TY  - SER
AU  - Tao Ji 
AU  - Xu Jian Lin
TI  - A mortar mix proportion design algorithm based rnon artificial neural networks
SN  - 1598-8198
KW  - Mortar Mix Proportion Design
KW  - Artificial Neural Network (ANN)
KW  - Nominal Water-Cement Ratio
KW  - Equivalent Water-Cement Ratio
KW  - Average Paste Thickness (APT)
KW  - Fly Ash-Binder ratio
N2  - The concepts of four parameters of nominal water-cement ratio, equivalent water-cement ratio, average paste thickness, fly ash-binder ratio were introduced. It was verified that the four parameters and the mix proportion of mortar can be transformed each other. The behaviors (strength, workability, et al.) of mortar primarily determined by the mix proportion of mortar now depend on the four parameters. The prediction models of strength and workability of mortar were built based on artificial neural networks (ANNs). The calculation models of average paste thickness and equivalent water-cement ratio of mortar can be obtained by the reversal deduction of the two prediction models, respectively. A mortar mix proportion design algorithm was proposed. The proposed mortar mix proportion design algorithm is expected to reduce the number of trial and error, save cost, laborers and time
UR  - DOI: 10.12989/cac.2006.3.5.357
ER  -