Technical Paper
An Automated Proper Orthogonal Decomposition-Based Post-processing of In-Cylinder Raw Flow Datasets
2022-08-31
2022-01-5061
Laser-based diagnostic techniques like particle image velocimetry (PIV) and molecular tagging velocimetry (MTV) are used to measure flow fields at a high spatial resolution. Post-processing of the obtained flow fields is essential for outlier correction as the datasets may be skewed by local flow vectors with a disproportionate disparity in magnitude or directions from neighborhood vectors. The rationale behind this work is to propose an algorithm using proper orthogonal decomposition (POD), namely, POD-OROC (POD-based outlier removal and outlier correction), which can correct outliers in an ensemble of flow fields. The proposed algorithm is first validated on synthetic flows with a known percentage of outlier rate and then applied to engine in-cylinder flow fields. The algorithm ran for a few iterations for both flow datasets and rejected frames with high outlier rates (above 15%) and then post-processed the remaining ones to detect and correct local spurious vectors.