Lucio Pinello

Lucio's research activities focus on self-sensing materials, high-fidelity models, and statistical and Machine Learning algorithms for Structural Health Monitoring and Health and Usage Monitoring Systems.

Advanced methods for Health and Usage Monitoring Systems: from smart materials to data-driven prognostics

Politecnico di Milano · 2026

1. In-situ monitoring of impact dynamics, indentation, and compression after impact (CAI) on CNT-doped GFRP panels by means of electrical monitoring

   L. Pinello, X. X. F. Sánchez-Romate, A. Vescovini, S. Cinquemani, D. Scaccabarozzi, F. Libonati, A. Jiménez Suárez, A. Ureña, C. Sbarufatti

   Structural Health Monitoring · 2025

2. Exploiting the self-sensing capabilities of buckypapers for in-situ monitoring of impacts and compression after impact on GFRP panels

   L. Pinello, B. Patel, M. Giglio, C. Sbarufatti

   Composite Structures 375, 119787 · 2026

3. MPCA-Based Domain Adaptation for Transfer Learning in Ultrasonic Guided Waves

   L. Pinello, F. Cadini, L. Lomazzi

   Structural Control and Health Monitoring 2026, 4747489 · 2026

1. Shape sensing and damage detection of composite pressure vessels using inverse finite element method coupled with physics-based strain pre-extrapolation

   J. Bardiani, R. Faure Ragani, L. Pinello, A. Kefal, A. Manes, C. Sbarufatti

   Thin-Walled Structures, 218, 113935 · 2026

2. Preliminary Nose Landing Gear Digital Twin for Damage Detection

   L. Pinello, O. Hassan, M. Giglio, C. Sbarufatti

   Aerospace, 11(3), 222 · 2024

All group publications

• Teaching assistant in 2025/2026

  Lab – Structural Health and Usage Monitoring in Action

  MSc Mechanical Engineering · 5 CFU · 2nd semester · Milano Bovisa

  Lecturer: Claudio Sbarufatti

  Course sheet

Courses of 2026/2027, from the Politecnico’s course sheets. All the group’s courses

• 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