Data assimilation of three-dimensional turbulent flow using lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

Hasegawa, Yuta   ; Onodera, Naoyuki   ; Asahi, Yuichi   ; Idomura, Yasuhiro   

This study implemented and tested the ensemble data assimilation (DA) of turbulent flows using the lattice Boltzmann method and the local ensemble transform Kalman filter (LBM-LETKF). The computational code was implemented fully on GPUs. The test was carried out for the 3D turbulent flow around a square cylinder with meshes and 32 ensemble members using 32 GPUs. The time interval of the DA in the test was a half of the period of the Kalman vortex shedding. The normalized mean absolute errors (NMAE) of the lift coefficient were 132%, 148%, and 13.2% for the non-DA case, the nudging case (a simpler DA algorithm), and the LETKF case, respectively. It was found that the LETKF achieved good DA accuracy even though the observation was not frequent enough for the small scale turbulence, while the nudging showed systematic delays in its solution, and could not keep the DA accurately.