Life Prediction of Desert Sand PVA-ECC in Salt Freezing Environment

In order to predict the life of Desert Sand PVA-ECC in chloride environment and freeze-thaw cycle coupling, the average influence value (MIV) method was used to screen the input variables of the prediction model. Finally, the fiber volume, fly ash, silica fume and freeze-thaw cycles are selected as...

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Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2020-09, Vol.567 (1), p.12026
Main Authors: Huifang, Hou, Min, Yan
Format: Article
Language:English
Subjects:
Back propagation networks
Deserts
Fiber volume fraction
Fly ash
Freeze thaw cycles
Freeze-thaw durability
Freeze-thawing
Freezing
Life prediction
Mechanical properties
Neural networks
Prediction models
Sand
Silica
Silica fume
Silicon dioxide
Storage modulus
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Summary:In order to predict the life of Desert Sand PVA-ECC in chloride environment and freeze-thaw cycle coupling, the average influence value (MIV) method was used to screen the input variables of the prediction model. Finally, the fiber volume, fly ash, silica fume and freeze-thaw cycles are selected as input variables, and the "4-13-1" error reverse transmission neural network model with relative dynamic elastic modulus as the output value is established. Finally, the GA-BP neural network is used to predict the life of the specimens which have not been destroyed by 300 freeze-thaw cycles. Finally, the best fiber volume fraction of salt freeze resistant life is 1%. Only after 475 freeze-thaw cycles.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/567/1/012026