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dc.contributor.authorQingxia Yue
dc.contributor.authorWeina Wang
dc.contributor.authorXin Zhang
dc.date.accessioned2023-11-27T23:09:49Z
dc.date.available2023-11-27T23:09:49Z
dc.date.issued7/12/2023 12:00:00 AM
dc.date.issued2023-07-12
dc.identifier.otherAJRUA6.RUENG-1071.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4293346
dc.description.abstractProbabilistic analysis and time variation model of concrete compressive strength in existing buildings were conducted based on relevant site testing data. The data were collected from rebound hammer (RH) method and core test method. There were 73,840 of RH test data and 4,149 of core test data. First, the data were normalized through dividing by the cube strength, to eliminate the concrete grade effect. The probability distribution analysis showed that the normal distribution is more suitable than the log-normal distribution. Moreover, it was found that the mean value of the core test data was higher than that of the RH data. Further, regression analysis on the data was carried out, and two quadratic functions were adopted to capture the time variation models of the compressive strength based on the RH data, and the core test data, respectively. Furthermore, some more data were obtained by the Genetic algorithm-back propagation (GA-BP) neural network method, and the time variation models were accordingly updated including the new data. Finally, the relationship between the RH model and core test model was discussed, and two approximately linear curves existed from 0 to 30 years and 31 to 60 years. Hopefully, this probabilistic analysis and the time variation model can be helpful in the assessment of the bearing capacity and evaluation of structure reliability in concrete structures.
dc.publisherASCE
dc.titleProbabilistic Analysis and Time Variation Model of Concrete Compressive Strength in Existing Buildings
dc.typeJournal Article
dc.journal.volume9
dc.journal.issue3
dc.journal.titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
dc.identifier.doi10.1061/AJRUA6.RUENG-1071
dc.journal.fristpage04023026-1
dc.journal.lastpage04023026-9
dc.page9
dc.treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2023:;Volume ( 009 ):;issue: 003
dc.contenttypeFulltext


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