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Study On Hybrid Fiber Concrete Property And Prodict The Concrete Strength Based On BP Neural Network

Posted on:2009-03-07Degree:MasterType:Thesis
Country:ChinaCandidate:Y LiuFull Text:PDF
GTID:2132360272975143Subject:Materials Science and Engineering
Abstract/Summary:PDF Full Text Request
Fiber reinforced concrete is heterogeneous material, it is widespread used in engineering, but single fiber is limited to strength and toughness, if incorporating different performance fibers, the cracking resistance and strength will be increased. So, incorporating hybrid fiber is an effective way to preparation high-quality cement base composite materials.By orthogonal experiment, range analysis and variance analysis are used to study the workability,hysical mechanical performance and lasting quality, main factor influence to hybrid fiber concrete performance is analysised, and synergy effect,strengthen mechanism are researched. regression analysis the slump,divergence,pressive strength,rupture strength and splitting strength by SPSS; use the collecting date , hybrid fiber concrete strength is predicted. This paper has some results as follow:①Priority adulterate fiber in favor of dispersibility, can increase the workability;②Under the experiment condition, adultering hybrid fiber can increase strength 10%-20%, but the slope rises is less than stell fiber concrete.③Hybrid fiber can increase rupture strength and splitting strength, the slope rises reach 20%;④Hybrid fiber mixed into concrete can reduce concrete shrinkage, comparing with black concrete, hybrid fiber concrete restrained shrinkage 60%, until 28 days, the restraining still reach 40%-50%.⑤Hybrid fiber mixed into conrete can also resist permeability of chloride ion, osmotic coefficient between mekralon concrete and stell-fiber concrete, and is higer 85% than adultering mekralon, and lower 2% than adultering stell-fiber concrete.⑥BP network can predict strength of hybrid fiber reinforced concrete, and the module reach 95% precision.
Keywords/Search Tags:Hybrid Fiber, Orthogonal Desig, Synergy Effect, SPSS, Back-Propagation Network
PDF Full Text Request
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