Particle image velocimetry, delayed detached eddy simulation and data assimilation of inclined jet in crossflow

Abstract

This research employs a continuous adjoint data assimilation (DA) algorithm to enhance the prediction of three-dimensional flow behavior in the inclined round jet in crossflow (JICF). To rectify model-form errors arising from the Boussinesq approximation, a force correction is implemented, and the linear part of the eddy viscosity is incorporated for numerical stability. The DA model is theoretically derived to minimize discrepancies between particle image velocimetry (PIV) measurement and the numerical predictions of the primary-adjoint system, thus enabling determination of the optimal contribution of the force correction. Observational data are acquired through planar PIV measurement in the centerplane of JICF with a fixed velocity ratio of 1.2 and a bulk Reynolds number of 150,000. Delayed detached eddy simulation is validated using PIV results and serves as supplementary data for evaluating the reconstruction capabilities of the DA method. The research explores various regularization parameters in the data assimilation procedure, emphasizing their impact on eddy viscosity, correction force, and overall flow prediction accuracy. The findings underscore the effectiveness of regularization in promoting smoothness in the optimized field, thereby mitigating overfitting and irregular solutions. In-depth analyses of critical flow features, including counter-rotating vortex pairs and Reynolds stress forcing, provide insights into the accuracy achieved by the data assimilation procedure. Despite limited measurement data, the study demonstrates the capability of the presented method to successfully recover global flow fields.

Graphical abstract