Claudio Sbarufatti 
- : Particle filter-based fatigue damage prognosis by fusing multiple degradation models. In: Structural Health Monitoring.
- (2023): Research on a quantitative fault diagnosis method for rotor rub-impact. In: Structural Health Monitoring, v. 23, n. 3 (September 2023).
- (2023): Qualification of distributed optical fiber sensors using probability of detection curves for delamination in composite laminates. In: Structural Health Monitoring, v. 22, n. 5 (February 2023).
- (2023): Debonding quantification in adhesive bonded joints by the inverse finite element method. In: Smart Materials and Structures, v. 32, n. 4 (2 March 2023).
- (2022): Particle filter-based delamination shape prediction in composites subjected to fatigue loading. In: Structural Health Monitoring, v. 22, n. 3 (September 2022).
- (2022): Particle filter‐based hybrid damage prognosis considering measurement bias. In: Structural Control and Health Monitoring, v. 29, n. 4 (14 March 2022).
- (2019): Modelling and Experimental Testing of Thick CFRP Composites Subjected to Low Velocity Impacts. In: Procedia Structural Integrity, v. 24 ( 2019).
- (2021): On the mitigation of the RAPID algorithm uneven sensing network issue employing averaging and Gaussian blur filtering techniques. In: Composite Structures, v. 278 (December 2021).
- (2020): Fatigue damage diagnosis and prognosis of an aeronautical structure based on surrogate modelling and particle filter. In: Structural Health Monitoring, v. 20, n. 5 (December 2020).
- (2021): Damage diagnosis and prognosis in composite double cantilever beam coupons by particle filtering and surrogate modelling. In: Structural Health Monitoring, v. 20, n. 3 (January 2021).
- (2021): Comparison of strain pre-extrapolation techniques for shape and strain sensing by iFEM of a composite plate subjected to compression buckling. In: Composite Structures, v. 262 (April 2021).
- (2020): Numerical and experimental verification of an inverse‐direct approach for load and strain monitoring in aeronautical structures. In: Structural Control and Health Monitoring, v. 28, n. 2 (October 2020).
- (2018): A Bayesian framework for fatigue life prediction of composite laminates under co-existing matrix cracks and delamination. In: Composite Structures, v. 187 (March 2018).
- (2020): Fatigue crack growth identification in bonded joints by using carbon nanotube doped adhesive films. In: Smart Materials and Structures, v. 29, n. 3 (27 January 2020).
- (2019): Particle filtering‐based adaptive training of neural networks for real‐time structural damage diagnosis and prognosis. In: Structural Control and Health Monitoring, v. 26, n. 12 (12 November 2019).
- (2017): A particle filter-based model selection algorithm for fatigue damage identification on aeronautical structures. In: Structural Control and Health Monitoring, v. 24, n. 11 (November 2017).
- (2017): Optimization of an artificial neural network for fatigue damage identification using analysis of variance. In: Structural Control and Health Monitoring, v. 24, n. 9 (September 2017).
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