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DC Field | Value | Language |
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dc.contributor.author | Chinnappa, G.B. | - |
dc.contributor.author | Ram Chandar, K. | - |
dc.date.accessioned | 2020-03-31T08:30:50Z | - |
dc.date.available | 2020-03-31T08:30:50Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Journal of Hazardous, Toxic, and Radioactive Waste, 2020, Vol.24, 1, pp.- | en_US |
dc.identifier.uri | https://idr.nitk.ac.in/jspui/handle/123456789/11141 | - |
dc.description.abstract | Iron ore tailings (IOT) are the by-products of iron ore beneficiation, and these tailings are disposed of in several tons annually in quarries, landfills, and tailings dams, causing environmental issues. Various researchers have attempted to study the properties of IOT and the use of them in concrete as a building material. The present research aims to investigate the potential use of alccofine, a microfine particle of slag, as a cement replacement and IOT as fine aggregates in concrete. Experimental results indicated that the concrete workability decreased with an increase in the IOT-alccofine content and the maximum compressive strength (CS) obtained was 70.00, 68.67, and 65 MPa respectively at 40%, 30%, and 20% IOT-alccofine dosage for varying water-to-cement (w/c) ratios of 0.35, 0.40, and 0.45 respectively. Similarly, the flexural strength (FS) and splitting tensile strength (STS) increased with an increase in IOT-alccofine content. A statistically fitted multiple regression analysis was performed for all the mechanical properties to evaluate the significant level of concrete containing alccofine and IOT in concrete. These prediction models have high accuracy and low bias and the validation process represented that the equations can perform excellently in predicting the IOT-alccofine concrete properties. 2019 American Society of Civil Engineers. | en_US |
dc.title | Experimental and Statistical Evaluations of Strength Properties of Concrete with Iron Ore Tailings as Fine Aggregate | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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1 Experimental and Statistical.pdf | 3.47 MB | Adobe PDF | View/Open |
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