Prediction of unsteady mixed convection over circular cylinder in the presence of nanofluid- A comparative study of ANN and GEP
DOI:
https://doi.org/10.3329/jname.v12i1.21812Keywords:
Mixed forced convection, Circular cylinder, Nanofluid, Neural network, Gene ExpressionAbstract
Heat transfer due to forced convection of copper water based nanofluid in the presence of buoyancy has been predicted by the Artificial Neural network (ANN) Gene Expression Programming (GEP). The present nanofluid is formed by mixing copper nano particles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are varying from 80 to 180. The buoyancy effect is done by introducing Richardson number (Ri) as 1 and -1. The back propagation algorithm is used to train the network. The present ANN and GEP models are trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Fluent. The numerical simulation based results are compared with the back propagation based ANN and GEP results. It is found that the mixed convection heat transfer of water based nanofluid can be predicted correctly by both ANN and GEP but GEP is found more efficient. It is also observed that the back propagation ANN and GEP both can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.
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References
GeneXproTools; Version: 5. GEPSOFT.
Abu-Nada, E., Oztop, H.F., 2009. Effects of inclination angle on natural convection in enclosures filled with Cuwater nanofluid. International Journal of Heat and Fluid Flow 30, 669-678.
Buongiorno, J., 2006. Convective transport in nanofluids. Journal of Heat Transfer 128, 240-250.
Chakraborty, J., Verma, N., Chhabra, R., 2004. Wall effects in flow past a circular cylinder in a plane channel: a numerical study. Chemical Engineering and Processing: Process Intensification 43, 1529-1537.
Chhabra, R., Soares, A., Ferreira, J., 2004. Steady nonNewtonian flow past a circular cylinder: a numerical study. Acta Mechanica 172, 1-16.
Daungthongsuk, W., Wongwises, S., 2007. A critical review of convective heat transfer of nanofluids. Renewable and Sustainable Energy Reviews 11, 797-817.
Dey, P., Das, A.K., 2014. Numerical analysis of characteristic of flow and heat transfer due to natural convection in a enclosure (square) using nano-fluid, Advances in Energy Conversion Technologies (ICAECT), 2014 International Conference on. IEEE, pp. 92-98.
Eastman, J., Choi, S., Li, S., Yu, W., Thompson, L., 2001. Anomalously increased effective thermal conductivities of ethylene glycol-based nanofluids containing copper nanoparticles. Applied Physics Letters 78, 718-720.
Ferreira, C., 2001. Gene expression programming: a new adaptive algorithm for solving problems. arXiv preprint cs/0102027.
Ferreira, C., 2002. Gene expression programming in problem solving, Soft Computing and Industry. Springer, pp. 635-653.
Fluent, I., 2006. FLUENT 6.3 users guide. Fluent documentation.
Golani, R., Dhiman, A., 2004. Fluid flow and heat transfer across a circular cylinder in the unsteady flow regime.
Kakaç, S., Pramuanjaroenkij, A., 2009. Review of convective heat transfer enhancement with nanofluids. International Journal of Heat and Mass Transfer 52, 3187-3196.
Khanafer, K., Vafai, K., Lightstone, M., 2003. Buoyancy-driven heat transfer enhancement in a two-dimensional enclosure utilizing nanofluids. International Journal of Heat and Mass Transfer 46, 3639-3653.
Kurtulus, D.F., 2009. Ability to forecast unsteady aerodynamic forces of flapping airfoils by artificial neural network. Neural Computing and Applications 18, 359-368.
Mahír, N., Altaç, Z., 2008. Numerical investigation of convective heat transfer in unsteady flow past two cylinders in tandem arrangements. International Journal of Heat and Fluid Flow 29, 1309-1318.
Martí, P., Shiri, J., Duran-Ros, M., Arbat, G., De Cartagena, F.R., Puig-Bargués, J., 2013. Artificial neural networks vs. Gene Expression Programming for estimating outlet dissolved oxygen in micro-irrigation sand filters fed with effluents. Computers and Electronics in Agriculture 99, 176-185.
Park, J., Kwon, K., Choi, H., 1998. Numerical solutions of flow past a circular cylinder at Reynolds numbers up to 160. KSME International Journal 12, 1200-1205.
Posdziech, O., Grundmann, R., 2007. A systematic approach to the numerical calculation of fundamental quantities of the two-dimensional flow over a circular cylinder. Journal of Fluids and Structures 23, 479-499.
Rahman, M.M., Karim, M.M., Alim, M.A., 2007. Numerical investigation of unsteady flow past a circular cylinder using 2-D finite volume method. Journal of Naval Architecture and Marine Engineering 4, 27-42.
Santra, A.K., Chakraborty, N., Sen, S., 2009. Prediction of heat transfer due to presence of copperwater nanofluid using resilient-propagation neural network. International Journal of Thermal Sciences 48, 1311-1318.
Sarkar, S., Dalal, A., Biswas, G., 2011. Unsteady wake dynamics and heat transfer in forced and mixed convection past a circular cylinder in cross flow for high Prandtl numbers. International Journal of Heat and Mass Transfer 54, 3536-3551.
Sarkar, S., Ganguly, S., Biswas, G., 2012. Mixed convective heat transfer of nanofluids past a circular cylinder in cross flow in unsteady regime. International Journal of Heat and Mass Transfer 55, 4783-4799.
Shi, J.-M., Gerlach, D., Breuer, M., Biswas, G., Durst, F., 2004. Heating effect on steady and unsteady horizontal laminar flow of air past a circular cylinder. Physics of Fluids (1994-present) 16, 4331-4345.
Sreekanth, S., Ramaswamy, H., Sablani, S., Prasher, S., 1999. A neural network approach for evaluation of surface heat transfer coefficient. Journal of food processing and preservation 23, 329-348.
Tiwari, R.K., Das, M.K., 2007. Heat transfer augmentation in a two-sided lid-driven differentially heated square cavity utilizing nanofluids. International Journal of Heat and Mass Transfer 50, 2002-2018.
Trisaksri, V., Wongwises, S., 2007. Critical review of heat transfer characteristics of nanofluids. Renewable and Sustainable Energy Reviews 11, 512-523.
Tritton, D.J., 1959. Experiments on the flow past a circular cylinder at low Reynolds numbers. Journal of Fluid Mechanics 6, 547-567.
Xuan, Y., Li, Q., 2000. Heat transfer enhancement of nanofluids. International Journal of Heat and Fluid Flow 21, 58-64.
Yacob, N.A., Ishak, A., Pop, I., Vajravelu, K., 2011. Boundary layer flow past a stretching/shrinking surface beneath an external uniform shear flow with a convective surface boundary condition in a nanofluid. Nanoscale research letters 6, 1-7.
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