The present thesis investigates the application of the Inverse Finite Element Method (iFEM) for the Structural Health Monitoring (SHM) of naval structures, with the ultimate goal of integrating predictive maintenance strategies into ship operations. The research focuses on a scaled experimental model of a German frigate, specifically designed and manufactured to evaluate the capability of the iFEM to reconstruct structural deformations and, thereby, detect damages and localize their position under both static and dynamic conditions. The experimental activity was conducted at the towing tank facilities of CNR-INM in Rome, using a 1:28-scale segmented model composed of a hollow aluminum backbone connected to six hull segments. Four optical fibers based on Fiber Bragg Grating (FBG) technology were installed along the backbone to measure local strain distributions in real time. Static tests were performed to validate the sensor network and the iFEM implementation by comparing the reconstructed deflections with analytical, FEM and laser measurements, while dynamic tests were carried out under regular and irregular wave conditions, with varying levels of structural damage, to assess the method’s capability to detect and localize damage under realistic operating conditions. Results from the static tests show good agreement between iFEM and the other measurements, with deviations below 2%, confirming the accuracy of both the experimental setup and the inverse formulation. The dynamic tests further proved that iFEM can identify and localize damage through strain-based anomaly indices, even under complex hydrodynamic loading. Overall, the findings validate the iFEM as an effective and computationally efficient technique for shape sensing and damage monitoring of naval structures, representing a step toward the digitalization of ship maintenance and the implementation of predictive strategies that enhance safety, reduce costs and extend service life.
La presente tesi indaga l’applicazione del Metodo degli Elementi Finiti Inverso (iFEM) per il Monitoraggio dell’Integrità Strutturale (SHM) di strutture navali, con l’obiettivo finale di integrare strategie di manutenzione predittiva nelle operazioni navali. La ricerca si concentra su un modello sperimentale in scala di una fregata tedesca, appositamente progettato e realizzato per valutare la capacità dell’iFEM di ricostruire le deformazioni strutturali e, di conseguenza, rilevare e localizzare i danni in condizioni sia statiche che dinamiche. L’attività sperimentale è stata condotta presso le vasche navali del CNR-INM di Roma, utilizzando un modello a segmenti in scala 1:28, costituito da un backbone in alluminio cavo collegato a sei segmenti di scafo. Lungo il backbone sono state installate quattro fibre ottiche basate sulla tecnologia a reticolo di Bragg (FBG) per misurare in tempo reale la distribuzione locale delle deformazioni. Sono state eseguite prove statiche per validare la rete sensoriale e l’implementazione dell’iFEM, confrontando le deformazioni ricostruite con misure analitiche, FEM e laser, mentre le prove dinamiche sono state svolte in condizioni di mare regolare e irregolare, con diversi livelli di danneggiamento strutturale, per valutare la capacità del metodo di rilevare e localizzare il danno in condizioni operative realistiche. I risultati delle prove statiche mostrano un buon accordo tra iFEM e le altre misurazioni, con scostamenti inferiori al 2%, confermando l’accuratezza sia dell’apparato sperimentale sia della formulazione inversa. Le prove dinamiche hanno inoltre dimostrato che l’iFEM è in grado di identificare e localizzare i danni attraverso indici di anomalia basati sulla deformazione, anche in presenza di carichi idrodinamici complessi. Nel complesso, i risultati convalidano l’iFEM come tecnica efficace e computazionalmente efficiente per il rilevamento della forma e il monitoraggio dei danni nelle strutture navali, rappresentando un passo verso la digitalizzazione della manutenzione navale e l’implementazione di strategie predittive in grado di aumentare la sicurezza, ridurre i costi e prolungare la vita operativa delle imbarcazioni.
Application of iFEM for shape sensing and damage detection on a naval scale model
Annoni, Marco Carlo
2024/2025
Abstract
The present thesis investigates the application of the Inverse Finite Element Method (iFEM) for the Structural Health Monitoring (SHM) of naval structures, with the ultimate goal of integrating predictive maintenance strategies into ship operations. The research focuses on a scaled experimental model of a German frigate, specifically designed and manufactured to evaluate the capability of the iFEM to reconstruct structural deformations and, thereby, detect damages and localize their position under both static and dynamic conditions. The experimental activity was conducted at the towing tank facilities of CNR-INM in Rome, using a 1:28-scale segmented model composed of a hollow aluminum backbone connected to six hull segments. Four optical fibers based on Fiber Bragg Grating (FBG) technology were installed along the backbone to measure local strain distributions in real time. Static tests were performed to validate the sensor network and the iFEM implementation by comparing the reconstructed deflections with analytical, FEM and laser measurements, while dynamic tests were carried out under regular and irregular wave conditions, with varying levels of structural damage, to assess the method’s capability to detect and localize damage under realistic operating conditions. Results from the static tests show good agreement between iFEM and the other measurements, with deviations below 2%, confirming the accuracy of both the experimental setup and the inverse formulation. The dynamic tests further proved that iFEM can identify and localize damage through strain-based anomaly indices, even under complex hydrodynamic loading. Overall, the findings validate the iFEM as an effective and computationally efficient technique for shape sensing and damage monitoring of naval structures, representing a step toward the digitalization of ship maintenance and the implementation of predictive strategies that enhance safety, reduce costs and extend service life.| File | Dimensione | Formato | |
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2025_12_Annoni_Tesi.pdf
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Descrizione: Tesi Annoni
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2025_12_Annoni_Executive Summary.pdf
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Descrizione: Executive summary Annoni
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https://hdl.handle.net/10589/247008