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- W3091893460 endingPage "120215" @default.
- W3091893460 startingPage "120215" @default.
- W3091893460 abstract "Self-compacting concrete (SCC) has high value for deformability and segregation resistance, moderate viscosity and smaller yield stress. When pouring the SCC, the mix possesses the distinctive practical features such as - it is easily flown around and within the formwork. Using the ingredients of normal concrete, the SCC is produced. Cementitious materials are adopted for replacing the SCC cement content using agricultural products and industrial waste materials. For optimizing the material contained in SCC to obtain effective performance many machine learning approaches are implemented. This paper focuses on undertaking a review of SCC along with fibre reinforcement and cement replacement materials along with the role of ANN in predicting the optimum composition of SCC. The prime objective is on compiling the various literature available for understanding different SCC properties in the hardened and fresh state and also when these fibres and cement replacement items are introduced." @default.
- W3091893460 created "2020-10-15" @default.
- W3091893460 creator A5019858792 @default.
- W3091893460 creator A5050272646 @default.
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- W3091893460 creator A5083013047 @default.
- W3091893460 date "2020-11-01" @default.
- W3091893460 modified "2023-10-01" @default.
- W3091893460 title "A Review on Performance of Self-Compacting Concrete – Use of Mineral Admixtures and Steel Fibres with Artificial Neural Network Application" @default.
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- W3091893460 doi "https://doi.org/10.1016/j.conbuildmat.2020.120215" @default.
- W3091893460 hasPublicationYear "2020" @default.
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