Journal
CONSTRUCTION AND BUILDING MATERIALS
Volume 23, Issue 7, Pages 2614-2622Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2009.02.012
Keywords
Compressive strength; Genetic programming; JRing; Orimet; Pulverised fuel ash; Self-compacting concrete; Slump flow; Superplasticizer
Categories
Funding
- Engineering and Physical Sciences Research Council (EPSRC) of United Kingdom [GR/R75229/01]
- Gaziantep University
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Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183-317 kg/m(3) of cement content, 29-261 kg/m(3) of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, liking combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients. (C) 2009 Elsevier Ltd. All rights reserved.
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