Application of Probabilistic Robustness Framework: Risk Assessment of Multi-Storey Buildings under Extreme Loading

• Published in: Structural engineering international : journal of the International Association for Bridge and Structural Engineering (IABSE) Vol. 22; no. 1; pp. 85 - 79
• Main Authors: Izzuddin, Bassam A., Pereira, Miguel F., Kuhlmann, Ulrike, Rölle, Lars, Vrouwenvelder, Ton, Leira, Bernt J.
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 01.02.2012
• Subjects: extreme loading; multi-storey buildings; progressive collapse; risk assessment; robustness
• ISSN: 1016-8664; 1683-0350
• DOI: 10.2749/101686612X13216060213518

Risk assessment is a requirement for robustness design of high consequence class structures, yet very little guidance is offered in practice for performing this type of assessment. This paper demonstrates the application of the probabilistic risk assessment framework arising from COST Action TU0601 to multi-storey buildings subject to extreme loading. A brief outline of the probabilistic framework is first provided, including the main requirements of describing uncertainty in the hazards and the associated local damage as well as the consequences of global failure. From a practical application perspective, it is emphasised that there is a need for (a) computationally efficient deterministic models of global failure for specific local damage scenarios, and (b) effective probabilistic simulation methods that can establish the conditional probability of global failure on local damage. In this respect, this work utilises a recently developed multi-level deterministic assessment framework for multi-storey buildings subject to sudden column loss, which is coupled with a response surface approach utilising first-order reliability methods to establish the conditional probability of failure. The application of the proposed approach is illustrated to a multi-storey steel-composite building, where it is demonstrated that probabilistic risk assessment is a practical prospect. The paper concludes with a critical appraisal of probabilistic risk assessment, highlighting areas of future improvement.