A schlieren motion estimation method for seedless velocimetry measurement

Abstract

Schlieren imaging is a widely used technique for flow visualization in thermal fluid investigations due to its high sensitivity, flexibility and ease of use. In this paper, a schlieren motion estimation (SME) algorithm is developed by adopting the physical-based constraints and a second-order div-curl regularizer to provide a dense motion field. A simple quadratic penalty function is utilized. The computing scheme is established using the variation method, while the global cost function is derived and minimized to resolve the velocity field. A standard coarse-to-fine scheme is integrated to deal with large displacements. The proposed method has been applied on a co-flow methane jet flame before and during the ignition process. The velocity and vorticity has been estimated and compared to the results obtained by an optimized optical flow (OF) method, which used conventional smoothness constraint assumptions and advanced optimization techniques to improve the robustness. The comparison indicates that SME method is able to resolve more details in the flow field, showing better continuity in the main flow region and also the boundaries. Although being more sensitive to the weight parameter values, the SME method still shows good robustness in the test cases. The variation method used in current study also supplies the flexibility for integrating advanced optimization techniques to further improve the SME computing scheme.