Emanuele Conte
Optimization and implementation of a software code for the automated analysis of fatigue data.
Rel. Davide Salvatore Paolino, Andrea Tridello, Michele Maria Tedesco. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Dei Materiali, 2022
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (6MB) | Preview |
Abstract
Material fatigue is the most common cause of failures of components and must be properly considered during the design process. Fatigue is a highly structure-sensitive process, depending mainly on the material characteristics at sub microscopic and microscopic scale. If, in fact, samples of the same size and material are subjected to the same loading conditions, different results can be obtained. This induces a statistical variability of the material fatigue strength. Therefore, data obtained from fatigue tests should be analysed using statistical methodologies. The purpose of a statistical analysis of fatigue test results is to estimate the fatigue properties of the material, such as fatigue limit, or fatigue strength at a given number of cycles, S-N curve, etc., from the test data.
The least squares method is generally used for assessing the parameters of the S-N curve, in the finite life range, while the Staircase method is used for assessing the fatigue strength in the infinite life range of the Wӧhler curve
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
