TY - JFULL AU - V. Nikkhah Rashidabad and M. Manteghian and M. Masoumi and S. Mousavian and D. Ashouri PY - 2014/2/ TI - Application of Neural Networks to Predict Changing the Diameters of Bubbles in Pool Boiling Distilled Water T2 - International Journal of Computer and Information Engineering SP - 15 EP - 18 VL - 8 SN - 1307-6892 UR - https://publications.waset.org/pdf/9997023 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 85, 2014 N2 - In this research, the capability of neural networks in  modeling and learning complicated and nonlinear relations has been  used to develop a model for the prediction of changes in the diameter  of bubbles in pool boiling distilled water. The input parameters used  in the development of this network include element temperature, heat  flux, and retention time of bubbles. The test data obtained from the  experiment of the pool boiling of distilled water, and the  measurement of the bubbles form on the cylindrical element. The  model was developed based on training algorithm, which is  typologically of back-propagation type. Considering the correlation  coefficient obtained from this model is 0.9633. This shows that this  model can be trusted for the simulation and modeling of the size of  bubble and thermal transfer of boiling. ER -