Human Behaviour in Fire
Människors beteende vid brand

VBRN10, 8.0 credits, A (Second Cycle)

Valid for: 2025/26
Faculty: Faculty of Engineering LTH
Decided by: PLED BI/RH
Date of Decision: 2025-04-03
Effective: 2025-05-05

General Information

Main field: Fire Safety Technology Depth of study relative to the degree requirements: Second cycle, in-depth level of the course cannot be classified
Mandatory for: MFST1
Language of instruction: The course will be given in English

Aim

The course provides students with insight into theories of human behaviour in fires and evacuation behaviour, and computer modelling of evacuation.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

• be able to explain RSET-models that are commonly used in guidelines and regulations.
• be able to describe different theories of human behaviour in fire in building and wildfire scenarios.
• be able to state typical walking speeds for evacuation and explain how movement of people is influenced by demographic factors (e.g. age and mobility).
• be able to understand and apply the main evacuation calculations methods.
• be able to describe how people are affected by combustion products.
• be able to explain the main assumptions behind egress models (network, grid and continuous models).

Competences and skills
For a passing grade the student must

• apply RSET-models to estimate the required safe escape time.
• analyse a fire accident and relate the behaviour of occupants to theories of human behaviour in fire.
• apply egress models to simulate movement of people during evacuation and critically analyse results.
• select appropriate occupant behavioural scenarios for fire safety engineering design.
• communicate theories of human behaviour in fire to laymen and experts.
• communicate results from simulations with egress models to laymen and experts (oral, written and graphic representation).
• independently seek information (articles, reports, manuals, etc) about human behaviour in fire.

Judgement and approach
For a passing grade the student must

• adequately consider relevant scientific and ethical aspects of experiments with human participants (evacuation experiments).
• adequately consider relevant ethical and scientific aspects relating to analysis of evacuation with egress models.

Contents

The course provides students with insight into theories of human behaviour in fire and evacuation behaviour, and computer modelling of evacuation. The course is imparted through lectures, compulsory seminars, and compulsory computer laboratory sessions. During the course the students also work on group assignments, with oral presentations to fellow students and teachers. An exam will be held at the end of the course.

Examination details

Grading scale: TH - (U, 3, 4, 5) - (Fail, Three, Four, Five)
Assessment:

The final certificate is based on an examination, attendance at compulsory activities (including seminars and laboratories), assignments, reports, presentations, and laboratory reports.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Modules
Code: 0111. Name: Human Behaviour in Fire.
Credits: 8.0. Grading scale: TH - (U, 3, 4, 5). Assessment: Approved written examination. In case of special circumstances, the course coordinator can consider an oral examination. Passing grade on assignments, seminars and laboratories. The module includes: Written examination, reports/presentations, seminars and laboratory reports.

Admission

The number of participants is limited to: No
Selection: Completed university credits within the program. Within programs where the course is given as a compulsory course students are guaranteed admission. Thereafter priority is given to students enrolled on programmes that include the course in their curriculum."

Reading list

• The course literature consists of a selection of journal papers and relevant chapters from engineering books, such as the latest version of the SFPE Handbook. The literature is tailored to the content of each lecture and is provided on the corresponding CANVAS page.

Contact

Course coordinator: Enrico Ronchi, enrico.ronchi@brand.lth.se
Examinator: Enrico Ronchi, enrico.ronchi@brand.lth.se
Examinator: Silvia Arias, silvia.arias@brand.lth.se
Course administrator: Linnéa Ekman, linnea.ekman@ebd.lth.se

Further information

Active participation in group work is required. Each group member must be able to report and be responsible for the content individually. If a group member does not fulfill the requirements for active participation, or disregards his/her commitments, she/he can be reassigned by the examiner to another group or get a fail result.

In the course, some assignments require you to present information in the form of a report, a presentation, or a video. Since feedback will be provided on your work, the use of Generative Artificial Intelligence (GAI) is not allowed for the retrieval of information. It will be considered cheating if any parts of your work are produced by GAI and you present them as you own. This is aligned with Lund University’s guidelines - see point 1 here https://www.campusonline.lu.se/en/learning-strategies/four-things-keep-mind-asking-ai-help?q=digital-tools/generative-ai-tools

The use of Large Language Models is allowed, although not encouraged, for translations, fixing grammar, and general improvements of your own text. No feedback will be provided on the work produced by GAI. Images can be produced using GAI, but not videos. If you choose to use GAI for any purpose in your work you must specify the precise application you did of it.