Optimum Design of Reactive Powder Concrete Mixture Proportion Based on Artificial Neural and Harmony Search Algorithm

An optimum mixture proportion design method of reactive powder concrete (RPC) based on an artificial neural network (ANN) and harmony search (HS) algorithm was developed. ANNs were adopted to establish the relationship between design parameters (water-binder ratio, silica fume content, sand-binder ratio, and steel fiber content) and properties (compressive strength under standard curing and autoclaved curing, splitting tensile strength under autoclaved curing, and slump) of RPC, and the HS algorithm was used to design and optimize RPC mixture proportions with the objective criterion of minimum cost while meeting all property requirements. The proposed method can consider the influence of curing regimes, and its reliability was verified by experiment data.

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    • Abstract reprinted with permission from the American Concrete Institute.
  • Authors:
    • Ji, Tao
    • Yang, Yu
    • Fu, Mao-yuan
    • Chen, Bao-Chun
    • Wu, Hwai-Chung
  • Publication Date: 2017-1


  • English

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  • Accession Number: 01631602
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Mar 31 2017 12:08PM