Article(id=1319222810904482472, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1319222668956643677, articleNumber=null, orderNo=null, doi=10.14062/j.issn.0454-5648.20220694, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1661443200000, receivedDateStr=2022-08-26, revisedDate=1663776000000, revisedDateStr=2022-09-22, acceptedDate=null, acceptedDateStr=null, onlineDate=1792456828094, onlineDateStr=2026-10-20, pubDate=1684512000000, pubDateStr=2023-05-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792456828094, onlineIssueDateStr=2026-10-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792456828094, creator=13701087609, updateTime=1792456828094, updator=13701087609, issue=Issue{id=1319222668956643677, tenantId=1146029695717560320, journalId=1263187385517883426, year='2023', volume='51', issue='5', pageStart='1091', pageEnd='1372', issueExtLink='null', onlineDate='null', pubDate='1684512000000', pubDateStr='2023-05-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1792456794251, creator='13701087609', updateTime=1792456976356, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1319223432827490920, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1319222668956643677, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1319223432827490921, tenantId=1146029695717560320, journalId=1263187385517883426, issueId=1319222668956643677, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1344, endPage=1354, ext={EN=ArticleExt(id=1319222811164529321, articleId=1319222810904482472, tenantId=1146029695717560320, journalId=1263187385517883426, language=EN, title=Durability Assessment and Life Prediction of Concrete by Entropy Weight Method, columnId=1263922769897599102, journalTitle=Journal of the Chinese Ceramic Society, columnName=Research Articles, runingTitle=null, highlight=null, articleAbstract=

Wet-dry cycles of fly ash (FA) and cellulose fiber double-doped concrete with sulphate in Nazi Gorge water conservancy pivot project were investigated. The durability value (D), a durability index that can comprehensively reflect the mass, compressive strength and splitting strength of concrete were established based on an entropy weight method. The effects of sulphate mass fraction and fly ash admixture on the D were analyzed. A grey model-back propagation (GM-BP) neural network was constructed to reveal the time-varying law of the D. The results show that the D can reflect the effects of sodium sulphate mass fraction and fly ash admixture on the durability of concrete. At 180 day, the D loss is proportional to sodium sulphate solution mass fraction within 10% (mass fraction). The GM-BP neural network can predict the time-varying law of the D under salt intrusion-wet and dry cycles more accurately than the GM.

, authors=Yuan QIN¹, Gao LV¹, Ke GUAN², Heng ZHOU³, authorsList=Yuan QIN, Gao LV, Ke GUAN, Heng ZHOU, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1319222811399410346, articleId=1319222810904482472, tenantId=1146029695717560320, journalId=1263187385517883426, language=CN, title=基于熵权法的混凝土耐久性评价及寿命预测, columnId=1263922770220560512, journalTitle=硅酸盐学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

以纳子峡水利枢纽工程为背景，进行了粉煤灰、纤维素纤维双掺混凝土硫酸盐干湿循环试验。基于熵权法建立了可以综合反映混凝土质量、抗压强度和抗劈拉强度的耐久性指标耐久性值（D），分析了硫酸钠溶液质量分数和粉煤灰掺量对D值的影响，并构建了Grey Models—Back Propagation（GM-BP）神经网络，用以揭示混凝土D值的时变规律，得到了不同条件下混凝土的预期寿命。结果表明：D值可以反映出硫酸钠溶液质量分数和粉煤灰掺量对混凝土耐久性的影响。180 d时，混凝土D值损失在10%（质量分数）内与硫酸钠溶液质量分数成正比；粉煤灰最佳掺量在10%掺量梯度下为20%；在数据量较小时，GM-BP神经网络相比于GM模型可以更加精确地预测混凝土在盐侵—干湿循环下D值的时变规律。

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QIN Yuan (1983-), male, Ph.D., Professor. E-mail: qinyuan@xaut.edu.cn

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QIN Yuan (1983-), male, Ph.D., Professor. E-mail: qinyuan@xaut.edu.cn

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覃源（1983—），男，博士，教授。

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覃源（1983—），男，博士，教授。

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