He, Kunhou; (2022) A study on the fire-induced progressive collapse of steel plated structures of offshore installations. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

For fire safety engineering of structures and infrastructures, it is required to characterise the structural crashworthiness in fires. The present study aims to develop advanced computational methodologies to simulate the crashworthiness of steel plated structures in fires. To achieve the goals, the following tasks were undertaken: (a) complete a literature review on fire safety engineering of structures, (b) examine the mechanism of structural crashworthiness in fires by large-scale physical model testing, (c) develop advanced computational models for the structural crashworthiness analysis in fires, (d) validate the developed computational models by comparison with test data, and (e) demonstrate the applicability of the developed methods to realistic plated structures in fires. For this purpose, a physical model testing was performed on a full-scale steel stiffened plate structure under lateral patch loading in fires to obtain a fire test database. Steel plate panels of an as-built 1900 TEU containership in compliance with test facility in maximum size and capacity were considered as a reference structure, with principal dimensions of 7 m long and 4.8 m wide fitted with two transverse frames and seven longitudinal stiffeners. Lateral patch loading was applied using two loading actuators at the centre of each transverse frame. The fire test was conducted in a furnace fuelled by liquefied petroleum gas, where the maximum gas cloud temperature inside the furnace was increased up to 15% below the target ISO 834 fire curve during testing. A time history of the lateral deformations of the test structure was measured with the focus on a critical period until the structure reached the ultimate limit state (or collapse) after the fires started. Details of the test database are documented, which is confirmed to be useful for validating computational models for structural failure analysis in fires. Additional work was completed to experimentally examine the effects of passive fire protection application on the fire collapse of steel stiffened plate structures. Another full-scale physical model testing was conducted where the test set-up is the same as the previous one, but the transverse frames (primary strength members) were protected with cerawool which is a fire protection material. The structural collapse was monitored at discrete time intervals from when the fire started until the test structure entirely collapsed. The effect of fire-protected transverse frames on the structural collapse was investigated by comparison with test results on the structure that was unprotected from the fires. It is confirmed that passive fire protection is an efficient option to delay structural collapse. New computational models for the analyses of heat transfer (from ambient to steel temperatures) and fire-induced progressive collapse behaviour of steel stiffened plate structures without or with PFP were developed using transient thermal elastic-plastic large-deformation finite element models. A comparison between test data and numerical computations was made to validate the developed computational models. It is confirmed that modelling the steel structure and PFP as shell elements in a single layer is successful and the developed computational methods are useful for both heat transfer analysis and nonlinear structural response. To demonstrate that the developed computational models can be applied to the analysis of the heat transfer and fire-induced progressive collapse behaviour of the topside structures of a ship-shaped offshore installation, a hypothetical VLCC-class floating, production, storage and offloading (FPSO) unit hull structure is considered, and CFD simulations involving fire events under three gas release levels were performed. Transient thermal elastic-plastic large-deformation finite element models were used. Finally, the applicability of the newly developed computational models is verified.

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