Computers and Concrete

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Case-based reasoning approach to estimating the strength of sustainable concrete

  • Koo, Choongwan (Department of Building Services Engineering, The Hong Kong Polytechnic University) ;
  • Jin, Ruoyu (School of Environment and Technology, University of Brighton) ;
  • Li, Bo (Department of Civil Engineering, University of Nottingham Ningbo China) ;
  • Cha, Seung Hyun (Department of Building Services Engineering, The Hong Kong Polytechnic University) ;
  • Wanatowski, Dariusz (Faculty of Engineering, University of Leeds)
  • Received : 2017.03.28
  • Accepted : 2017.07.19
  • Published : 2017.12.25
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Abstract

Continuing from previous studies of sustainable concrete containing environmentally friendly materials and existing modeling approach to predicting concrete properties, this study developed an estimation methodology to predicting the strength of sustainable concrete using an advanced case-based reasoning approach. It was conducted in two steps: (i) establishment of a case database and (ii) development of an advanced case-based reasoning model. Through the experimental studies, a total of 144 observations for concrete compressive strength and tensile strength were established to develop the estimation model. As a result, the prediction accuracy of the A-CBR model (i.e., 95.214% for compressive strength and 92.448% for tensile strength) performed superior to other conventional methodologies (e.g., basic case-based reasoning and artificial neural network models). The developed methodology provides an alternative approach in predicting concrete properties and could be further extended to the future research area in durability of sustainable concrete.

Keywords

Acknowledgement

Supported by : Ningbo Science and Technology Bureau, National Research Foundation of Korea (NRF)

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