A study on a flow/acoustic field hybrid model for turbomachinery based on the permeable data surface

To address the limitations of the ducted blade-row acoustic analogy (DBAA) method in multi-stage turbomachinery where the acoustic source modeling does not adequately consider blade row shielding effects, this paper proposes a novel acoustic analogy method, DBAA_PDS, based on the permeable data surface (PDS), for ducted blade-row noise prediction, combining Goldstein’s acoustic analogy methodology, and further develops a flow/acoustic field hybrid model based on this method. This hybrid model acquires key parameters, such as unsteady loading on the permeable data surface through three-dimensional numerical simulation, which are then input into the DBAA_PDS method as acoustic sources to calculate the sound pressure levels for each acoustic mode. A two-stage fan model is taken as the test case, and the experimentally validated three-plane pressure modal matching (TPP) method is used as a reference. The comparison reveals that, for most acoustic modes, the proposed method DBAA_PDS can effectively calculate modes shielded by blade rows, with certain modes achieving a 67% improvement in accuracy over the DBAA method. To reduce computational costs, further investigation on a single-stage fan model reveals that both the TPP and DBAA_PDS methods have the same requirement for the grid number in the physical computational domain. Moreover, the results calculated by DBAA_PDS method demonstrate better robustness in the axial direction compared to the TPP method.