Date of Award
Master of Science in Engineering
Mechanical and Aerospace Engineering
Dr. Javier Montefort
Dr. Tianshu Liu
Dr. Christopher Cho
Dr. Parviz Merati
Masters Thesis-Open Access
This thesis describes the different methods used when trying to solve inverse heat transfer problems, particularly those involving recovering heat flux. There are currently several techniques to measure the temperature history in an object subjected to heat transfer using various temperature sensors, however these types of sensors are gradually being replaced by Temperature Sensitive Paints (TSP), a technique that is more accurate and provides a better spatial resolution. TSP is a polymer that is applied on a base object. Changes in temperature in the polymer result in variations of the luminescence intensity in the paint. These variations can be captured by a monochrome Coupled Charged Device (CCD) camera, with a grayscale. Knowing the temperature history at the surface of an object will allow for the recovery of the heat flux provided that the inverse problem can be solved.
Liu, along with others, have studied, created, and tested solutions that would allow the heat flux to be recovered analytically considering a semi-infinite base (Liu 2010) as well as a finite base (Liu 2017). A numerical solution to recover the heat flux history using a finite base for TSP data was presented by Cai (Cai 2017). However, depending on the size of the image used to measure the temperature history of an object and the number of images, both solutions might require a significant amount of time, sometimes days, to recover the heat flux of the object. Using MATLAB the method created by Liu was optimized so that the time required to recover the heat flux history has been significantly reduced from about 2 days to 30-60 seconds.
Schick, Nathan, "Optimization of Analytical Inverse Heat Transfer Recovery Solution" (2018). Master's Theses. 3797.