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Abstract

This article presents two over-looked post-processing techniques which provide the investigator with additional tools for data analysis and visualization. Both techniques exploit the trend for planar experimental data collection and are implemented in two-dimensions. Critically, both techniques are suitable for use on computational and experimental datasets, require no a-priori knowledge of the flow-field, and minimal user interaction during processing. Firstly, line integral convolution will be introduced as an alternative to streamline or in-plane velocity vector visualization. Secondly, a feature identification procedure will be outlined that can be used to reduce datasets for clearer visualization and provide quantitative information about topological flow features.

Keywords

line-integral convolution vortex identification critical-point analysis visualization

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Planar visualization of vortical flows

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