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Analysis And Research On The Factors Affecting The Elastic Modulus Of C50 Concrete Used In Yunnan Highway

Posted on:2017-01-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y B ChenFull Text:PDF
GTID:2272330488464209Subject:Architecture and Civil Engineering
Abstract/Summary:PDF Full Text Request
As one of the indexes of prestressed concrete tension control, elastic modulus has an vital effect on prestressed concrete members and quality of the integrated structure. The existing calculation formula of elastic modulus in national norms only applies to the standard period of 28 days. But due to the lack of direct ways to judge the elastic modulus and the restrictions on experimental conditions, most of the transportation engineerings will adopt compressive strength as the only way to judge the tension time of prestressed concrete, ignoring the effects from elastic modulus. In addition to this, the quality of concrete cannot be easily guaranteed because of the highly regional raw materials used in transportation engineerings, thus set a higher demand for the testing of elastic modulus of high performance concrete.With a regression analysis on the experimental data of C50 concrete used in many Yunnan Highways, this article has found that the major factors effecting the elastic modulus of C50 concrete is aggregate, especially the coarse aggregate. Besides, by experimenting to make concrete in 54 groups with 243 specimens, it has analyzed the correlativity between multiple aggregate performance index and elastic modulus of concrete. In the end, by introducing the nonlinear fitting of the relationship between those effecting factors and Momentum BP Neural Network which contains a variable practice rate, it has worked out a relation curve which will provide an intuitive way to judge the elastic modulus. The results show that:(1) The elastic modulus of concrete in different period is mainly effected by different factors. Both compressive strength and elastic modulus of natural sand concrete are inferior to that of manufactured sand concrete while there is a distinct linear relation between compressive strength and elastic modulus.(2) BP Neural Network’s nonlinear fitting of the relationship between elastic modulus and other effecting factors are better than a linear regression. The curve of effecting factors and elastic modulus showed from the nonlinear fitting is quiet reasonable, leaving a significant guidance on the estimation of the elastic modulus of C50 concrete.
Keywords/Search Tags:C50 concrete, Elastic modulus, Aggregate, Factors, Neural Network
PDF Full Text Request
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