Date of Award:


Document Type:


Degree Name:

Master of Science (MS)


Mechanical and Aerospace Engineering

Committee Chair(s)

Ryan B. Berke


Ryan B. Berke


Thomas Fronk


Nadia Kouraytem


In extreme environments, such as hot-fire rocket testing, gathering strain data can be challenging due to temperature constraints. Traditional methods for measuring material deformation such as strain gages, a small device attached to a test specimen, cannot withstand the extreme temperature and tend to burn off. When these situations occur non-contacting methods such as Digital Image Correlation (DIC) are preferable. DIC is an optical method of measuring strains across the material’s entire surface by using a camera to track the deformation of a speckle pattern applied to the surface of a deforming object. When used at temperatures above approximately 500°C, the light emitted may saturate the camera image. A popular approach to high temperature DIC is to collect light in shorter wavelengths than emitted by the specimen, such as UV light. However, in a high-speed environment, UV-DIC has not previously been used as most high-speed cameras do not detect UV light. In the first portion of this thesis, UV-DIC is demonstrated using a device known as a UV intensifier that can essentially convert UV light into visible light that a high speed camera can detect.

Furthermore, for some materials used in the tracking pattern, a specimen initially speckled with a dark background and a light speckle at room temperature may then invert at high temperature to appear as a bright background with a less bright speckle. It was recently shown that this inversion can be mitigated by subtracting two images one containing emitted light and one containing emitted and reflected light. With the subtraction method no motion can occur between the subtracted images, limiting the approach to quasi-static measurements. In the second portion of this thesis, another approach is demonstrated which uses a color camera paired with a blue light source. Since color images can be split into the three color spaces red, green, and blue, the green data provides an inverted speckle image while the blue data provides an un-inverted speckle image, thus removing the requirement that both image be subtracted, and allowing data collection during faster experiments.