Journal of the Architectural Institute of Korea (대한건축학회논문집)

Architectural Institute of Korea (대한건축학회)
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Predicting Shear Performance of Reinforced Concrete Beams Through Crack Data and Neural Network Modeling

균열 정보와 신경망 모델을 이용한 철근콘크리트 보의 전단 성능 예측 연구

  • Kwon, Ah-Young (Dept. of Architectural Engineering, Inha University) ;
  • Eng Lybundith (Dept. of Architectural Engineering, Inha University) ;
  • Kim, Changhyuk (Dept. of Architectural Engineering, Inha University)
  • Received : 2023.07.13
  • Accepted : 2023.09.14
  • Published : 2023.10.30
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Abstract

This study aims to predict how reinforced concrete beams perform under shear stress using Artificial Neural Networks (ANN) and numerical crack data. The shear crack data from reinforced concrete beam specimens through finite element analysis were obtained. Afterward, K-clustering to create an input dataset for the ANN analysis was used. The training and testing of a multi-layer perceptron regression model involved the use of samples that had been analyzed using the Finite Element Method (FEM). The evaluation of the ANN model's performance considered the Mean Absolute Error (MAE), Adjusted R squared, Coefficient of Correlation, and Coefficient of Variation (CV).

Keywords

Acknowledgement

이 연구는 2023년도 인하대학교의 지원에 의한 결과의 일부임. 또한 이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2022R1C1C1009269).

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