Summer Course on Structural Health Monitoring 2025 (3rd Edition)

5 ECTS | July 14-18, 2025, in person (30h) | 15h remotely | MSc and PhD Students

We are happy to announce the 3rd Edition of the Summer Course on Structural Health Monitoring. The in-person sessions will take place in Lisbon from July 14 to 18, 2025. A limited number of vacancies is available, so pre-enroll to express your interest. You can still find one collection date: Januart 15, 2025.

This blended intensive summer course, funded by the Erasmus+ Program, focuses on Structural Health Monitoring (SHM), with 15 hours of remote sessions and 30 hours of in-person sessions. The main goal of this summer course is to introduce the concept of SHM applied to bridges and special civil structures to MSc and PhD students from several European institutions.

The SHM is posed in the context of a statistical pattern recognition paradigm, rooted in the artificial intelligence field, where machine learning algorithms are essential to perform damage identification, by learning (or modeling) the structural behavior from the experience (past data), following the same principle of the human brain. In order to balance the general concept and the applicability of SHM, this course has been designed to allow students to gain a basic knowledge of SHM with hands-on experiences to demonstrate how SHM can be used for assessing the condition of structural systems, along with the lectures to give some insight into the theory and application examples.

Keywords

Structural Health Monitoring, Bridges, Wind Turbines, Machine Learning, Finite Element Modeling, Digital Twins, Risk, Value of Information, Climate Change

Most relevant upgrades since last edition

For the 3rd edition, we are adding two new instructors (Michael Havbro Faber and Luís Oliveira Santos) and more SHM in Action!

Funding source

Erasmus+ Program through Blended Intensive Program (BIP), Student Mobility of Education (SME), and Staff Mobility for Teaching (SMT). The BIP covers expenses related to the course organization. SMT and SME cover expenses related to traveling and housing of students in Lisbon.

Which are the host and partners institutions?

Lusófona University is host and responsible for the organization and funding of the course through BIP. Each partner institution is responsible to find students and staff members through SME and SMT (this funding must be coordinated with the international office of each partner institution).

Who can participate?

MSc and PhD students from countries participating in the Erasmus+ Program who are interested in speeding up the learning process of SHM posed in the context of a statistical pattern recognition paradigm.

Enrollment

A limited number of vacancies is available. This registration form serves as a pre-enrollment to express your interest and does not guarantee final admission until all required steps are completed. We will notify you when official enrollment becomes available in one of the two collection dates: (i) December 15, 2024; and (ii) January 15, 2025. 

Course material

PowerPoints, books, and research articles: all course materials are available through a website on the e-learning platform, Moodle. Students are encoureged to bring their own laptops.

Student evaluation

The evaluation includes three main components: individual homework, a group project report, and a group presentation. Small groups of five or six students are formed to design an SHM system or a damage identification strategy for laboratory or real-world structures. Each group is assigned a supervisor for guidance.  Each group's outcome must be documented in a report and defended in an oral examination, conducted publicly in the form of a seminar. Students are graded, and the grades will be awarded according to the university’s Education and Examination Regulations.

Remote lectures

1. Introduction to SHM
2. Statistical pattern recognition paradigm
3. Data-based modeling
4. Hybrid-based modeling
5. SHM in Action: hands-on experience
6. Probabilistic digital twins in SHM
7. Trending SHM topics: The role of transfer learning for SHM and the role of SHM for bridge adaptation to climate change
8. Limitations, grand challenges, and trends

In-person lectures

1. Value of information
2. Vision-based monitoring
3. Probabilistic FE modeling
4. Risk and resilience
5. Field instrumentation
6. SHM in Action (lab and field activities)

Instructors

• Eloi Figueiredo, Lusófona University, Portugal
• Ionut Moldovan, Lusófona University, Portugal
• Michael Havbro Faber, Lusófona University, Portugal
• Luís Oliveira Santos, National Laboratory of Civil Engineering, Portugal
• Marek Salamak, Silesian University of Technology, Poland
• Marcin Jasiński, Silesian University of Technology, Poland
• Maria Pina Limongelli, Politecnico di Milano, Italy
• Mihai Nedelcu, Technical University of Cluj-Napoca, Romania
• Pier Francesco Giordano, Politecnico di Milano, Italy
• Roland Kromanis, University of Twente, Netherlands

Invited Instructors

• João Canto, Lusófona University, Portugal
• Luca Pèla, Barcelona Tech - UPC, Spain
• Nuno Peres, Lusófona University, Portugal
• Nuno Santos, Lusófona University, Portugal
• Semih Gonen, Barcelona Tech - UPC, Spain

Institutional Support

• DEWESoft - measurement innovation

General Schedule

In-Person Schedule (July 14-18, 2025)

Testimony from the 1st edition in 2023