データ同化が導く工学シミュレーションの新しい方向

抄録

The utilization of measurement data is becoming attractive in various fields due to the massive growth of sensing and networking technologies boosted by, so-called, the internet of things (IoT). It is expected to utilize such a data-rich environment to improve engineering simulations in computer-aided engineering (CAE). Data assimilation is one of the methodologies to statistically integrate a numerical model and measurement data, and it would be a key technology to take advantage of IoT technologies in CAE. Unlike meteorological data assimilation where the estimation of initial conditions for numerical weather prediction is of primary interest, engineering data assimilation, as it is called, data assimilation-aided engineering (DAE), should focus on other functionalities of data assimilation such as the improvement of a model by parameter estimation and adaptive measurement based on model prediction. In this article, we describe examples of such data assimilation studies applied to engineering problems.