A spectrum of physics-informed Gaussian processes for regression in engineering

EJ Cross, TJ Rogers, DJ Pitchforth… - Data-Centric …, 2024 - cambridge.org
Despite the growing availability of sensing and data in general, we remain unable to fully
characterize many in-service engineering systems and structures from a purely data-driven …

[HTML][HTML] On the use of the inverse finite element method to enhance knowledge sharing in population-based structural health monitoring

G Delo, R Roy, K Worden, C Surace - Computers & Structures, 2025 - Elsevier
Abstract Efficient Structural Health Monitoring (SHM) is critical for ensuring safety and
improving the operation and maintenance of aerospace structures. This study focusses on …

Quantifying the value of positive transfer: An experimental case study

AJ Hughes, G Delo, J Poole, N Dervilis… - arxiv preprint arxiv …, 2024 - arxiv.org
In traditional approaches to structural health monitoring, challenges often arise associated
with the availability of labelled data. Population-based structural health monitoring seeks to …

Regional-scale bridge health monitoring: survey of current methods and roadmap for future opportunities under changing climate

S Quqa, O Lasri, G Delo, PF Giordano… - Structural Health …, 2025 - journals.sagepub.com
Climate-related extreme events are becoming increasingly frequent, posing significant
threats to bridges, which are critical components of transportation infrastructure. This paper …

On the influence of structural attributes for transferring knowledge in population-based structural health monitoring

G Delo, DS Brennan, C Surace, K Worden - IMAC, A Conference and …, 2024 - Springer
The recently proposed theory of Population-Based Structural Health Monitoring (PBSHM)
aims at improving diagnostic inferences, by sharing damage-state knowledge across a …

On the investigation of Statistical Alignment performance for enhancing damage identification across a population of heterogeneous shear structures

S Badariotti - 2024 - webthesis.biblio.polito.it
The development of machine learning algorithms for Structural Health Monitoring (SHM) is
rapidly advancing. However, their application for real-world structures finds a high number of …