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Uncertainty propagation in FE modelling of a fire resistance test using fractional factorial design based model reduction and deterministic sampling
RISE - Research Institutes of Sweden, Safety and Transport, Safety.
RISE - Research Institutes of Sweden, Safety and Transport, Safety.
RISE - Research Institutes of Sweden, Safety and Transport, Safety.
2017 (English)In: Fire safety journal, ISSN 0379-7112, E-ISSN 1873-7226Article in journal (Refereed) In press
Abstract [en]

In this paper, fractional factorial design (FFD) and deterministic sampling (DS) are applied to a finite element (FE) model of a fire resistance test of a loaded steel beam, to investigate how uncertainties are propagated through the FE model. The sought quantity was the time when the deflection of the beam exceeded 225. mm. The FFD method was used as a model reduction technique which reduced the number of uncertain parameters from 5 to 3. The DS method was compared to a reference Monte Carlo (MC) method of 1000 simulations from all 5 uncertain parameters, which was the minimum number of simulations in order for the statistical moments to converge. The combined FFD and DS method successfully computed the propagation of the mean and standard deviation in the model, compared to the MC method. Given the uncertainties in the FE model, the fractional factorial design reduced the number of simulations required in the DS method by 82%. The combined method of FFD and DS reduced the number of required simulations by 96% compared to the MC method. The DS method did not capture the tails of the probability distribution and is therefore not a suitable candidate for probabilistic evaluation of the time of failure at the edges of the domain of possible failure times. Future research could very well be on improving the tails in DS. However, the DS method provides a conservative 95% coverage interval of 6. min for the time to failure of the steel beam.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Deterministic sampling, Factorial design, Fire resistance, Modelling, Monte Carlo, Statistics, Models, Monte Carlo methods, Probability distributions, Sampling, Steel beams and girders, Uncertainty analysis, Fire resistance test, Fractional factorial designs, Mean and standard deviations, Model reduction techniques, Probabilistic evaluation, Uncertainty propagation, Finite element method
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-29348DOI: 10.1016/j.firesaf.2017.03.032Scopus ID: 2-s2.0-85017091436OAI: oai:DiVA.org:ri-29348DiVA: diva2:1093850
Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2017-05-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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