A continuous-adjoint based data assimilation technique coupled with Particle Image Velocimetry (PIV) error was proposed to optimize the objective loss function, thereby enhancing the robustness of the technique in different error scenarios. For verification, a given PIV flow field implanted with synthetic errors was selected as a preliminary test, and a further data assimilation test was implemented in the flow fields obtained with different parameter settings of the PIV cross-correlation algorithm. The results indicated that the continuous-adjoint algorithm coupled with the PIV error can discard the false experimental observations and improve the anti-interference ability and robustness, compared with its original counterpart. The high-fidelity flow fields can be well obtained using this data assimilation technique even in large error scenarios.
DENG Zhiwen
,
HE Chuangxin
,
LIU Yingzheng
. Continuous-adjoint based data assimilation technique coupled with particle image velocimetry error[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022
, 43(5)
: 125305
-125305
.
DOI: 10.7527/S1000-6893.2021.25305
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