IMAGE PRE-PROCESSING

SlugFlow is a C++ based software package developed within the Environmental Hydraulics Research Group at the University of Aberdeen by Dr S. Cameron. The software has been developed to streamline all PIV image processing and velocity field post processing tasks into a single unified package. Analysis is divided into three stages: (1) Image pre-processing, (2) Image analysis, and (3) Velocity field post-processing.

VELOCITY POST-PROCESSING

IMAGE ANALYSIS

Raw image Edge detection Background removed

Velocity vectors, vorticity contours Double-averaged velocity Power spectra Space-time correlations

Gradient-based edge detection, median filtering, and background removal algorithms are implemented and used to extract roughness geometry information and prepare images for further analysis by removing boundary reflections.

A number of FFT-based iterative cross corellation algorithms are implemented to extract fluid velocity data from raw images. A 2-pass discrete window shift method, with a peak computation performance of around 40 vector fields per second (1 Megapixel images) is used when fast analysis is required, i.e. for checking data quality before leaving the laboratory. For a more comprehensive analysis a 4-pass continuous window shift with

Built in functions for statistical analysis include double averaged fluid velocities, stresses and higher order moments of velocity probability distributions, frequency and wave number power spectra, correlation functions, and structure functions amongst others. All output files are formatted ready to be imported directly into Tecplot for plotting.

window deformation algorithm is preferred. Although measurement noise is reduced with this algorithm, the increased complexity and requirement for image interpolation reduces calculation speed to 2.5 vector fields per second.

Multi-camera algorithms for 3D-particle tracking and panoramic and stereoscopic PIV are under development.