The invention discloses a
pressure vessel lower chamber
model order reduction method combining sparse grids and POD, and the method comprises the steps: adding one to the grade of the sparse grids after iteration initialization, and obtaining test grid points according to important grid points; executing the lower chamber full-order computational fluid
mechanics model corresponding to the test grid points to obtain a first snapshot; reconstructing a second snapshot by using the mapping relation and the POD
modal matrix; calculating a root-mean-
square error of the two snapshots, and if the root-mean-
square error is smaller than a threshold value, completing construction of a reduced-order model Otherwise, the grid points with the errors meeting the requirements are stored in a non-important grid
point set, the grid points which do not meet the requirements are marked as important grid points, and the snapshot matrix is updated. Performing
singular value decomposition on the snapshot matrix, updating the mapping relation, judging whether the maximum
sparse grid grade is reached or not, and continuing iteration if the maximum
sparse grid grade is not reached. According to the method, the field distribution of the thermal hydraulic parameters in the lower chamber can be quickly obtained through matrix algebraic operation, and the method can be used for application scenes such as parameterization analysis, design optimization and digital twinning.