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作 者:周明翔 郑祥增 唐炜业 罗伟文 谢圣林 季韬[1] ZHOU Mingxiang;ZHENG Xiangzeng;TANG Weiye;LUO Weiwen;XIE Shenglin;JI Tao(College of Civil Engineering,Fuzhou University,Fuzhou University,Fuzhou,Fujian 350108,China;Transportation and Construction Bureau of Pingtan Comprehensive Experimental Zone,Pingtan,Fujian 350400,China;Fujian Jintong Construction Group Co.,LTD.,Fuzhou 350001,China)
机构地区:[1]福州大学土木工程学院,福建福州350108 [2]福建省平潭综合实验区交通与建设局,福建平潭350400 [3]福建省金通建设集团有限公司,福建福州350001
出 处:《福州大学学报(自然科学版)》2025年第1期69-77,共9页Journal of Fuzhou University(Natural Science Edition)
基 金:国家自然科学基金资助项目(52278248);平潭综合实验区专家工作室郑祥增工作室资助项目(PTZJ202301)。
摘 要:根据最少浆体理论优化机制砂混凝土(MSC)的抗裂性能,采用人工神经网络建立名义水灰比、等效水灰比、粉煤灰掺量、矿渣掺量、石粉掺量、平均浆体厚度与MSC坍落度、抗压强度和氯离子扩散系数的非线性映射关系.利用遗传算法对MSC配合比进行优化,提出和验证基于最少浆体理论与智能算法(人工神经网络和遗传算法)的机制砂混凝土配合比设计方法.研究结果表明,在满足坍落度、28 d抗压强度及氯离子扩散系数设计要求下,优化后的MSC配合比中水泥用量和碳排放减少,实现固废利用的同时降低了混凝土单方造价,其经济效益及环境效益明显.In this paper,the least paste theory was used to optimize the cracking resistance of manufactured sand concrete(MSC).Artificial neural network was used to establish the nonlinear mapping relationship between nominal water-cement ratio,equivalent water-cement ratio,fly ash content,slag content,stone powder content,average paste thickness and the slump,compressive strength and chloride diffusion coefficient of MSC.Genetic algorithm was used to optimize MSC mix proportion.A design method of mix proportion of manufactured sand concrete based on the least paste theory and intelligent algorithm(artificial neural network and genetic algorithm)is proposed and verified.The research result shows that under the condition of meeting the design requirements of slump,28 d compressive strength and chloride ion diffusion coefficient,the optimized MSC mix proportion reduces the amount of cement and carbon emission,and realizes the utilization of solid waste,reduces the cost of concrete,and its economic and environmental benefits are obvious.
关 键 词:机制砂混凝土 配合比设计方法 最少浆体理论 人工神经网络 遗传算法
分 类 号:TU526[建筑科学—建筑技术科学]
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