Student research opportunities
Photographic reflectivity measurement
Project Code: CECS_843
This project is available at the following levels:
CS single semester, Engn4200, Engn R&D, Honours, Summer Scholar
Please note that this project is only for undergraduate students.
Supervisor:
Dr John PyeOutline:
The student will determine the feasibility of performing reflectivity measurements optically with the use of a camera situated at the focal point to record images of the sky as it appears over the surface of a paraboloidal mirror or dish.
Paraboloidal dishes are designed to focus incoming parallel rays to a focal point. When viewing the surface of an ideal paraboloidal concentrator from the focal point, the image that appears across the surface originates from parallel light rays that are incident perpendicular to the average surface direction. For a non-ideal, good quality concentrator, the variation of the angle of light incident on the collector and perceived at the focal region should be small, with an accordingly small variation in intensity and spectrum in the sky-image on the concentrator surface. It should follow that any perceived variation in intensity in this image can mostly be attributed to reflectivity variations. From this information a reflectivity profile of the dish may be determined.
Experiments performed by the student will involve obtaining photos of the sky as imaged onto a paraboloidal dish or mirror surface when viewed from the focal point. Image processing of the photos will be conducted in an attempt to obtain a relative reflectivity profile of the reflective surface. From this, the student may then be able to devise a method for determining the average reflectivity of the collector as well as the absolute reflectivity for a given image pixel. If time permits, estimation of the uncertainty associated with this technique may be performed.
Goals of this project
* experimentally determine dish reflectivity using reflections from a small portion of the sky
* undertake an analysis of the accuracy of the method and assess its value for ongoing use in experimental work
Requirements/Prerequisites
There will be some significant computer programming involved, probably in the Python language (which is fairly easy to learn if you know Java, C, Matlab or similar).
