Uncertainty in Smoke Transport Models

Research output: Book/ReportReport


Data from full scale experiments are collected and organized in a database. A statistical method is developed to evaluate the uncertainty in predictions of smoke transport models. The method is based on a regression analysis of measured and predicted data. The computer program CFAST is evaluated to exemplify the statistical method. The uncertainty is quantified with a regression coefficient and the residual variance When the model uncertainty
is quantified it is possible to adjust the model predictions for the model error. The uncertainty in CFAST’s predictions of smoke gas temperature and position of the interface is investigated for a number of different scenarios.


  • Johan Lundin
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Building Technologies
  • Other Civil Engineering


  • full scale fire experiments, model error, random error, systematic error, bias, knowledge uncertainty, smoke transport models, model prediction, design, simulation tools., CFAST, model uncertainty, Risk analysis
Original languageEnglish
PublisherDepartment of Fire Safety Engineering and Systems Safety, Lund University
Number of pages42
Publication statusPublished - 1997
Publication categoryResearch

Publication series

ISSN (Print)1102-8246

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