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Advances in Concrete Construction Volume 15, Number 4, April 2023 , pages 269-286 DOI: https://doi.org/10.12989/acc.2023.15.4.269 |
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Simulating the performance of the reinforced concrete beam using artificial intelligence |
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Yong Cao, Ruizhe Qiu and Wei Qi
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| Abstract | ||
| In the present study, we aim to utilize the numerical solution frequency results of functionally graded beam under thermal and dynamic loadings to train and test an artificial neural network. In this regard, shear deformable functionally-graded beam structure is considered for obtaining the natural frequency in different conditions of boundary and material grading indices. In this regard, both analytical and numerical solutions based on Navier's approach and differential quadrature method are presented to obtain effects of different parameters on the natural frequency of the structure. Further, the numerical results are utilized to train an artificial neural network (ANN) using AdaGrad optimization algorithm. Finally, the results of the ANN and other solution procedure are presented and comprehensive parametric study is presented to observe effects of geometrical, material and boundary conditions of the free oscillation frequency of the functionally graded beam structure. | ||
| Key Words | ||
| AdaDelta, vibration; atificial intelligence (AI); functionally graded beams; numerical analysis; optimizations | ||
| Address | ||
| (1) Yong Cao, Wei Qi: School of Rail Transit, Chengdu Vocational & Technical College of Industry, Chengdu 610200, Sichuan, China; (2) Ruizhe Qiu: School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China. | ||
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