Abstract
To demonstrate adequate structural fire safety for exceptional designs, the uncertainties of the design input parameters must be explicitly considered. In this contribution, the case study included in ISO/CD TR 24679-8:2020 of a concrete column subject to a standardized heating regime is revisited considering improved uncertainty modelling for the input parameters. Monte Carlo simulations are applied to obtain the distribution of the axial load bearing capacity of the column, \({P}_{\max}\), at 240 min of ISO 834 standard fire exposure. The obtained distribution however does not fit any distribution type commonly assumed for the resistance effect. To get more detailed information on the parameters governing the distribution of \({P}_{\max}\), and to allow for the application of more efficient calculation procedures and the development of design guidance, a detailed analysis of the obtained distribution for the load bearing capacity is conducted. The effect of each of the input parameters’ uncertainty on the column capacity is quantified using three different methods of sensitivity analysis. Furthermore the distribution type describing the concrete load bearing capacity for the considered standard fire exposure is evaluated in detail. It is concluded that the parameter defining the quantile of the concrete strength retention is the main contributor to the variability of the column capacity at 240 min standard fire exposure. Furthermore, it is found that the column capacity can be described by a mixed lognormal distribution, considering constituent lognormal distributions for fixed concrete strength retention parameter values. Based on these findings, improvements for probability of failure calculations of fire-exposed concrete columns are developed. The analysis provides insight for the reliability-based design of concrete columns exposed to fire, achieving a specified target safety level.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Van Coile, R., Hopkin, D., Lange, D., Jomaas, G., & Bisby, L. (2019). The need for hierarchies of acceptance criteria for probabilistic risk assessments in fire engineering. Fire Technology, 55, 1111–1146. https://doi.org/10.1007/s10694-018-0746-7
ISO. (2020). ISO/CD TR 24679-8 fire safety engineering—Performance of structures in fire. Part 8: example of a probabilistic fire design of structures. International Organization for Standardization, Geneva, Switzerland.
Biasoli, F., Mancini, G., Just, M., Curbach, M., Walraven, J., Gmeiner, S., Arrieta, J., Frank, R., Morin, C., Robert, F., Poljansek, M., Kamenarova, B., Dimova, S., Pinto Vieira, A. (2014). Eurocode 2: background and applications, design of concrete buildings. Worked examples. Publications Office of the European Union, Luxemburg.
ISO. (2017). ISO/TR 24679-6:2017 fire safety engineering—Performance of structures in fire—Part 6: example of an eight-storey office concrete building. Geneva, Switzerland: International Organization for Standardization.
Franssen, J.-M., & Gernay, T. (2017). Modeling structures in fire with SAFIR®: Theoretical background and capabilities. Journal of Structural Fire Engineering, 8, 300–323. https://doi.org/10.1108/JSFE-07-2016-0010
CEN. (2004). EN 1992-1-2:2004: Eurocode 2: Design of concrete structures—Part 1-2: General rules. Structural fire design. European Standard.
Qureshi, R., Ni, S., Elhami Khorasani, N., Van Coile, R., Hopkin, D., & Gernay, T. (2020). Probabilistic models for temperature dependent strength of steel and concrete. Journal of the Structural Engineering. American Society of Civil Engineers, 146, 04020102. https://doi.org/10.1061/(asce)st.1943-541x.0002621
JCSS. (2001). Probabilistic model code. Part 3.10 dimensions. Joint Committee on Structural Safety.
Achenbach, M., Lahmer, T., & Morgenthal, G. (2017). Global sensitivity analysis of reinforced concrete walls subjected to standard fire—A comparison of methods. 14th International Probabilistic Workshop (pp. 97–106). Springer.
Holický, M., & Sýkora, M. (2010). Stochastic models in analysis of structural reliability. In Proceedings of the International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operation Management. Beer Sheva, Israel.
JCSS. (1999). Probabilistic model code. Part 3.11 excentricities. Joint Committee on Structural Safety.
Spearman, C. (1904). The proof and measurement of association between two things. American Journal of Psychology, 15, 72–101. https://doi.org/10.2307/1412159
Marzban, S., & Lahmer, T. (2016). Conceptual implementation of the variance-based sensitivity analysis for the calculation of the first-order effects. Journal of Statistical Theory and Practice, 10, 589–611. https://doi.org/10.1080/15598608.2016.1207578
Sobol, I. M. (2001). Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation, 55, 271–280. https://doi.org/10.1016/S0378-4754(00)00270-6
Saltelli, A. (2002). Making best use of model evaluations to compute sensitivity indices. Computer Physics Communications, 145, 280–297. https://doi.org/10.1016/S0010-4655(02)00280-1
Chaudhary, R. K., Van Coile, R., & Gernay, T. (2020). Fragility curves for the fire exposed structural elements through application of regression techniques. In 18th International Probabilistic Workshop.
Van Coile, R., Balomenos, G. P., Pandey, M. D., & Caspeele, R. (2017). An unbiased method for probabilistic fire safety engineering, requiring a limited number of model evaluations. Fire Technology, 53, 1705–1744. https://doi.org/10.1007/s10694-017-0660-4
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Jovanović, B., Van Coile, R. (2021). Probabilistic Characterization of the Axial Load Bearing Capacity of a Concrete Column Exposed to the Standard Fire. In: Matos, J.C., et al. 18th International Probabilistic Workshop. IPW 2021. Lecture Notes in Civil Engineering, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-030-73616-3_43
Download citation
DOI: https://doi.org/10.1007/978-3-030-73616-3_43
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-73615-6
Online ISBN: 978-3-030-73616-3
eBook Packages: EngineeringEngineering (R0)