| 要旨 |
Rheological properties of shotcrete mortar largely affect the conveying as well as the placing process of shotcrete. Conventional fitting techniques fail to give a universal prediction of rheology from given parameters of mixing such as water cement ratio, elapsed time, etc. This research is to find the correlation between rheological properties and material parameters of shotcrete mortar using neural network.. Asimple network was developed to predict rheology from water by cement ratio, sand by cement ratio, filling ratio and time.
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