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Structural Engineering and Mechanics Volume 74, Number 4, May25 2020 , pages 559-565 DOI: https://doi.org/10.12989/sem.2020.74.4.559 |
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Displacement prediction of precast concrete under vibration using artificial neural networks |
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Gultekin Aktas and Mehmet Sirac Ozerdem
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| Abstract | ||
| This paper intends to progress models to accurately estimate the behavior of fresh concrete under vibration using artificial neural networks (ANNs). To this end, behavior of a full scale precast concrete mold was investigated numerically. Experimental study was carried out under vibration with the use of a computer-based data acquisition system. In this study measurements were taken at three points using two vibrators. Transducers were used to measure time-dependent lateral displacements at these points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using ANNs. Benefiting ANNs used in this study for modeling fresh concrete, mold design can be performed. For the modeling of ANNs: Experimental data were divided randomly into two parts such as training set and testing set. Training set was used for ANN\'s learning stage. And the remaining part was used for testing the ANNs. Finally, ANN modeling was compared with measured data. The comparisons show that the experimental data and ANN results are compatible. | ||
| Key Words | ||
| modeling; artificial neural networks (ANNs); precast concrete mold; compaction of fresh concrete; vibration | ||
| Address | ||
| Gultekin Aktas: Department of Civil Engineering, Dicle University, 21280 Diyarbakir, Turkey Mehmet Sirac Ozerdem: Department of Electrical and Electronics Engineering, Dicle University, 21280 Diyarbakir, Turkey | ||