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Semi Analytical Prediction of Automobile Body Temperature Distribution in the Top Coat Paint Oven

[+] Author Affiliations
P. Hanafizadeh, B. Sajadi, M. H. Saidi

Sharif University of Technology, Tehran, Iran

H. Khalkhali, M. Taherraftar

IKCO, Tehran, Iran

Paper No. HT2009-88384, pp. 655-660; 6 pages
  • ASME 2009 Heat Transfer Summer Conference collocated with the InterPACK09 and 3rd Energy Sustainability Conferences
  • Volume 3: Combustion, Fire and Reacting Flow; Heat Transfer in Multiphase Systems; Heat Transfer in Transport Phenomena in Manufacturing and Materials Processing; Heat and Mass Transfer in Biotechnology; Low Temperature Heat Transfer; Environmental Heat Transfer; Heat Transfer Education; Visualization of Heat Transfer
  • San Francisco, California, USA, July 19–23, 2009
  • Conference Sponsors: Heat Transfer Division
  • ISBN: 978-0-7918-4358-1 | eISBN: 978-0-7918-3851-8
  • Copyright © 2009 by ASME


Automotive industry frequently needs to test new products, according to different production parameters, in order to determine the actual thermal behavior of bodies before mass production is implemented. Numerical simulation of these processes can reduce the very expensive and time consuming experimental procedures. For the drying and hardening process of the top paint applied in the coating process, the body temperature must be raised according to the paint manufacturer regulations. Consequently, prediction of temperature distribution of the car body during various zones of ovens is very vital in the design and performance analysis of the paint dryers. In this research, a novel semi-analytical approach has been used to predict the body temperature variation during the curing process. Considering the energy balance for the body, a set of differential equation has been extracted, depending on the oven zone. These equations can be solved numerically to find the transient temperature profile of the car body. Some parameters in these equations have been achieved by experimental procedure. The results show that the present model predictions are in a good agreement with the experimental data. Therefore, the developed model has a reasonable accuracy and can be used as an efficient robust approach to distinguish overall thermal behavior of the body. These techniques can be used to optimize the design of curing paint oven.

Copyright © 2009 by ASME



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