A constrained reduced order model (ROM) based on proper orthogonal decomposition (POD) is proposed to achieve fast and accurate prediction of steady hypersonic flows. The proposed method addresses the convergence issue of the projection-based POD ROM which violates the boundary conditions by using a constrained Gauss-Newton iterative process. The constraints in the iteration are formulated by satisfying the physical boundary conditions. To achieve this, a weighting matrix constructed by an improved Gauss weighting function is adopted to determine the contribution of each cell to the constraint term. The proposed constrained reduced-order method is accelerated by a parallel algorithm based on message passing interface (MPI) and load balancing, which makes the method practical for prediction of complex flows with large memory cost. Fast predictions of hypersonic flows over the two-dimensional cylindrical blunt body and the three-dimensional reentry vehicle using the constrained reduced-order method show that the error is significantly smaller than that of the interpolation-based POD ROM and the projection-based POD ROM. Computing efficiency is increased by 2 ∼ 3 orders of magnitude compared to CFD.
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