Funding line:

LG.0160/2019 et seq. – Fiscal years 2020-2021-2022

Project objectives:

The recent increasing occurrence of disasters and extraordinary events, such as floods and earthquakes, together with the aging and deterioration of structures and infrastructure makes it now more necessary than ever to consciously and proactively manage them. Indeed, it is well known that most structures but also road infrastructure were built before the introduction of seismic design guidelines in the 1970s (or later), so these structures are vulnerable not only to seismic action but also to the effects of aging and deterioration. An emerging area of research that focuses on addressing this challenge is one that exploits the creation of a “digital twin” for structures. A digital twin is a virtual representation of an existing infrastructure. Because it is a digital representation this can and should be updated as new data is collected on the actual facility. This virtual model can be used to provide information and feedback of the real structure. Also with the help of artificial intelligence algorithms it is possible to hypothesize “what-if” scenarios; to assess the actual state of the structures, possible risks schedule their maintenance as well as assess predictive scenarios. A digital twin can be used for visualization, monitoring, evaluation, simulation, prediction, optimization, management, etc. Thus, the ultimate goal of the research project is to achieve greater resilience of structures through preventive measures, effective resource management and prioritization, focusing on seismic risk and aging and deterioration of structures.

Role of ASDEA: Internal project

Activities:

• Analysis and definition of technical specifications
• Design and Development of finite element framework – digital twin
• Analysis of Big Data and Design of predictive algorithms
• Development of BIM models and predictive algorithms
• Testing and performance verification

Related Publications:

Alessia Amelio, Roberto Boccagna, Maurizio Bottini, Guido Camata, Nicola Germano, et al.. A disruptive strategy for structural health monitoring with STKO. Accepted to the 2st Eurasian Conference on OpenSees, OpenSees Days 2022 Eurasia, Jul 2022, Turin, Italy. ⟨hal-03793253⟩
L. Aceto, Alessia Amelio, Roberto Boccagna, Maurizio Bottini, Guido Camata, et al.. A Self-Consistent Artificial Intelligence-Based Strategy for Structural Health Monitoring. Fifth International Conference on Railway Technology: Research, Development and Maintenance (RAILWAYS 2022), Aug 2022, Montpellier, France. ⟨hal-03784295⟩
Alessia Amelio, Roberto Boccagna, Maurizio Bottini, Guido Camata, Nicola Germano, et al.. Digital Twin: a Hybrid Approach for Structural Health Monitoring. Accepted to the Fifth International Conference on Railway Technology: Research, Development and Maintenance (RAILWAYS), Aug 2022, Montpellier, France. ⟨hal-03773062⟩