Dynamic Feature Extraction and Data Mining for the Analysis of Turbulent Flows

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The objective of the proposed reserch is to develop a new class of data analysis methods. This will involve on-the-fly identification of physically-important events selectively store the data. This database will then be interrogated by feature extraction algorithms to yield an additional object database, which is a compact representation of the physically important space-time object trajectories. These database objects will be used as input to novel data mining methods to discover causal relationships between the objects. This approach will result in efficient storage of data, visualization of the important events within the data set, and methods for the high-level analysis of relationships between objects in the data.