Inverse estimation for the thermal boundary conditions of conjugate heat transfer using decentralized fuzzy inference method

A decentralized fuzzy inference method (DFIM) for estimating the heat flux distribution of a heated cylinder experiencing the conjugate heat transfer is proposed in this study. The deviations between the computed and measured temperature at each measurement points are taken as the input parameters of a set of fuzzy inference units (FIUs), and the corresponding fuzzy inference components of measured information are obtained by the FIUs. According to the importance of the various measured information, the fuzzy inference components then are weighted and synthesized to gain the compensations of the guessed heat flux distribution. Ultimately, the prediction of the heat flux is accomplished. Numerical tests are performed to study the effect of initial guessed heat flux, measurement point numbers and measurement errors on the estimated results. The validity and superiority can be concluded by comparing with the conjugate gradient method (CGM).