Falcetelli, Francesco
(2023)
Qualification of optical fiber sensors for the structural health monitoring of aerospace structures, [Dissertation thesis], Alma Mater Studiorum Università di Bologna.
Dottorato di ricerca in
Meccanica e scienze avanzate dell'ingegneria, 35 Ciclo.
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Abstract
In recent years, composite materials have revolutionized the design of many structures. Their superior mechanical properties and light weight make composites convenient over traditional metal structures for many applications. However, composite materials are susceptible to complex and challenging to predict damage behaviors due to their anisotropy nature. Therefore, structural Health Monitoring (SHM) can be a valuable tool to assess the damage and understand the physics underneath. Distributed Optical Fiber Sensors (DOFS) can be used to monitor several types of damage in composites. However, their implementation outside academia is still unsatisfactory. One of the hindrances is the lack of a rigorous methodology for uncertainty quantification, which is essential for the performance assessment of the monitoring system. The concept of Probability of Detection (POD) must function as the guiding light in this process. However, precautions must be taken since this tool was established for Non-Destructive Evaluation (NDE) rather than Structural Health Monitoring (SHM). In addition, although DOFS have been the object of numerous studies, a well-established POD methodology for their performance assessment is still missing. This thesis aims to develop a methodology to produce POD curves for DOFS in composite materials. The problem is analyzed considering several critical points, such as the strain transfer characterizing the DOFS and the development of an experimental and model-assisted methodology to understand the parameters that affect the DOFS performance.
Abstract
In recent years, composite materials have revolutionized the design of many structures. Their superior mechanical properties and light weight make composites convenient over traditional metal structures for many applications. However, composite materials are susceptible to complex and challenging to predict damage behaviors due to their anisotropy nature. Therefore, structural Health Monitoring (SHM) can be a valuable tool to assess the damage and understand the physics underneath. Distributed Optical Fiber Sensors (DOFS) can be used to monitor several types of damage in composites. However, their implementation outside academia is still unsatisfactory. One of the hindrances is the lack of a rigorous methodology for uncertainty quantification, which is essential for the performance assessment of the monitoring system. The concept of Probability of Detection (POD) must function as the guiding light in this process. However, precautions must be taken since this tool was established for Non-Destructive Evaluation (NDE) rather than Structural Health Monitoring (SHM). In addition, although DOFS have been the object of numerous studies, a well-established POD methodology for their performance assessment is still missing. This thesis aims to develop a methodology to produce POD curves for DOFS in composite materials. The problem is analyzed considering several critical points, such as the strain transfer characterizing the DOFS and the development of an experimental and model-assisted methodology to understand the parameters that affect the DOFS performance.
Tipologia del documento
Tesi di dottorato
Autore
Falcetelli, Francesco
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
35
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
structural health monitoring; distributed optical fiber sensors; probability of detection; strain transfer; carbon fiber reinforced polymers;
URN:NBN
Data di discussione
17 Marzo 2023
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Falcetelli, Francesco
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
35
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
structural health monitoring; distributed optical fiber sensors; probability of detection; strain transfer; carbon fiber reinforced polymers;
URN:NBN
Data di discussione
17 Marzo 2023
URI
Gestione del documento: