Course Syllabus for

Critical Infrastructure Resilience
Kritiska Infrastrukturers resiliens

VRSN45F, 7.5 credits

Valid from: Autumn 2019
Decided by: Senior lecturer Gudbjörg Erlingsdottir
Date of establishment: 2019-05-14

General Information

Division: Division of Risk Management and Societal Safety
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: VRSN45
Teaching language: English


- prepare the students so that they are able to work with critical infrastructures topics within for example private business, government agencies or nongovernmental organization. - provide a foundation for students interested in further studies and research on critical infrastructure topics.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must

Course Contents

The course introduces and discusses important aspects for management of critical infrastructure, such as power systems, water supply systems, telecommunication systems and transport systems. The course should be seen as an introduction to the subject of critical infrastructure and vital societal functions. Important aspects covered are the form and function of critical infrastructures and their role in society as well as key methods and concepts for analysis and management of critical infrastructures. Methods covered in the course include: network theory as an analysis tool for complex infrastructure systems, risk management, asset management, infrastructure interdependency modelling, and impact assessments of large-scale infrastructure disruptions. Concepts that are important for the student to understand and reflect on during the course are for example: risk, reliability, uncertainty, resilience, complexity and continuity. An important part of the learning process is that students will apply concepts and methods to realistic representations of infrastructures as well as to connect to and reflect on the different concepts and methods. Throughout the course, there is a progression from abstract to more realistic representations of infrastructures, where the student will reflect on the different strengths and weaknesses of different models, methods and concepts. The course is hence divided into a number of parts that guide the student through important concepts and methods. To each central part, computer labs are used to enable students to apply the various methods introduced in the course. Teacher-led seminars for each central part of the course are also given, where students can actively discuss and reflect on the theme and the literature as well as compare approaches for problem solving. Examination of the course takes place through essays that deal with the different central parts of the course as well as a final project work in which either one or more central parts of the course are explored in more depth or a synthesis of all parts of the course is presented (i.e. each central part covered becomes input values for the final project work). The project is discussed in a teacher-led seminar so that the students also can acquire the ability to verbally present and discuss their approaches and preliminary results, as well as provide constructive feedback.

Course Literature

Instruction Details

Types of instruction: Lectures, seminars, laboratory exercises

Examination Details

Examination formats: Written report, seminars given by participants
Grading scale: Failed, pass

Admission Details

Admission requirements: - FMAA01 Calculus in One Variable OR FMAA05 Calculus in One Variable. - FMSF50 Mathematical Statistics, Basic Course OR FMSF20 Mathematical Statistics, Basic Course OR EXTA60 Statistics OR FMSF30 Mathematical Statistics. - A minimum of 150 credits from a five-year engineering programme or from the Fire Safety Engineering Programme at LTH or equivalent educational background and academic credits for incoming exchange students. Basic knowledge within University matemathics such as Calculus in One Dimension e.g. FMAA05 and basic knowledge in statistics e.g. FMFS20, FMFS30, FMSF50, EXTA60.
Assumed prior knowledge: Basic knowledge of programming.

Course Occasion Information

Contact and Other Information

Course coordinator: Jonas Johansson <>

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