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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 94
PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by:
Paper 118
Modelling of Bacterial Growth in Nano Liquids T. Amanbayev1, G. Okeke2, M. Afzal2 and S.J. Antony2
1Department of Mathematical Methods and Simulation, Southern-Kazakh State University, Shimkent, Kazakhstan
T. Amanbayev, G. Okeke, M. Afzal, S.J. Antony, "Modelling of Bacterial Growth in Nano Liquids", in , (Editors), "Proceedings of the Seventh International Conference on Engineering Computational Technology", Civil-Comp Press, Stirlingshire, UK, Paper 118, 2010. doi:10.4203/ccp.94.118
Keywords: bacterial growth model, nanofluids, computational modelling.
Summary
Mechanics of nanofluids is a fast developing research area which possesses relevant promising development for industries. Nanofluids are solid-liquid composites in which metallic or non-metallic nanoparticles are stably suspended in common liquids for different engineering and science applications [1]. Bacterial growth within nanofluids is a common problem met in large scale production of nanofluids in industrial plants, which can destabilise the quality of the nanofluids for their subsequent applicability in manufacturing processes. This has motivated the present work to understand the growth of bacterial and the combined mass of aggregate of particles and bacteria, refereed to as a complex, in nanofluids. Using a computational approach, here we study the growth kinetics of bacteria modelled as a particulate inclusion in nano liquids. The study shows that, the biological and chemical conditions [2] of nanofluids influences the particle-particle and particle-bacteria interactions including a change in the mass of the resulting complex formed. The evolution plot of the population of the bacteria with time shows a transition regime, below which rapid growth or decline of the population occurs. We have shown that the mass of the complex is influenced significantly by the biological and chemical environmental factors such as nutrient concentration, temperature, acidity etc. represented in terms of their characteristic parameters in the modelling. Further studies are required to understand the effect of the mass of the complex on the effective thermal conductance of nanofluids [3].
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