Work presented at ENSEIRB-MATMECA in the Institut National Polytechinique de Bordeaux as a second-year internship, carried out at the Laboratoire de l’Intégration du Matériau au Système (IMS) and Institut de mécanique et d’ingénierie (I2M).
Author: Lucas Furlan Supervisors: Stéphane Victor, Jean-Luc Battaglia and Andrzej Kusiak.
This repository contains all matlab files used during the thermal analysis of a thermocouple and its coupled system. It includes:
- Solution for heat equation in frequency domain for one-dimensional and two-dimensional models;
- One-dimensional and two-dimensional axisymmetric finite difference method;
- Polynomial class implementation.
The files are divided into four different main subdirectories for each analysis. The database contains the raw data in TXT files and also the equivalent in MAT files (matlab variables). They are saved as a thermalData class, which is defined in myClasses directory, as well as other class definitions. All functions have their own help context implementation, meaning that the command help functionName will display its description. It also works with directories, for instance help freqAnalysis displays its structure with some instructions. Finally, the output figures are saved in outFig, which is generated in the first code execution and can be changed in analysisSettings.m file.
The freqAnalysis directory presents files used to generate the frequency response of all models, including their polynomial approximations. The file also generates some TEX files for reporting and
Files for theoretical comparison using analytical and numerical models. Contains the three finite difference methods implemented and the convergence of numerical methods.
Sets of all functions used to identify the system parameters, including model convergence, model delay convergence and model inversion. The convergence is analyzed for four different noise structures: OE, ARX, ARMAX and BJ, using the system identification toolbox. Uses a minimum phase filter approximation and an optimization of future time step prediction to estimate the heat flux.
Input identification for reentry data. Uses the reentry heat flux data as a reference to generate a tension input to the power source.
Analyze the noise in the data using an oscilloscope and DAS acquired data.