统预测模型和试验数据的对比,验证了该模型的有效性与精确性,其模型可决系数为0.90。

关键词: 混凝土, 氯离子扩散系数, 材料参数, 应力水平, 逐步回归分析, 预测模型

Abstract: In order to overcome the shortcomings of low prediction accuracy for traditional model that cannot effectively consider the effect of material parameters and external load, a multi-factor prediction model for chloride diffusion coefficient was proposed by considering material parameters and stress level. Firstly, the influences of water-binder ratio, sand ratio, mineral admixture (fly ash, slag, silica fume) and stress level on diffusion coefficient were investigated based on 311 sets of rapid chloride migration test data. Then a multi-factor prediction model for chloride diffusion coefficient was established by using the two-phase analysis method and stepwise regression method. Finally, the effectiveness and accuracy of the prediction model were verified by comparing with traditional models and experimental data. The coefficient of determination of the model is 0.90.

Key words: concrete, chloride diffusion coefficient, material parameter, stress level, stepwise regression, prediction model

中图分类号: