抄録
Recently, with the aim of low cost and high cycle "out-of-autoclave method" is proposed. However, since out-of-autoclave method of forming a vacuum pressure, imperfect moldings such as voids are likely to occur. Therefore, compared to the autoclave method, it is quite inferior in terms of the molding quality. In the past, the smart manufacturing technique has been studies to perform efficient molding by forecasting the molding state using the numerical simulation based on the information obtained by monitoring the molding process. But there is a problem that the modeling quality is degraded by the sensors embedded in the interlaminar of CFRP. In this study, by using data assimilation technique to integrate the forecast value by numerical simulation with the observed value by measurement, we constructed the model state estimation technique with high accuracy and we proposed that the technique of estimating the internal state of CFRP without embedding a sensor. In this technique, we estimate the whole internal temperature distribution of CFRP from observed values of the surface of CFRP by using an ensemble kalman filter, which is one of data assimilation techniques. In addition, we confirmed that the thermal conductivity distribution could be estimated simultaneously.
