@mastersthesis{10902/20122,
year = {2020},
month = {7},
url = {http://hdl.handle.net/10902/20122},
abstract = {ABSTRACT: This work is framed in the context of a muography experiment, a safe, non-destructive testing technique allowing to study the internal properties of physical objects. This method is emerging in the industry, for instance, to study the degradation of industrial equipment such as pipes, furnaces or cauldrons.
This project aims at developing a new framework that allows to perform a maximum likelihood estimation method on relevant geometrical parameters of such equipment, focusing on a particular case: gas pipes. In this context, a new C++ framework has been developed in order to i) recreate the geometry associated to the problem, ii) study the results of a muography experiment from a statistical point of view, and iii) define a coherent way to estimate the optimal geometry. In particular, once defined and fully tested, this framework allows us to determine the thickness of steel pipes with a precision of the order of 1 millimeter.},
abstract = {RESUMEN: Este proyecto tiene como objetivo el desarrollo de un framework que permita realizar una estimación de máxima verosimilitud sobre parámetros relevantes de dicho equipamiento industrial, centrándose en un caso particular: tuberías de gas. En este contexto, un nuevo framework en C++ ha sido desarrollado con el objeto de i) recrear la geometría asociada al problema, ii) estudiar los resultados del experimento de muografía desde un punto de vista estadístico, y iii) definir un modo coherente de estimar la geometría óptima. En particular, una vez programado y testado, el framework nos permite determinar el espesor de una tubería de acero con una precisión del orden de 1 milímetro.},
title = {Development of a statistical analysis framework in the context of Muography applied to the industry},
author = {Prieëls, Cédric},
}