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Lange D.,SP Fire Research | Devaney S.,Institute for Infrastructure and the Environment | Usmani A.,Institute for Infrastructure and the Environment
Engineering Structures | Year: 2014

The Pacific Earthquake Engineering Research (PEER) Center's Performance Based Earthquake Engineering (PBEE) framework is well documented. The framework is a linear methodology which is based upon obtaining in turn output from each of the following analyses: hazard analysis; structural analysis; loss analysis, and finally decision making based on variables of interest, such as downtime or cost to repair. The strength of the framework is in its linearity, its clear flexibility and in the consideration of uncertainty at every stage of the analysis. The framework has potential applications to other forms of extreme loading; however in order for this to be achieved the 'mapping' of the framework to the analysis of structures for other loading situations must be successful.This paper illustrates one such 'mapping' of the framework for Performance Based Fire Engineering (PBFE) of structures. Using a combination of simple analytical techniques and codified methods as well as random sampling techniques to develop a range of response records, the PEER framework is followed to illustrate its application to structural fire engineering. The end result is a successful application of the earthquake framework to fire which highlights both the assumptions which are inherent in the performance based design framework as well as subjects of future research which will allow more confidence in the design of structures for fire using performance based techniques.This article describes the PEER framework applied to structural earthquake design then follows the framework from start to completion applying suitable alternative tools to perform each stage of the analysis for structures in fire. © 2014 Elsevier Ltd. Source

Lange D.,Institute for Infrastructure and the Environment | Roben C.,Institute for Infrastructure and the Environment | Usmani A.,Institute for Infrastructure and the Environment
Engineering Structures | Year: 2012

A methodology for assessing the vulnerability of tall buildings to fire on multiple floors is presented. It is based upon numerical modelling of real and imagined tall building structures. Key results from the modelling work are also presented here to introduce and illustrate two potential failure mechanisms for tall buildings in multiple floor fires. Events leading up to the failure of an external column are described for the two collapse mechanisms identified, namely, a weak floor failure mechanism and a strong floor failure mechanism.In the weak floor mechanism failure initiates in a non-fire floor and spreads progressively to adjacent floors above and below the fire affected floors. Failure is first initiated in the nearest floor below the fire affected floor which experiences large axial or membrane compressions giving rise to large P-δ moments (in addition to the pre-existing load induced moments) leading either to a buckling or a flexure failure. If the floors do not fail then the strong floor failure mechanism can occur caused by large P-δ moments in the column as a result of the inward deflection of the column in the region of the fire floors. These mechanisms are discussed in detail to understand the structural behaviour before and during collapse, following which a summary of additional numerical work to further illustrate the failure mechanisms is presented.Following discussion of the failure mechanisms, a simple design assessment methodology is proposed which could potentially offer engineers a useful tool for estimating the upper bound collapse mechanisms for tall buildings subjected to a range of multiple floor fires without resorting to complex and labour-intensive finite element models. The methodology is first demonstrated in comparison with the results obtained for the two collapse mechanisms discussed in detail in the numerical modelling part of the paper, and then it is compared with the summary of a series of numerical results from a parametric analysis to ensure that the method produces conservative results. © 2011 Elsevier Ltd. Source

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