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Uncertainty in Smoke Transport Models

Lundin, Johan LU (1997) In LUTVDG/TVBB--3086--SE 3086.
Abstract
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.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Book/Report
publication status
published
subject
keywords
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
in
LUTVDG/TVBB--3086--SE
volume
3086
pages
42 pages
publisher
Department of Fire Safety Engineering and Systems Safety, Lund University
ISSN
1102-8246
language
English
LU publication?
yes
id
20bc32c3-c5dc-4611-804d-a19c2ce5e462 (old id 605441)
date added to LUP
2008-11-10 15:50:52
date last changed
2016-04-16 03:26:44
@techreport{20bc32c3-c5dc-4611-804d-a19c2ce5e462,
  abstract     = {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<br/><br>
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.},
  author       = {Lundin, Johan},
  institution  = {Department of Fire Safety Engineering and Systems Safety, Lund University},
  issn         = {1102-8246},
  keyword      = {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},
  language     = {eng},
  pages        = {42},
  series       = {LUTVDG/TVBB--3086--SE},
  title        = {Uncertainty in Smoke Transport Models},
  volume       = {3086},
  year         = {1997},
}