摘要
采用海水、海砂分别替代淡水、河砂制备了海水海砂混凝土(SSC),研究了耐碱玻璃纤维(GF)掺量和粉煤灰掺量对SSC抗压强度和劈裂抗拉强度的影响,并基于灰色关联理论建立了双因素影响下的抗压强度和劈裂抗拉强度预测模型。结果表明:与普通混凝土相比,SSC的7 d抗压强度较高,28 d抗压强度较低;单掺粉煤灰或GF时,随着相应掺量的增加,试件的抗压强度和劈裂抗拉强度基本先增大后减小;与单掺粉煤灰相比,单掺GF对SSC抗压强度和劈裂抗拉强度的提高效果较好;复掺GF与粉煤灰时,当GF、粉煤灰的掺量分别为0.24%、10%时,对SSC抗压强度和劈裂抗拉强度的提高效果最显著;建立的NSGM(1,3)灰色预测模型的精度较高,SSC的28 d抗压和劈裂抗拉强度的预测值与试验值的平均相对误差分别仅为2.969%和0.708%。
Seawater and sea sand were used to replace fresh water and river sand to prepare seawater sea sand concrete(SSC).The effects of alkali resistant glass fiber(GF)content and fly ash content on the compressive strength and splitting tensile strength of SSC were studied,and the prediction models for compressive strength and splitting tensile strength under the influence of two factors were established based on grey correlation theory.The results show that compared with ordinary concrete,SSC has a higher 7 d compressive strength and a lower 28 d compressive strength.When adding fly ash or GF alone,with the increase of fly ash or GF content,the compressive strength and splitting tensile strength of the specimen basically increase first and then decrease.Compared with the single addition of fly ash,the single addition of GF has a better effect on improving the compressive strength and splitting tensile strength of SSC.When GF and fly ash are mixed together,the most significant improvement effect on the compressive strength and splitting tensile strength of SSC is achieved when the content of GF and fly ash is 0.24%and 10%respectively.The established NSGM(1,3)grey prediction model has high accuracy,and the average relative errors between the predicted and experimental values of 28 d compressive strength and splitting tensile strength of SSC are only 2.969%and 0.708%respectively.
作者
关国浩
王学志
贺晶晶
刘华新
韩刚
GUAN Guohao;WANG Xuezhi;HE Jingjing;LIU Huaxin;HAN Gang(School of Civil and Architectural Engineering,Liaoning University of Technology,Jinzhou 121001,China;Power China Northwest Engineering Co.,Ltd.,Xi’an 710100,China)
出处
《混凝土与水泥制品》
2023年第6期48-53,59,共7页
China Concrete and Cement Products
基金
辽宁省教育厅基金项目(JJL201915402)
中国电建集团西北勘测设计研究院工程实验监测院科技项目(SYY-KJ-2020-02)。
关键词
海水海砂混凝土
耐碱玻璃纤维
粉煤灰
力学性能
灰色预测模型
Seawater sea sand concrete
Alkali resistant glass fiber
Fly ash
Mechanical property
Grey prediction model
