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作 者:党帅翰 王子振 卢金马 余波[1,2,3] DANG Shuaihan;WANG Zizhen;LU Jinma;YU Bo(School of Civil Engineering and Architecture,Guangxi University,Nanning 530004,China;Key Laboratory of Engineering Disaster Prevention and Structural Safety of Ministry of Education,Nanning 530004,China;Guangxi Key Laboratory of Disaster Prevention and Engineering Safety,Nanning 530004,China)
机构地区:[1]广西大学土木建筑工程学院,广西南宁530004 [2]工程防灾与结构安全教育部重点实验室,广西南宁530004 [3]广西防灾减灾与工程安全重点实验室,广西南宁530004
出 处:《混凝土》2023年第7期16-20,共5页Concrete
基 金: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资助项目(YCSW2021026)。
摘 要:为了克服传统临界氯离子浓度(Ccr)计算模型由于考虑因素不全面导致计算精度较低的问题,研究建立了一种综合考虑环境条件和材料参数影响的Ccr多因素计算模型。首先基于374组混凝土中钢筋脱钝Ccr的试验数据,分析了水胶比、胶凝材料种类和环境条件对Ccr的影响规律;继而分两个阶段进行多元非线性回归分析,分别确定了环境条件和胶凝材料种类对Ccr的修正系数;最后与已有模型以及实测试验值进行了对比分析,验证了该模型的计算精度。分析表明,随着水胶比的增大,临界氯离子浓度逐渐降低;与全浸泡环境相比,干湿循环条件下的临界氯离子浓度更低;与普通硅酸盐水泥混凝土相比,硅灰、粉煤灰、矿渣的掺入会使Ccr降低;与已有模型相比,该模型由于综合考虑了环境条件和材料参数的影响,预测精度较高。In order to overcome the disadvantages of low computation accuracy of traditional models due to inadequacy of influence factors,a multi-factor calculation model considering the influence of environmental conditions and material parameters was developed.Firstly,based on the experimental data of 374 sets of critical chloride content,the influences of water-binder ratio,cementing material type and environmental conditions were analyzed.Then the correction coefficients of environmental conditions and binder types on critical chloride content were proposed respectively by means of two-stage nonlinear regression analysis.Finally,the effectiveness and applicability of the proposed model were verified by comparing with the experimental data and existing formula.The analysis shows that the critical chloride content decreases gradually with the increase of water-to-binder ratio.Comparing with full immersion environment,critical chloride content under dry-wet cycle conditionis lower.The critical chloride content of ordinary Portland concrete is larger than those of concrete mixed with silica fume,fly ash,and slag.In comparison to the existing model,the prediction accuracy of this model is higher due to the comprehensive consideration of environmental conditions and material parameters.
分 类 号:TU528.01[建筑科学—建筑技术科学]
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