Publications
Peer-Reviewed Journal Papers
Value of Information-based assessment of strain-based thickness loss monitoring in ship hull structures
Ocean Engineering, 357, 125434, (2026),
10.1016/j.oceaneng.2026.125434.
Vibration-based Bayesian updating of hull girder finite element models
Ocean Engineering, 342, 123068, (2025),
10.1016/j.oceaneng.2025.123068.
On decision-theoretic model assessment for structural deterioration monitoring
Mechanical Systems and Signal Processing, 222, 111776 (2025),
10.1016/j.ymssp.2024.111776.
Deep learning-based surrogate models for spatial field solution reconstruction and uncertainty quantification in Structural Health Monitoring applications
Computers & Structures, 301, 107462, (2024),
10.1016/j.compstruc.2024.107462.
Maximum likelihood estimation of probabilistically described loads in beam structures
Probabilistic Engineering Mechanics, 76, 103627, (2024),
10.1016/j.probengmech.2024.103627.
Optimal sensor placement for corrosion induced thickness loss monitoring in ship structures
Marine Structures, 93, 103524 (2024),
10.1016/j.marstruc.2023.103524.
Damage detection in ship hull structures under operational variability through strain sensing
Ocean Engineering, 286, 115537 (2023),
10.1016/j.oceaneng.2023.115537.
Spectral fatigue analysis of ship structures based on a stochastic crack growth state model
International Journal of Fatigue, 176, 107878 (2023),
10.1016/j.ijfatigue.2023.107878.
Structural health monitoring for corrosion induced thickness loss in marine plates subjected to random loads
Ocean Engineering, 273, 114037 (2023),
10.1016/j.oceaneng.2023.114037.
Data-driven probabilistic quantification and assessment of the prediction error model in damage detection applications
Probabilistic Engineering Mechanics, 71, 103412 (2023),
10.1016/j.probengmech.2023.103412.
Static strain-based identification of extensive damages in thin-walled structures
Structural Health Monitoring, 21(5), 2026–2047 (2022),
10.1177/14759217211050605.
Preprints
A hierarchical Bayesian approach for population-based structural health monitoring in ship hull structures
arXiv preprint (2025),
arXiv:2510.16316.
Surrogate modeling for stochastic crack growth processes in structural health monitoring applications
arXiv preprint (2023),
arXiv:2310.07241.
Thesis
Structural health monitoring of deteriorating ship hull structures
(2025),
10.12681/eadd/58332.
Conference Papers
Estimation of the Size of a Growing Crack Through Strain Sensing Under Uncertainty
ICEAF VIII, (2025),
10.3390/engproc2025119003.
Corrosion State Diagnosis of Ship Hull Structures Through Strain Sensing
Innovations in Sustainable Maritime Technology—IMAM 2025, pp. 159-171, (2025)
10.1007/978-3-032-01566-2_13.
Quantifying the value of information for structural health monitoring of deteriorating ship hull structures
Innovations in the Analysis and Design of Marine Structures, pp. 387-395, CRC Press (2025),
10.1201/9781003642411-46.
A hierarchical Bayesian approach for parameter identification in structural deterioration models using probabilistic surrogate models
E-Journal of Nondestructive Testing, 29(7) (2024),
10.58286/29571.
Reduction of the model prediction error in vibration-based SHM applications
E-Journal of Nondestructive Testing, 29(7) (2024),
10.58286/29603.
Uncertainty quantification within strain-based SHM schemes used for detecting thickness loss in ship hulls
Advances in the Analysis and Design of Marine Structures, pp. 743–750, CRC Press (2023),
10.1201/9781003399759-82.
From preventive to predictive maintenance of ship hulls: The role of SHM
SOME, (2023),
10.5957/SOME-2023-033.
Holistic Design of a Twin-Hull Short-Sea Shipping Vessel With Hybrid-Electric Propulsion
IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC), (2023),
10.1109/ESARS-ITEC57127.2023.10114881.
On the Detection of Thickness Loss in Ship Hull Structures Through Strain Sensing
In P. Rizzo & A. Milazzo (Eds.), European Workshop on Structural Health Monitoring, (2022),
10.1007/978-3-031-07258-1_22.
Statistical Pattern Recognition for Optimal Sensor Placement in Damage Detection Applications
In P. Rizzo & A. Milazzo (Eds.), European Workshop on Structural Health Monitoring, (2022),
10.1007/978-3-031-07258-1_23.
An Optimization Based Approach for Damage Identification of Idealized Ship Structural Assemblies
(OMAE) Volume 2: Structures, Safety, and Reliability, (2021),
10.1115/OMAE2021-60810.