低次元化モデル作成における線形固有モードとPOMのハイブリッド基底の適用について

抄録

This paper proposes the method that obtain a reduced-order model using sampled data. The outline of the method is as follows. First, after coordinate transformation from the displacement coordinate system to the modal coordinate system,the sample data is projected onto the space that the 1st mode is excluded. Next, the proper orthogonal decomposition (POD) is applied to the projected data to obtain the POMs in the space that the 1st mode is excluded. The obtained POMs are expanded to the whole mode space and the correction bases are obtained by transforming the coordinate to the displacement coordinate system. Finally, a reduced-order model is obtained by using the 1st mode and the correction bases. The results are as follows: 1) This paper proposed the method for simultaneously obtaining the correction bases for obtaining a reduced-order model using sample data of the solution space. 2) At least in the calculation example of this paper, it is shown that the obtained reduced-order model has sufficient accuracy. 3) The relationship between the characteristics of the sample data and the accuracy (applicability range) of the reduced-order model is a future subject.