Rheological Characteristics of Ice Slurries Based on Propylene- and Ethylene-Glycol at High Ice Fractions
Ice slurries are considered as a promising phase-changing secondary fluids for air-conditioning, packaging or cooling industrial processes. An experimental study has been here carried out to measure the rheological characteristics of ice slurries. Ice slurries consist in a solid phase (flake ice crystals) and a liquid phase. The later is composed of a mixture of liquid water and an additive being here either (1) Propylene-Glycol (PG) or (2) Ethylene-Glycol (EG) used to lower the freezing point of water. Concentrations of 5%, 14% and 24% of both additives are investigated with ice mass fractions ranging from 5% to 85%. The rheological measurements are carried out using a Discovery HR-2 vane-concentric cylinder with four full-length blades. The experimental results show that the behavior of ice slurries is generally non-Newtonian with shear-thinning or shear-thickening behaviors depending on the experimental conditions. In order to determine the consistency and the flow index, the Herschel-Bulkley model is used to describe the behavior of ice slurries. The present results are finally validated against an experimental database found in the literature and the predictions of an Artificial Neural Network model.
[1] Bédécarrats, J. P. (2010). Utilisation rationnelle de l'énergie par les techniques de stockage et de transport du froid par chaleur latente, Habilitation dissertation, Université de Pau et des Pays de l'Adour.
[2] Kauffeld, M., Wang, M. J., Goldstein, V., & Kasza, K. E. (2010). Ice slurry applications. International Journal of Refrigeration, 33(8), 1491-1505.
[3] Egolf, P. W., & Kauffeld, M. (2005). From physical properties of ice slurries to industrial ice slurry applications. International Journal of Refrigeration, 28(1), 4-12.
[4] Niezgoda-Żelasko, B., & Zalewski, W. (2006). Momentum transfer of ice slurry flows in tubes, experimental investigations. International Journal of Refrigeration, 29(3), 418-428.
[5] Boumaza, M. (2009). Experimental Investigation of Rheological Characteristics of Ice Slurry. In ICF12, Ottawa.
[6] Metzner, A. B. (1985). Rheology of suspensions in polymeric liquids. Journal of Rheology, 29(6), 739-775.
[7] Mellari, S., Boumaza, M., & Egolf, P. W. (2012). Physical modeling, numerical simulations and experimental investigations of Non-Newtonian ice slurry flows. International Journal of Refrigeration, 35(5), 1284-1291.
[8] Barnes H. A. and Carnali J. O. (1990) The vane-in-cup as a novel rheometer geometry for shear thinning and thixotropic materials Journal of Rheology. 34, 841-866.
[9] Barnes A. B., Nguyen Q. D. (2001) Rotating Vane Rheometry - A Review, J. Non-Newtonian Fluid Mech. 98 1-14
[10] Liddell P. V. and Boger D. V. (1996) Yield stress measurement with the vane, J. Non-Newtonian Fluid Mech. 63, 235-261
[11] Turian R. M., Ma T. W., Hsu F. L. G., Sung D. J. (1997) Characterization, settling, and rheology of concentrated fine particulate mineral slurries Powder Tech. 93, 219-233
[12] Zhang X. D., Giles D. W., Barocas V. H., Yasunaga K., and Macosko C.W. (1998) Measurement of foam modulus via a vane rheometer, Journal of Rheology. 42(4), 871-889.
[13] Ben Lakhdar, M.A., (1998). Comportement thermohydraulique d’un fluide frigoporteur diphasique: le coulis de glace, Etude théorique et expérimentale, Ph.D. thesis. INSA, Lyon, France.
[14] Guilpart, J., Fournaison, L., Lakhdar, M. B., Flick, D., & Lallemand, A. (1999). Experimental study and calculation method of transport characteristics of ice slurries, Proceedings of the First Workshop on Ice Slurries of the International Institute of Refrigeration, Yverdon-les-Bains, Switzerland; 27–28 May 1999. p. 74–82.
[15] Mellari, S. (2016). Experimental investigations of ice slurry flows in horizontal pipe based on monopropylene glycol. International Journal of Refrigeration, 65, 27-41.
[16] Kitanovski, A., Vuarnoz, D., Ata-Caesar, D., Egolf, P. W., Hansen, T. M., & Doetsch, C. (2005). The fluid dynamics of ice slurry. International Journal of Refrigeration, 28(1), 37-50.
[17] Lippmann RP (1987) An introduction to computing with neural nets. ASSP Mag IEEE 4(2), 4–22
[18] Demuth H, Beale M, Hagan M (2007) Neural network toolbox 5,user’s guide. The MathWorks Inc, Natick.
[19] Erkaymaz, O., Özer, M., & Yumuşak, N. (2012). Performance Analysis of a Feed-Forward Artifical Neural Network with Small-World Topology. Procedia Technology, 1, 291-296.
[20] Laïdi, M., & Hanini, S. (2012). Approche neuronale pour l’estimation des transferts thermiques dans un fluide frigoporteur diphasique. Revue des Energies Renouvelables, 15(3), 513-520.
[21] Goudarzi, K., Moosaei, A., & Gharaati, M. (2015). Applying artificial neural networks (ANN) to the estimation of thermal contact conductance in the exhaust valve of internal combustion engine. Applied Thermal Engineering, 87, 688-697.
[1] Bédécarrats, J. P. (2010). Utilisation rationnelle de l'énergie par les techniques de stockage et de transport du froid par chaleur latente, Habilitation dissertation, Université de Pau et des Pays de l'Adour.
[2] Kauffeld, M., Wang, M. J., Goldstein, V., & Kasza, K. E. (2010). Ice slurry applications. International Journal of Refrigeration, 33(8), 1491-1505.
[3] Egolf, P. W., & Kauffeld, M. (2005). From physical properties of ice slurries to industrial ice slurry applications. International Journal of Refrigeration, 28(1), 4-12.
[4] Niezgoda-Żelasko, B., & Zalewski, W. (2006). Momentum transfer of ice slurry flows in tubes, experimental investigations. International Journal of Refrigeration, 29(3), 418-428.
[5] Boumaza, M. (2009). Experimental Investigation of Rheological Characteristics of Ice Slurry. In ICF12, Ottawa.
[6] Metzner, A. B. (1985). Rheology of suspensions in polymeric liquids. Journal of Rheology, 29(6), 739-775.
[7] Mellari, S., Boumaza, M., & Egolf, P. W. (2012). Physical modeling, numerical simulations and experimental investigations of Non-Newtonian ice slurry flows. International Journal of Refrigeration, 35(5), 1284-1291.
[8] Barnes H. A. and Carnali J. O. (1990) The vane-in-cup as a novel rheometer geometry for shear thinning and thixotropic materials Journal of Rheology. 34, 841-866.
[9] Barnes A. B., Nguyen Q. D. (2001) Rotating Vane Rheometry - A Review, J. Non-Newtonian Fluid Mech. 98 1-14
[10] Liddell P. V. and Boger D. V. (1996) Yield stress measurement with the vane, J. Non-Newtonian Fluid Mech. 63, 235-261
[11] Turian R. M., Ma T. W., Hsu F. L. G., Sung D. J. (1997) Characterization, settling, and rheology of concentrated fine particulate mineral slurries Powder Tech. 93, 219-233
[12] Zhang X. D., Giles D. W., Barocas V. H., Yasunaga K., and Macosko C.W. (1998) Measurement of foam modulus via a vane rheometer, Journal of Rheology. 42(4), 871-889.
[13] Ben Lakhdar, M.A., (1998). Comportement thermohydraulique d’un fluide frigoporteur diphasique: le coulis de glace, Etude théorique et expérimentale, Ph.D. thesis. INSA, Lyon, France.
[14] Guilpart, J., Fournaison, L., Lakhdar, M. B., Flick, D., & Lallemand, A. (1999). Experimental study and calculation method of transport characteristics of ice slurries, Proceedings of the First Workshop on Ice Slurries of the International Institute of Refrigeration, Yverdon-les-Bains, Switzerland; 27–28 May 1999. p. 74–82.
[15] Mellari, S. (2016). Experimental investigations of ice slurry flows in horizontal pipe based on monopropylene glycol. International Journal of Refrigeration, 65, 27-41.
[16] Kitanovski, A., Vuarnoz, D., Ata-Caesar, D., Egolf, P. W., Hansen, T. M., & Doetsch, C. (2005). The fluid dynamics of ice slurry. International Journal of Refrigeration, 28(1), 37-50.
[17] Lippmann RP (1987) An introduction to computing with neural nets. ASSP Mag IEEE 4(2), 4–22
[18] Demuth H, Beale M, Hagan M (2007) Neural network toolbox 5,user’s guide. The MathWorks Inc, Natick.
[19] Erkaymaz, O., Özer, M., & Yumuşak, N. (2012). Performance Analysis of a Feed-Forward Artifical Neural Network with Small-World Topology. Procedia Technology, 1, 291-296.
[20] Laïdi, M., & Hanini, S. (2012). Approche neuronale pour l’estimation des transferts thermiques dans un fluide frigoporteur diphasique. Revue des Energies Renouvelables, 15(3), 513-520.
[21] Goudarzi, K., Moosaei, A., & Gharaati, M. (2015). Applying artificial neural networks (ANN) to the estimation of thermal contact conductance in the exhaust valve of internal combustion engine. Applied Thermal Engineering, 87, 688-697.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:74928", author = "Senda Trabelsi and Sébastien Poncet and Michel Poirier", title = "Rheological Characteristics of Ice Slurries Based on Propylene- and Ethylene-Glycol at High Ice Fractions", abstract = "Ice slurries are considered as a promising phase-changing secondary fluids for air-conditioning, packaging or cooling industrial processes. An experimental study has been here carried out to measure the rheological characteristics of ice slurries. Ice slurries consist in a solid phase (flake ice crystals) and a liquid phase. The later is composed of a mixture of liquid water and an additive being here either (1) Propylene-Glycol (PG) or (2) Ethylene-Glycol (EG) used to lower the freezing point of water. Concentrations of 5%, 14% and 24% of both additives are investigated with ice mass fractions ranging from 5% to 85%. The rheological measurements are carried out using a Discovery HR-2 vane-concentric cylinder with four full-length blades. The experimental results show that the behavior of ice slurries is generally non-Newtonian with shear-thinning or shear-thickening behaviors depending on the experimental conditions. In order to determine the consistency and the flow index, the Herschel-Bulkley model is used to describe the behavior of ice slurries. The present results are finally validated against an experimental database found in the literature and the predictions of an Artificial Neural Network model.
", keywords = "Ice slurry, propylene-glycol, ethylene-glycol, rheology, artificial neural network.", volume = "11", number = "1", pages = "177-5", }
