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Minerals 2017, 7(9), 165; doi:10.3390/min7090165

Rheology of Fly Ash Mixed Tailings Slurries and Applicability of Prediction Models

Department of Civil Engineering, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Korea
Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock, TX 79409-1023, USA
Department of Marine and Civil Engineering, Chonnam National University, 50 Daehak-ro, Yeosu 59626, Korea
Author to whom correspondence should be addressed.
Received: 17 August 2017 / Revised: 4 September 2017 / Accepted: 6 September 2017 / Published: 8 September 2017
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Coal fly ash has potential applications in the management of reactive mine tailings. The shear stress versus shear rate curves obtained during viscometer tests are presented to describe the rheological behaviors of tailings slurries mixed with fly ash. The investigation was conducted on specimens prepared with different fly ash additions as well as prepared at variable conditions of temperature, mixing time, and CaCl2 solution. It was observed that the rheological properties of ash-tailings slurry mixtures are influenced by the hydration of fly ash as well as the particle packing and arrangement. Rheological properties of specimen mixtures were determined from the resulting flow curves using the existing rheological models. The performance of prediction models in calculating the rheological properties of the mixed specimens, as quantified by the root mean square error (RMSE), varied with the mixture constituents, temperature, and time. In general, the Papanastasion, Herschel-Bulkley, Sisko, and Robertson-Stiff models were found to be favorable for use with mixtures of fly ash and tailings slurries, compared to the Bingham, Modified Bingham, Casson, and De Kee models. View Full-Text
Keywords: rheology; tailings; fly ash; slurry; modelling rheology; tailings; fly ash; slurry; modelling

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Lee, J.K.; Ko, J.; Kim, Y.S. Rheology of Fly Ash Mixed Tailings Slurries and Applicability of Prediction Models. Minerals 2017, 7, 165.

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