DynamicStudio Dynamic Masking add-on

The presence of moving objects in PIV raw images is more a reality than an exception for PIV flow investigations today. The PIV investigations focusing on flows close to the boundary require accurate masking of the moving objects, and dynamic masking techniques are quite useful in digitally removing these objects from PIV raw images.

Rigid Object Tracking and Rigid Object Stabilization

The Dynamic Masking add-on can be used to remove rigid objects from PIV images. This is achieved by first tracking the rigid objects in the field of view (FoV) and then stabilizing them by making a coordinate transformation from a camera-fixed coordinate system to an object-fixed coordinate system. The new masking strategy is a combination of Rigid Object Tracking (ROT), Rigid Object Stabilization (ROS), and static masking.

The Dynamic Masking tool has been applied to a vibrating airplane model in a wind tunnel (see below). The model is vibrating due to aerodynamic forces (left) and is stabilized using ROT and ROS (right). First, a sub-image that contains the rigid object is selected, secondly, this image is tracked within the FoV and the sub-pixel shifts are determined (ROT). Thirdly the shifts are corrected to stabilize the object (ROS) and finally, a static mask is applied to the ROT and ROS-stabilized image.

Phase Boundary Detection

Accuracy of PIV measurements in two-phase flows is often reduced along the phase boundaries because the information from both phases is included in interrogation windows along the phase boundaries. Information along the phase boundary differs in terms of seeding density, velocity magnitude, and flow direction across the boundary. Phase-separated PIV measurements often minimize this problem and increase accuracy along the boundary by considering each phase separately.
The phase boundary detection module takes an image or double-framed image dataset and determines the phase boundaries in two-phase flows (flame fronts for combustion data or mixing of two liquids etc.). The method uses a combination of global thresholding and local thresholding to determine the phase boundaries. The gradient can also be used to subsequently filter away boundaries without a sharp gradient, which is most useful in flame front investigations in combustion diagnostics. The method can be used for dynamic masking, interface detection, and application of certain filters on the detected interface.

Phase Boundary Detection: For dynamic masking, interface detection, and more.

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