Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire
Concrete columns are critical for the stability of structures in case of fire. In order to allow for a true Perfor-mance Based Design, the design should be based on considerations of risk and reliability. Consequently, the probability density function (PDF) which describes the load-bearing capacity...
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sg-ntu-dr.10356-886372019-12-06T17:07:47Z Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire Van Coile, Ruben Balomenos, Georgios P. Pandey, Mahesh D. Caspeele, Robby Criel, Pieterjan Wang, Lijie Alfred, Strauss School of Civil and Environmental Engineering 2016 International Symposium of the International Association for Life-Cycle Civil Engineering Concrete Column Fire Concrete columns are critical for the stability of structures in case of fire. In order to allow for a true Perfor-mance Based Design, the design should be based on considerations of risk and reliability. Consequently, the probability density function (PDF) which describes the load-bearing capacity of concrete columns during fire exposure has to be assessed. As second order effects can be very significant for columns, traditional probabil-istic methods to determine the PDF become very computationally expensive. More precisely, for most current numerical calculation tools (e.g. Finite Element), the computational requirements are so high that traditional Monte Carlo simulations become infeasible for any practical application. In order to tackle this, a computa-tionally very efficient method is presented and applied in this paper. The method combines the Maximum En-tropy Principle together with the Multiplicative Dimensional Reduction Method, and Gaussian Interpolation, resulting in an estimation of the full PDF requiring only a very limited number of numerical calculations. Alt-hough the result is necessarily an approximation, it gives very good assessment of the PDF and it is a signifi-cant step forward towards true risk- and reliability-based structural fire safety. Accepted version 2018-04-24T08:10:37Z 2019-12-06T17:07:47Z 2018-04-24T08:10:37Z 2019-12-06T17:07:47Z 2016-10-01 2016 Conference Paper Van Coile, R., Balomenos, G. P., Pandey, M. D., Caspeele, R., Criel, P., Wang, L., et al. (2016). Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire, 2016 International Symposium of the International Association for Life-Cycle Civil Engineering, Delft, The Netherlands, 16-19 October 2016. https://hdl.handle.net/10356/88637 http://hdl.handle.net/10220/44709 https://biblio.ugent.be/publication/8130731 205874 en © 2016 IALCCE. This is the author created version of a work that has been peer reviewed and accepted for presentation in 2016 International Symposium of the International Association for Life-Cycle Civil Engineering, by IALCCE. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [https://biblio.ugent.be/publication/8130731]. 8 p. application/pdf |
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Concrete Column Fire Van Coile, Ruben Balomenos, Georgios P. Pandey, Mahesh D. Caspeele, Robby Criel, Pieterjan Wang, Lijie Alfred, Strauss Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
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Concrete columns are critical for the stability of structures in case of fire. In order to allow for a true Perfor-mance Based Design, the design should be based on considerations of risk and reliability. Consequently, the probability density function (PDF) which describes the load-bearing capacity of concrete columns during fire exposure has to be assessed. As second order effects can be very significant for columns, traditional probabil-istic methods to determine the PDF become very computationally expensive. More precisely, for most current numerical calculation tools (e.g. Finite Element), the computational requirements are so high that traditional Monte Carlo simulations become infeasible for any practical application. In order to tackle this, a computa-tionally very efficient method is presented and applied in this paper. The method combines the Maximum En-tropy Principle together with the Multiplicative Dimensional Reduction Method, and Gaussian Interpolation, resulting in an estimation of the full PDF requiring only a very limited number of numerical calculations. Alt-hough the result is necessarily an approximation, it gives very good assessment of the PDF and it is a signifi-cant step forward towards true risk- and reliability-based structural fire safety. |
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School of Civil and Environmental Engineering |
author_facet |
School of Civil and Environmental Engineering Van Coile, Ruben Balomenos, Georgios P. Pandey, Mahesh D. Caspeele, Robby Criel, Pieterjan Wang, Lijie Alfred, Strauss |
format |
Conference or Workshop Item |
author |
Van Coile, Ruben Balomenos, Georgios P. Pandey, Mahesh D. Caspeele, Robby Criel, Pieterjan Wang, Lijie Alfred, Strauss |
author_sort |
Van Coile, Ruben |
title |
Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
title_short |
Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
title_full |
Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
title_fullStr |
Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
title_full_unstemmed |
Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
title_sort |
computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire |
publishDate |
2018 |
url |
https://hdl.handle.net/10356/88637 http://hdl.handle.net/10220/44709 https://biblio.ugent.be/publication/8130731 |
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1681044028828680192 |