自然潮差环境下混凝土氯离子峰值浓度的时变性

Time-dependency of peak chloride concentration in concreteunder marine tidal environment

基于自然潮差环境下的现场暴露试验,研究了混凝土氯离子峰值浓度的时变性以及影响因素。测试了7个暴露时间,5种不同水灰比的普通混凝土、5种水胶比均为0.50的不同掺合料混凝土共10组混凝土内的自由氯离子浓度,并采用三点拟合法得到较为准确的对流区深度及对应的氯离子峰值浓度;然后,分析了水灰比及掺合料对混凝土氯离子峰值浓度时变性的影响,建立了其时变模型,并研究了氯离子峰值浓度的稳定趋势;最后,分析了峰值浓度的时变性对预测混凝土氯离子浓度的影响。结果表明,暴露时间和水灰比是影响混凝土中氯离子峰值浓度的重要因素,且掺合料减缓了混凝土中峰值浓度的增加速度;相对较短时间的暴露试验得到的混凝土峰值浓度时变模型,可以预测较长暴露时间后混凝土中峰值浓度;峰值浓度有逐渐趋于稳定的趋势,其稳定时间受水灰比和掺合料影响,加入掺合料缩短了稳定时间;考虑峰值浓度时变性可更为准确地预测不同深度处混凝土中的氯离子浓度。

Field exposure test based on marine tidal environment,the time-dependent and influencing factors of peak chloride concentration in concrete were studied.After 7 exposure times,the free chloride concentrations in 10 concrete groups,including ordinary concrete with 5 different water-binder ratios and concrete with 5 different admixtures and 0.50 water-binder ratio were tested,and the more accurate convection zone depth and corresponding peak chloride concentration were obtained by three-point fitting method.Then,the influence of water-binder ratio and admixtures on time-dependency of peak chloride concentration in concrete were analyzed,the time-dependent model was established,and the stable trend of peak chloride concentration was studied.Finally,the influence of time-dependency of peak concentration on the prediction of chloride concentration in concrete was analyzed.The results show that the exposure time and water-cement ratio are important influencing factors on the peak chloride concentration,and admixtures slow down the increase of peak concentration.The time-dependent model of peak chloride concentration obtained from relatively short-term exposure test can predict the peak concentration in concrete after long-term exposure.The peak concentration gradually tends to be stable,and the stability time is affected by the water-binder ratio and admixtures,and the addition of admixtures shortens the stability time.Considering the time-dependency of peak concentration,the chloride concentration in concrete at different depths can be predicted more accurately.