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- Title
Experimental investigation and prediction of copper slag incorporated self‐compacting concrete using artificial neural network.
- Authors
S., Dinesh; D., Brindha
- Abstract
This research work is aimed to carryout experimental investigation on copper slag incorporated self‐compacting (SCC) concrete; here, copper slag is used as a replacement to fine aggregate in the range of 0–100%. The self‐compacting concrete is manufactured with powder matrix incorporating cement, flyash, metakaolin, and silicafume. The powder matrix is decided based on the objective of flow properties and strength properties. The fresh concrete properties of various mixes were studied and collected. Then, the concrete is casted as cubes and cylinders and tested for its strength behavior. The flow properties of copper slag‐replaced mix were within stipulated guideline values by EFNARC, and early age strength attainment gets affected by the replacement of copper slag. The collected experimental results were designed to a data set categorizing as input and target. This data set is then used as a parameter in feed forward artificial neural network (ANN) and a predictive model is developed. This predictive model is then compared with the existing experimental values and tested for its performance. The results show that ANN provides a reliable predictive model for both flow and strength properties.
- Subjects
COPPER slag; SELF-consolidating concrete; ARTIFICIAL neural networks; PREDICTION models
- Publication
Structural Concrete, 2022, Vol 23, Issue 4, p2464
- ISSN
1464-4177
- Publication type
Article
- DOI
10.1002/suco.202100230