PROGRAMME STRUCTURE

 

The NORISK will provide a unique combination of theoretical work with cross-disciplinary, supported on risk assessment and infrastructure management, based on the cutting-edge knowledge at European Universities, with an effective cooperation between Civil, Industrial and Systems engineers on a common educational project, during which there is specially devised attention and time for project-based learning.

The NORISK programme structure comprises two semesters: in the 1st semester, from October to March, the coursework takes place, being composed of five sequential units (NR1 to NR5) and one project-based learning unit (NR6), while in the 2nd semester, from March to July, the MSc dissertation is developed by the student.

The programme provides two opportunities of interaction between all participant students, the Integration Week (late November) and the annual NORISK Workshop (late May). Those events take place in the Consortium members that are not hosting the coursework on that specific academic year:
 

  • Nearby the end of November, the Integration Week, lasting five days, will allow students of: i) having social interaction; ii) developing additional softs skills; and iii) gaining additional knowledge. The participation of students in the Integration Week will be supported by the Consortium (travel, accommodation and meals). The programme includes:
    • Day-1: check-in, welcome reception by the Rector representative and visiting the facilities of the Integration Week hosting Institution, with particularly emphasis in the labs;
    • Day-2: seminars on soft skills to be provided by experts to be invited for this specific task (morning) and teambuilding activities (afternoon);
    • Day-3: Technical in field visit to a case-study (morning) and cultural guided visit to downtown (afternoon);
    • Day-4: invited lectures provided by invited Associate Partners to address relevant topics not included in the curriculum (morning) and teambuilding activities (afternoon);
    • Day-5: check-out and closing communication (morning);
  • During the 2nd semester, at late May, the annual NORISK Workshop will take place, lasting 3 days, aiming at bringing all students once again to participate in i) a series of keynote lectures; ii) a pitch and discussion of the ongoing MSc dissertations and iii) a job fair. The technical programme of NORISK Workshop includes:
    • Day-1: check-in, welcome reception by the Rector representative and visiting to the facilities of the NORISK Workshop hosting Institution, with particularly emphasis in the labs;
    • Day-2: pitch session and discussion of the ongoing MSc dissertations (all day);
    • Day-3: invited lectures provided by invited Associate Partners to address relevant topics, not included in the curriculum and job fair event (morning) and, NORISK alumni testimonials, job fair event (continuation), and closing communication (afternoon).
Academic Year Coursework MSc dissertation Integration week NORISK Workshop
2024/2025 UMINHO, LRU ALL UPC UNIPD
2025/2026 UMINHO, UNIPD ALL LRU UPC
2026/2027 LRU, UNIPD ALL UPC UMINHO
The NORISK is a one year, full-time very intensive programme. The study programme is composed of seven course units (modules): i) five sequential units (5 ECTS each) and ii) one project-based learning unit along the 1st semester (October to March) (5 ECTS – 45 hours of lectures and 95 hours of independent student work); and, iii) one dissertation during the 2nd semester (March to July) (30 ECTS – 15 tutorial hours and 825 hours of independent student work). The curriculum is the same, no matter the student mobility track.
Introduction to risk assessment and management of infrastructures
Coordinator: José Campos e Matos

Description: Introduce the main aspects concerning the risk management of infrastructures, with an emphasis on those considered as critical. Moreover, important concepts, such as those of redundancy, robustness, resilience, adaptability and mitigation will be respectively introduced. In order to evaluate infrastructure global performance, sustainability assessment concepts and tools will be given. In addition, basic modelling skills and tools, such as multi-physics analysis, scientific programming, geographic information systems, among others, will be provided.

Main learning objectives:

  • to identify the main components of risk assessment for infrastructure management;
  • to identify the performance level and sustainability of infrastructures, based on quality control tools and advanced modelling;
  • to list the main aspects of redundancy, robustness, resilience, adaptation and mitigation;
  • to model a multi-physics problem;
  • to apply digital tools and use geographic information systems, within a context of risk assessment and infrastructure management;
  • to integrate the main concepts and tools for the risk assessment and management of infrastructures into a real case study.

Reliability and risk analysis of infrastructures

Coordinator: Mariano Zanini

Description: All aspects related to reliability and risk analysis for infrastructural systems will be covered by the syllabus. In detail, students will be introduced in the reliability analysis theory, providing them key concepts related to the definition of limit states, uncertainty sources, types of limit state functions, reliability indexes and target values, current methods for reliability calculation, and time-variant approaches to component and system reliability. Stochastic models will be introduced to complete the overview of methods and models to be used when dealing with reliability assessment. Trainees will be pushed to critically assess key factors involved in the quantification of different types of risks. The last part of the unit will be oriented at providing some practical applications of risk assessments to infrastructure component to different hazards like traffic overloads, earthquakes, floods and landslides.

Main learning objectives:

  • to execute a reliability analysis, taking into account the uncertainty sources and the suitable probabilistic load and resistance models;
  • to develop time-dependent reliability assessment, capturing time-variant demand and capacity factors;
  • to formulate loss models for the quantification of direct and indirect consequences, linked to the occurrence of a natural/man-made events;
  • to assess risk of infrastructural systems, combining all concepts and tools related to the topic;
  • to outline complex scenarios, like multi-hazard or cascading events, that should be addressed within a risk-based approach;
  • to identify key factors involved in the assessment of traffic- and geohazards risk for infrastructure components.
Infrastructures management and decision supporting tools

Coordinator: Paula Varandas Ferreira

Description: It covers all aspects related to infrastructure management and multi-criteria decision-making tools. It will be given relevant topics, such as those related to value of information, performance predictive modelling, intervention evaluation and optimization, and data or dataset analysis tools. Extreme events as well as climate adaptation topics will be also addressed, being respectively provided concepts and tools for the efficient use of resilience models. Rich with case studies, this course will enable students to develop a long-term, self-sustained, assessment capacity and more effective risk-management strategy.

Main learning objectives:

  • to participate effectively in infrastructure management decisions, including the levels of intervention on the management procedure;
  • to use analytical and statistical tools for the correct treatment and validation of data and datasets;
  • to develop a multi criteria decision making process, considering different costs, and the future performance conditions;
  • to implement the value of information theory for the correct management of civil infrastructures;
  • to implement resilience models, so as to address extreme events on the management of infrastructures;
  • to identify the main potential effects of climate change and the climate adaptation strategies for infrastructure assets.
Monitoring and digitalization of infrastructures

Coordinator: José Turmo

Description: Relevant topics related to sensoring equipment, non-destructive testing techniques, together with visual inspection, will be covered. All steps of data collection, processing, cleansing, such as data mining, machine learning, deep learning and artificial intelligence will be considered within a data analysis framework. Advantages and disadvantages of frequency and time domain modal analysis, under environmental vibrations, will be discussed. Basic principles and benefits of using visual programming will be considered, aiming at developing practical tools for improving the management of infrastructures through model updating. Finally, this course will enable students to develop a digital twin of an infrastructure supported on different sources of information and geospatial technologies (BIM, GIS, among others).

Main learning objectives:

  • to implement Structural Health Monitoring plans and long-term monitoring of infrastructures;
  • to identify the stateof-the-art methods for infrastructure assessment, visual inspection, non-destructive testing, sensoring and monitoring systems;
  • to choose the most proper method for assessing infrastructure condition affected by different phenomena;
  • to apply data collection methods and big data management within the monitoring and digitalization procedures;
  • to apply existing operational modal analysis, system identification and model updating tools;
  • to use a BIM and GIS digital twin of an infrastructure.
Assessment and intervention techniques on infrastructures

Coordinator: Emilio Bastidas-Arteaga

Description: Relevant topics related to durability of most used (reinforced and pre-stressed concrete, steel, masonry, among others) and non-conventional construction materials will be addressed. Deterministic, probabilistic, artificial intelligence models will be considered for lifetime assessment, under realistic exposure conditions, including intervention actions. These models will be used as a basis for estimating the effectiveness, costs and environmental footprint of repair/strengthening techniques. Legal frameworks for carrying out assessment and intervention planning will be presented. Advanced construction materials for repair/strengthening will be also included. Case studies and analysis of practical examples will serve to illustrate and discuss the advantages and disadvantages of different intervention materials and techniques.

Main learning objectives:

  • to assess the infrastructure during their life cycle, and their service life;
  • to quantify the effects of degradations and interventions on its service capacity and reliability, using deterministic, probabilistic, and artificial intelligence approaches;
  • to diagnose the potential risks associated with the immediate natural environment of a structure;
  • to select the most suitable assessment and intervention measures, within an existing portfolio, for a specific case;
  • to use the normative knowledges respected during intervention procedures;
  • to estimate the effects, environmental impact and costs, when considering assessment/intervention techniques.
Integrated project in risk analysis and management of infrastructures

Coordinator: Daniel Vitorino de Castro Oliveira

Description: The unit includes two comprehensive case study projects, field visits and seminars. The two case study projects are: i) the development of a project which includes risk analysis, design and reliability of a civil/critical infrastructure; and ii) the analysis, design of interventions in an infrastructure, as well as its management in a complex network of interdependent infrastructures. The second project will be developed among the students of the two involved coursework hosting Institutions, while the first one will be developed only with students of the local hosting Institution. Skills and competences will be ensured during the curricular unit period, due to the adopted teaching methodologies. It is based in a specific learning model, where the development of an integrated project with risk assessment and management of infrastructures is pursued. This learning model allows students to develop their capacity to interrelate knowledge and seek for practical solutions applied in real case studies. Knowledge acquired within other curricular units will be also used here for the project development.

Main learning objectives:

  • to perform risk assessment and management of infrastructures from case studies;
  • to apply risk-based management frameworks;
  • to implement tools for identifying the most suitable intervention plan on existing infrastructures, based on a decision making process;
  • to develop reports from field trips, related to the provided case studies, as well as of the given seminars on topics not covered by other units.
Dissertation

Coordinator: José Campos e Matos

Description: This purpose of this unit is that students develop the search for information on concepts, models and instruments relative to the planning of the research work, in order to develop and present an original dissertation work. The research is based on the implementation of the proposed tasks, supporting the development of the work, leading to the written document and its public discussion. In this context, it is intended that students develop their ability to integrate knowledge, handle complex questions, as well as their ability to understand and solve problems in new situations and multidisciplinary contexts, developing solutions and reflections on the subject under study

Main learning objectives:

  • to properly use technics and concepts related to the dissertation work;
  • to develop advanced theoretical and practical research;
  • to establish a suitable planification of the corresponding dissertation work;
  • to interact with the supervision team and associated partners, when needed;
  • to develop a written document of the work carried out;
  • to establish a public presentation and active discussion of the developed work.