5 ECTS | June 26-30, 2023, in person (30h) | 15h remotely | MSc and PhD Students
We are happy to announce that this course has been confirmed, with 31 students from eight European universities and eight countries!
The main goal of this summer course is to introduce the concept of structural health monitoring (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, Machine Learning, Finite Element Modeling, Digital Twins, Climate Change
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?
Each institution can indicate up to four MSc and PhD students interested to speed up the learning process on SHM posed in the context of a statistical pattern recognition paradigm. Additionally, each institution can propose one senior researcher for lecturing (≥4h).
Course material
PowerPoints, books, and research articles. All course material is available from a website in an e-learning platform (Moodle). All students should bring their own laptops.
Activity | Teaching mode | Description | Contact hours | Date and Time (WEST) |
---|---|---|---|---|
1 | Remote | Welcome session | 1 | May 9, 2023 (17:00-18:00) |
2 | Remote | Introduction to structural health monitoring | 9 | May 16, 18, 23, 25, 30 and June 1, 2023 (17:00-18:30) |
3 | Remote | Project’s presentation | 1 | June 6, 2023 (17:00-18:00) |
4 | In-person | Lecturing and laboratory activities | 30 | June 26-30, 2023 |
5 | Remote | Student’s presentation of final project | 3 | July 19 and 20, 2023 (8:00-9:30) |
6 | Remote | Closing session | 1 | July 21, 2023 (8:00-9:00) |
Instructors:
Teaching mode | Description | Instructor | Contact hours |
---|---|---|---|
Remote | Introduction to structural health monitoring | Eloi Figueiredo and Ionut Moldovan | 15 |
In-person | Value of Information | Maria Pina Limongelli and Pier Francesco Giordano | 4 |
In-person | Bridge loading testing | Grzegorz Poprawa | 4 |
In-person | Model updating | Mihai Nedelcu | 4 |
In-person | Computer vision-based measurement | Roland Kromanis | 4 |
In-person | Laboratory | – | 3 |
In-person | Supervision | – | 11 |
Notes:
Gestão de conteúdos por Eloi Figueiredo © 2022 COFAC.