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Politecnico di Milano, SIGMA Lab
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Portrait of Libero Lucii

Libero Lucii

PhD Student · Cycle 40

Supervised by Claudio Sbarufatti

libero.lucii@polimi.it
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Research

Libero’s research focuses on the development of advanced methodologies for real-time Structural Health Monitoring (SHM) of components subjected to dynamic loading. His work combines physics-based approaches, including the inverse Finite Element Method (iFEM) for rotating machinery, with data-driven techniques such as transfer learning, autoencoders, and LSTM networks for anomaly and damage detection. He also investigates ultrasonic guided waves for the detection, localization, and identification of damage in composite structures, with the broader goal of enabling reliable predictive maintenance strategies.

Open thesis topics

  • SHMDigital TwinsiFEMMachine Learning

    Displacement Field Reconstruction Using the iFEM Methodology on a Rotating Shaft for Imbalance Detection

    Building on strain data, this research aims to develop advanced iFEM methods for damage and imbalance identification by integrating physics-based models with machine learning techniques. The study will also incorporate pre-extrapolation methods to enhance prediction accuracy. Furthermore, adaptive strategies will be designed to accommodate varying shaft boundary conditions, ensuring robust and reliable full-field displacement reconstruction under realistic operational scenarios.

    Details and apply
  • SHMSensingImpact & BallisticsCompositesExperimental

    Self-Sensing Composite Structures for Impact Damage Detection Using CNT Buckypapers

    This thesis investigates impact damage detection, localisation, and characterisation in heterogeneous composite structures through the integration of self-sensing layers. A composite specimen is designed and manufactured using multiple material phases (e.g. CFRP and ceramic-like layers), embedding CNT buckypapers at different depths within the laminate.

    Details and apply

All thesis topics

Research in images

Experimental rotating-shaft test rig for Structural Health Monitoring, including the tested shaft, motor and inverter control, accelerometers, encoder, thermocouple, and NI/LabVIEW data acquisition system.
Experimental rotating-shaft test rig for Structural Health Monitoring, including the tested shaft, motor and inverter control, accelerometers, encoder, thermocouple, and NI/LabVIEW data acquisition system.
Schematic representation of the inverse Finite Element Method (iFEM) applied to a rotating shaft. The shaft is discretized into two inverse finite elements and three nodes, with strain sensors distributed along the structure to provide the measurements required for deformation and structural-state reconstruction.
Schematic representation of the inverse Finite Element Method (iFEM) applied to a rotating shaft. The shaft is discretized into two inverse finite elements and three nodes, with strain sensors distributed along the structure to provide the measurements required for deformation and structural-state reconstruction.
Influence of iFEM discretization on rotating-shaft reconstruction accuracy. Box plots show the variability of rotation, deformation-shape, and displacement errors for models with 1 to 11 inverse finite elements during steady-state operation.
Influence of iFEM discretization on rotating-shaft reconstruction accuracy. Box plots show the variability of rotation, deformation-shape, and displacement errors for models with 1 to 11 inverse finite elements during steady-state operation.
Full-field displacement reconstruction of a rotating shaft using iFEM and FBG strain measurements, shown as an illustrative representation of the theoretical operating principle.