Prediction of unconfined compressive strength of cement paste containing industrial wastes

Waste Management
J A Stegemann, N R Buenfeld

Abstract

Neural network analysis was used to construct models of unconfined compressive strength (UCS) as a function of mix composition using existing data from literature studies of Portland cement containing real industrial wastes. The models were able to represent the known non-linear dependency of UCS on curing time and water content, and generalised from the literature data to find relationships between UCS and quantities of five waste types. Substantial decreases in UCS were caused by all wastes; except for EAF dust, the effect was nonlinear with the greatest decrease caused initially by approx. 12% plating sludge, 40% foundry dust, 58% other ash, and 72% MSWI fly ash by mass of dry product. It appears that the maximum waste additions used in modelling may approximate the practical limits of waste additions used in modelling may approximate the practical limits of waste addition to Portland cement, i.e., 50% plating sludge or EAF dust, 64% foundry dust, 92% other ash, and 85% MSWI fly ash by mass of dry product. The laboratory was found to be a key predictive variable and acted as a surrogate for laboratory-specific variables related to cement composition, strength and hardening class, product mixing and preparation details, labor...Continue Reading

References

Apr 1, 1989·Bulletin of Environmental Contamination and Toxicology·D J Lisk
Oct 19, 2001·Journal of Hazardous Materials·A PolettiniF Testa
Feb 6, 2002·Journal of Hazardous Materials·J A Stegemann, N R Buenfeld

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Citations

Nov 27, 2007·Waste Management·Margarida J QuinaRosa M Quinta-Ferreira
Dec 11, 2007·Ecotoxicology and Environmental Safety·Senem BayarGuleda Onkal Engin

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