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

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

Author(s): Tao Ji, Yu Yang, Mao-yuan Fu, Bao-chun Chen, and Hwai-Chung Wu

Publication: Materials Journal

Volume: 114

Issue: 01

Appears on pages(s): 41-47

Keywords: artificial neural network (ANN); cost; curing regime; harmony search (HS) algorithm; mixture proportion design; reactive powder concrete

Date: 1/1/2017

Abstract:
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.