Artificial Intelligence and Heterogeneous Data Fusion Methods for SHM of Smart Masonry Structures
Deadline: 20/07/2026
Scientific-Disciplinary Group
08/CEAR-07 - Structural Analysis And Design
Description
The researcher will contribute to the FIS 2021 project SMS-SAFEST through the development of advanced methodologies for the structural health monitoring of smart masonry structures subjected to static and seismic actions. Activities will include the integration and fusion of data collected from smart bricks and smart mortars using machine learning and artificial intelligence techniques for damage identification and classification, detection of failure mechanisms and attained limit states, as well as the estimation of residual load-bearing capacity. The researcher will also contribute to the numerical modelling of full-scale masonry structures through nonlinear static and incremental dynamic analyses aimed at validating the Structural Health Monitoring strategies developed within the project. Finally, activities will include support for the design,construction, and experimental validation of smart masonry prototypes and innovative systems for damage detection and localization.
Job posting website
Funding body
Università degli studi di Perugia
How to apply
View the original posting on the MUR website: Go to MUR website