Artificial Neural Network Modeling of a Closed Loop Pulsating Heat Pipe
Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1127332Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 841
 Charoensawan, P., Khandekar, S., Groll, M., and Trenton, P. (2003). ‘Closed loop pulsating heat pipes-Part A: Parametric experimental investigations’. Applied Thermal Engineering, 23(16), 2009–2020.
 Zhang, Y., and Faghri, A. (2008). ‘Advances and Unsolved Issues in Pulsating Heat Pipes’. Heat Transfer Engineering, 29(1), 20–44.
 Patel, V., M., Gaurav, and Mehta, H., B. (2017). ‘Influence of working fluids on startup mechanism and thermal performance of a closed loop pulsating heat pipe’. Applied Thermal Engineering, 110, 1568–1577.
 Patel, V., M., and Mehta, H., B. (2016). 'Influence of Gravity on the Performance of a Closed Loop Pulsating Heat Pipe '. World Academy of Science, Engineering and Technology, International Science Index 109, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 10(1), 219 - 223.
 Patel, V., M., and Mehta, H., B. (2016). ‘Start Up Mechanism of Pulsating Heat Pipe’. National Conference on Thermal Fluid-science and Tribology Application, S.V. National Institute of Technology, Surat, ISBN: 978-93-5265-440-6, 1-8.
 Gamit, H., More, V., Bade, M., and Mehta, H., B. (2015). ‘Experimental Investigations on Pulsating Heat Pipe’. The 7th International Conference on Applied Energy, ICAE2015, Energy Procedia, 75, 3186-3191.
 Mehta, H. B., Patel, V., M., and Banerjee, J. (2016). 'Prediction of Air-Water Two-Phase Frictional Pressure Drop Using Artificial Neural Network'. World Academy of Science, Engineering and Technology, International Science Index 109, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 10(1), 210 - 213.
 Mehta, H., B., Pujara, M., P., and Banerjee, J. (2013). ‘Prediction of Two-Phase Flow Pattern using Artificial Neural Network’. International Conference on Chemical and Environmental Engineering (ICCEE-2013) Johannesburg (South Africa), April 15-16, 2013.
 Shafii, M., B., Arabnejad, S., Saboohi, Y., and Jamshidi, H. (2010). 'Experimental Investigation of Pulsating Heat Pipes and a Proposed Correlation'. Heat Transfer Engineering, 31(10), 854–861.