Predicting shrinkage of alkali-activated blast furnace-fly ash mortars using artificial neural network (ANN)
نویسندگان
چکیده
Drying shrinkage of alkali-activated binders are recognized as one the most important properties towards quality assurance binders. In this study, results experimental studies and predictive models developed to determine drying alkali - activated blast furnace-fly ash mortars presented discussed. Different parameters were altered in study such content GGBFS, FA, activator modulus (Ms), curing temperature. Their effects on then evaluated. Artificial neural network (ANN) Multiple Linear Regression (MLR) built predict at 28 days using above-mentioned inputs. The ANN model predictions showed strong correlations. prediction 28-days for GGBFS-FA was more accurate than MLR.
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ژورنال
عنوان ژورنال: Cement & Concrete Composites
سال: 2021
ISSN: ['0958-9465', '1873-393X']
DOI: https://doi.org/10.1016/j.cemconcomp.2021.104265