Guangjun Wang

Inverse Estimation for Heat Flux Distribution at the Metal-Mold Interface Using Fuzzy Inference

This study provides a new inverse approach based on fuzzy inference for solving the problem of estimating heat flux distribution at the metal-mold interface in the continuous casting process. Measured temperatures acquired with the thermocouples buried in the mold are used to obtain corresponding inference results with the fuzzy inference. Then according to the importance of measured information for estimating the heat flux distribution, inference results are weighted to realize estimation of heat flux distribution at the metal-mold interface. Some numerical tests are presented to discuss the validity of the present approach by using different initial guesses of heat flux distribution, the number of measuring points, and measurement errors. In comparison with the conjugate gradient method, it is concluded that the method based on fuzzy inference is of a good anti-illposed characteristic.

Decentralized fuzzy inference method for estimating thermal boundary condition of a heated cylinder normal to a laminar air stream

A decentralized fuzzy inference (DFI) method based on the fuzzy theory is proposed in this study for estimating the heat flux distribution of a heated cylinder experiencing conjugate heat transfer. A group of fuzzy inference units (FIUs) are designed. The deviations between the calculated and measured temperature at each measurement point are taken as the input parameters of FIUs, and the corresponding fuzzy inference components corresponding to the measured temperature are obtained by the FIUs. According to the importance of the various measured temperatures, the fuzzy inference components are then 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, measurement errors and the coupling of measurement point numbers and measurement errors on the estimated results. The results show that the DFI method can estimate the heat flux availably and possesses a better anti-ill-posed character and higher accuracy than the conjugate gradient method (CGM). The DFI method shows superiority.

Multi-model method for solving nonlinear transient inverse heat conduction problems

Abstract The multi-model inverse method for nonlinear inverse problems is established based on the multi-model control theory. First the model switching variable is chosen and several typical operating balance points in the workspace of the balance variable are selected. Then for each operating balance point the linear local model is established, and the local controller is designed for each linear local model. Finally, according to the instantaneous matching degree between the actual model and the local models, the inversion results of each local controller are weighted and synthesized to obtain the final inversion result. Numerical tests are implemented to solve the one-dimensional nonlinear inverse heat conduction problem by the multi-model inverse method associated with the dynamic matrix control (DMC) and DMC filter, respectively. Numerical results by the multi-model inverse method based on DMC demonstrate that the multi-model inverse method is a highly computationally efficient and accurate algorithm for inverse problems with complicated direct problems. Numerical results by the multi-model inverse method based on DMC filter show that the presented method can extend the applied field of the complicated linear inverse algorithms such as digital filter to the nonlinear inverse problems and it can obtain satisfactory inversion results.