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
Appears on pages(s): 41-47
Keywords: artificial neural network (ANN); cost; curing regime; harmony search (HS) algorithm; mixture proportion design; reactive powder concrete
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.