Adaptive weighting input estimation method to contact conductance during metal casting problem

The air-gap formation between a casting and the metal mold during metal casting creates a thermal resistance that reduces the heat transfer and solidification rates. This work applied an adaptive weighting input estimation algorithm that efficiently and on-line estimates time-varied thermal contact conductance, because it is not able to be measurement direct. The on-line inverse solution methodology based on the Kalman filtering technique and a recursive least-squares estimator, a recursive least-squares estimator weighted by the forgetting factor is proposed to extract the unknowns. The adaptive weighting technique is essential since unknowns input are time-varied and have unpredictable changing status. The superior capabilities of this inverse method are demonstrated in several one-dimensional time-varying estimate cases and comparisons of the proposed algorithm, with the conjugate gradient method. As a result, the adaptive weighting input estimation algorithm can offer a fast and reliable way of estimating the thermal contact conductance.