An Innovative Iterative Method to Derive Forced Convection Correlations
from the Lowest Number of Generated Data
Abstract
The turbulent flow incorporated with forced convection heat transfer is
considered as a complex phenomenon and it is hard to predict
analytically. Evidently, empirical correlations and numerical
simulations regard as the most suitable approaches to estimate the
turbulent flow integrated with forced convection heat transfer. The main
objective of this study is to derive the DittusBoelter equation (an
equation used to find the heat transfer coefficient for turbulent flow
through pipes) unexperimentally using the minimum number of numerical
trial. This paper uses the numerical simulation data and generate novel
random data to reach the dittusBoelter relation; generating minimum
data.