Probabilistic damage tolerance analysis using inspection data from integrated sensors

ABSTRACT : Fatigue failures are common failures within the aeronautical field. microcracks appear after many repetitions of cyclic stresses, then, these microcracks grow until a point of no return is reached and the growth becomes unstable and imminent. It is hard to do reliable estimations of a system subject to fatigue due to multiple random factors that affect the material, geometry, and stresses, among others. In this work, to estimate this type of failure, a probabilistic analysis is performed, where each parameter from the model is represented as a probability density function. This work presents a software application to perform fatigue failure analysis using MATLAB and SMART|DT. This last program follows the standards issued by the Federal Aviation Administration of United States (FAA). The application implements a Bayesian inference process to update the model’s crack size distribution when inspections are performed, to add more accuracy to risk predictions. This application is expected to support decisions about when to perform inspections based on an allowable desired risk for the fleet.

• Autores: Vallejo Ciro, María Isabel; Carvajal Loaiza, Manuel José
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2021
• Institución: Universidad de Antioquia
• Repositorio: Repositorio UdeA
• Idioma: eng
• OAI Identifier: oai:bibliotecadigital.udea.edu.co:10495/25415
• Acceso en línea: http://hdl.handle.net/10495/25415
• Palabra clave: Aeronautics - Safety measures; Aeronáutica - medidas de seguridad; Fracture of solids; Fractura de sólidos; Fracture strength; Resistencia a las fracturas; Materials fatigue; Fatiga de materiales; Probabilities; Probabilidades; Residual stresse; Esfuerzos residuales; Stability of airplanes; Estabilidad de los aviones; Sensors; Sensores; Bayesian updating; http://aims.fao.org/aos/agrovoc/c_28279
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-sa/2.5/co/