Strength predictions of GGBS based cement mortar with different M-Sands using Neural Networks
B. Akash Kumar,V. Vasugi,S. Elavenil +2 more
- Vol. 1716, Iss: 1, pp 012015
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The article was published on 2020-12-01 and is currently open access. It has received 0 citations till now.read more
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Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network
TL;DR: The results showed that ANN can be an alternative approach for the predicting the compressive strength of ground granulated blast furnace slag concrete using concrete ingredients as input parameters.
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Efficiency of GGBS in concrete
TL;DR: In this paper, the 28-day strength efficiency of ground granulated blast furnace slag (GGBS) concretes in concrete at various replacement levels was quantified and the overall strength efficiency was found to be a combination of general efficiency factor depending on the age and a percentage efficiency factor, depending upon the percentage of replacement.
Journal ArticleDOI
Comparison of artificial neural network (ANN) and response surface methodology (RSM) prediction in compressive strength of recycled concrete aggregates
TL;DR: In this paper, the authors aim at predicting and modeling the 7, 28 and 56 days compressive strength of a concrete containing concrete's recycled coarse aggregates and that, for different range of cement content and slump.
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A concrete mix proportion design algorithm based on artificial neural networks
Tao Ji,Tingwei Lin,Xujian Lin +2 more
TL;DR: In this paper, a concrete mix proportion design algorithm based on a way from aggregates to paste, a least paste content, Modified Tourfar's Model and ANNs was proposed, which is expected to reduce the number of trial and error, save cost, laborers and time.
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Rheological and mechanical properties of mortars prepared with natural and manufactured sands
TL;DR: In this paper, two natural and two manufactured sands were selected and tested at different water-cement ratios and fine aggregate tocement ratio for the same standard gradation to identify shape-related differences on the mechanical performance of mortars.