산업기술연구 (Journal of Industrial Technology)

  • 제41권1호
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  • Pages.1-6
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  • 2021
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  • 1229-9588(pISSN)
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  • 1598-1371(eISSN)
강원대학교 산업기술연구소 (Kangwon National University, Institute of Industrial Technology)
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인공신경망을 이용한 플라이애시 및 실리카 흄 복합 콘크리트의 압축강도 예측

Prediction of strength development of fly ash and silica fume ternary composite concrete using artificial neural network

  • Fan, Wei-Jie (NingboTech University) ;
  • Choi, Young-Ji (Department of Architectural Engineering, Kangwon National University) ;
  • Wang, Xiao-Yong (Department of Integrated Energy and Infra System, Department of Architectural Engineering, Kangwon National University)
  • 투고 : 2021.09.02
  • 심사 : 2021.10.19
  • 발행 : 2021.10.31
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초록

Fly ash and silica fume belong to industry by-products that can be used to produce concrete. This study shows the model of a neural network to evaluate the strength development of blended concrete containing fly ash and silica fume. The neural network model has four input parameters, such as fly ash replacement content, silica fume replacement content, water/binder ratio, and ages. Strength is the output variable of neural network. Based on the backpropagation algorithm, the values of elements in the hidden layer of neural network are determined. The number of neurons in the hidden layer is confirmed based on trial calculations. We find (1) neural network can give a reasonable evaluation of the strength development of composite concrete. Neural network can reflect the improvement of strength due to silica fume additions and can consider the reductions of strength as water/binder increases. (2) When the number of neurons in the hidden layer is five, the prediction results show more accuracy than four neurons in the hidden layer. Moreover, five neurons in the hidden layer can reproduce the strength crossover between fly ash concrete and plain concrete. Summarily, the neural network-based model is valuable for design sustainable composite concrete containing silica fume and fly ash.

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참고문헌

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