Tesis:
Correlation of spacecraft termal mathematical models to reference data
- Autor: TORRALBO GIMENO, Ignacio
- Título: Correlation of spacecraft termal mathematical models to reference data
- Fecha: 2019
- Materia: Sin materia definida
- Escuela: E.T.S.I. AERONÁUTICA Y DEL ESPACIO
- Departamentos: MECANICA DE FLUIDOS Y PROPULSIÓN AEROESPACIAL
- Acceso electrónico: http://oa.upm.es/57695/
- Director/a 1º: PÉREZ GRANDE, Isabel
- Director/a 2º: SANZ ANDRÉS, Ángel
- Resumen: Model-to-test correlation is a frequent problem in spacecraft-thermal control design. The goal of correlation is to determine the values of the parameters of the thermal mathematical model (TMM) that allows reaching a good _t between the TMM results and test data. This way the uncertainty of the mathematical model is reduced. Quite often, this task is performed manually, mainly because a good engineering knowledge and experience is needed to reach a successful compromise, but the use of a mathematical tool could undoubtedly facilitate this work. The correlation process can therefore be considered as the selection of the model parameters that minimize the error of the model results with regard to the reference data. In this doctoral dissertation, a simple method (GIPI) is presented. The method is suitable to solve the TMM-to-test correlation problem, using Jacobian matrix formulation and Moore-Penrose pseudo-inverse, generalized to include several load cases. Aside, in simple cases, this method also allows for analytical solutions to be obtained, which helps to analyze some problems that appear when the Jacobian matrix is singular. To show the implementation of the method, two problems have been considered, one more academic, consisting of a simple 4-node model, and the other one a complex model, the TMM of the optical unit of PHI, one of the remote sensing instruments of the ESA mission Solar Orbiter. The method has given satisfactory reslts in both cases. The convergence of the method has been studied and compared with several methods and the time required by this method (GIPI) subtantially outperforms the other methods.