为了研究工业钢渣等体积取代粗骨料对混凝土力学及耐久性能的影响,设置不同钢渣取代率、水灰比以及混凝土强度等级,共制作144块试件,测试钢渣混凝土力学性能及抗冻与抗碳化性能。结果表明:钢渣取代率增加会导致顶面与底面碳化深度差距变大,其中G-0.45-100相差最大,为53.4%。同时,相同龄期下,钢渣混凝土强度更高、抗冻性能更好,钢渣取代率为100%,水灰比为0.45的钢渣混凝土28 d立方体抗压强度较同等级普通混凝土抗压强度提高13%,劈裂抗拉强度提高12.6%,抗折强度提高7.1%。SEM试验发现,与普通骨料相比,钢渣与水泥石的界面过渡区(ITZ)更加致密,界面结构受冻融循环影响较小,界面粘结程度更好。通过数据多元回归分析以及最小二乘法建立钢渣粗骨料混凝土抗压强度数值模型与冻融损伤模型,拟合精度较好。
Abstract
To investigate the impact of equal volume replacement of coarse aggregate by industrial steel slag stone on the mechanical and durability properties of concrete, we produced 144 specimens with varying steel slag replacement ratio, water-cement ratio, and concrete strength grade to test the mechanical properties, frost resistance, and carbonation resistance of the specimens. The results indicate that the greater the steel slag replacement rate, the larger the difference in carbonization depth between the top surface and the bottom surface. G-0.45-100 (here 0.45 represents the water-cement ratio and 100 means that the replacemen ratio is 100%) exhibited the largest difference, at 53.4%. Moreover, steel slag concrete demonstrates better strength and frost resistance at the same age. At a steel slag replacement rate of 100%, the 28-day compressive strength of steel slag concrete with a water-cement ratio of 0.45 increased by 13% compared with that of ordinary concrete. The splitting tensile strength and the flexural strength increased by 12.6% and 7.1% respectively. SEM test revealed that the interface transition zone (ITZ) of steel slag and cement stone was denser than that of ordinary aggregate, less affected by freeze-thaw cycles, and exhibited superior interface bonding. Additionally, through multiple regression analysis and the least square method, we established a numerical model for compressive strength and a freeze-thaw damage model of steel slag coarse aggregate concrete with good fitting accuracy.
关键词
钢渣混凝土 /
力学性能 /
抗冻性能 /
抗碳化性能 /
微观分析 /
数值模型
Key words
steel slag concrete /
mechanical properties /
freezing resistance /
carbonation resistance /
microscopic analysis /
numerical model
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基金
国家自然科学基金项目(51868061,52368024); 内蒙古自然科学基金项目(2020MS05071,2022LHMS05011)
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