A wake tracking approach for two-phase Schlieren. (May 2018) - Davis, Ian; O'Reilly Meehan, Rudi; Nolan, Kevin; Grennan, Kieran; Murray, Darina
Highlights: A new method is presented for extracting flow information from Schlieren data. Algorithm identifies discrete flow structures using edge-based tracking methods. Spatio-temporal evolution of these edges is monitored using a Haar–Canny approach. Method is applied to Schlieren of an air bubble sliding under an inclined surface. Coherent flow features and near wake velocimetric information can be extracted. Abstract: Schlieren photography is a well-studied and long-standing technique. With the modern ubiquity of high-speed and high-resolution imaging equipment there is an opportunity for direct measurements of complex fluidic phenomena without the requirement for a seeding medium. Various techniques have been proposed for extracting flow information from Schlieren flow fields, but typically require either custom experimental setups or specific flow conditions. In this work, we present a new method for the extraction of quantitative flow information from Schlieren data. This algorithm identifies discrete structures within the flow by using edge-based tracking methods and continuously monitoring the spatio-temporal evolution of these edges using a combined Haar–Canny approach. This method is validated by means of previous Schlieren experiments of an air bubble sliding underneath a heated, inclined surface. This algorithm works in the general case for laminar and turbulent flows and has been found to extract coherent flow features and quantitative near wake velocimetric information. It is also suitably robust to be applied retro-actively to other existing Schlieren data.