1304 Construction of a Data Mining Method for Unsteady Flow Field
Details
Large amounts of data regarding various physical phenomena can be acquired from CFD analysis of unsteady flow field. However, the post-process of the unsteady CFD data is usually performed by averaging each time-step data or by searching eventual correlations among points in the flow field. In those cases, most of the unsteady CFD data end up being unused. The objective of this work is to construct a Data Mining method for the post-process of unsteady CFD data. The Data Mining method in this study consists of a time-series analysis and a cluster analysis. The time dependent flow characteristics are extracted by the time-series analysis, while the features regarding space are extracted by the cluster analysis. The Data Mining method was applied to unsteady CFD data of base flow at transonic speed and it successfully captured instability of shear layer, shock wave and vortex shedding.
