Applying numerical modeling to experimental data for improved optical diagnostics of fluid flows

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Experimental research into the motion of fluid in academic and industrial applications is now dominated by digital techniques. Cameras are used to take images of tracer particles seeded into the flow to track their movement, inferring the motion of the fluid. This technology has been developed over the last 30 years to a point where it is now compatible with even the most detailed numerical simulations. Importantly, these experimental techniques include all of the physics of the flow problem. They are therefore used as direct validation of the numerical approaches as well as a tool in academia and industry to investigate a wide variety of flows. A large family of these techniques now exist based on particle image velocimetry (PIV) and particle tracking velocimetry (PTV). These multi-camera systems have many challenges in the setup, the collection of data and the processing through to descriptive velocity fields.****A new approach to collect images of particle locations over three dimensions (3D) from a single camera is based on collecting the entire light field seen by the camera. Termed plenoptic imaging, the camera has a microlens array that allows small angle perspective viewing of particle locations. This type of imaging system, using only a single camera, promises to be significantly easier to install and setup in a flow system, especially where viewing access is limited. It also allows, for the first time, realistic measurement of three-dimensional flows at the microscale such as the flow in porous media and microscale biological flows. This project will continue to develop this type of camera system for experimental use by developing a general calibration procedure, data collection and processing and advanced approaches based on PTV and numerical models of particle motion to provide high-quality flow measurement.****With any particle imaging velocimetry technique, an appropriate methodology is needed to determine the uncertainty in the derived velocity vector. As yet, no generalised method for determining the uncertainty in a PIV or PTV measurement is available due to the complex interaction of the experimental setup and the computational processing of the data collected. This is a significant fundamental problem that has a strong impact across the experimental thermo-fluid community, both in academia and industry. A significant part of this project will be the development of a generalised methodology for determining the uncertainty in all of these types of particle image velocity measurement systems.****This project will train HQP in the areas of optical instrumentation and fluid mechanics developing new knowledge and science. Impact will be felt in both academia and industry where these techniques are unitized.******