Thermal Analysis Infrastructure in OpenSees for Fire and its Smart Application Interface Towards Natural Fire Modelling

Understanding the fire behaviour in buildings is fundamental and crucial to the practice of structural fire safety design. Traditionally, time-temperature curves associated with a burning rate developed from the compartment fire framework are most widely used by structural engineers and applied as a load to the structure. However, the adequacy of homogenous temperature distribution in fully developed fires was questioned by researchers after reviewing the existing fire test data, which suggested a localised burning nature of the fires in relatively large compartments. A groundbreaking travelling fire concept and travelling fire models were then proposed intending to provide an engineering description to this type of natural fire behaviour. The work in this paper was driven by such a trend and first summarises the modelling infrastructure in OpenSees to estimate the thermal response of structural members subjected to various scenario fires, followed by providing a smart application interface to capture the appropriate form of natural fire model through Python-OpenSees framework. The developed modelling infrastructure is validated against uniform and localised fire tests, which are also discussed regarding the smoke effect afterwards. Using the Python-OpenSees infrastructure, a real-scale localised fire test and the Malveira travelling fire test are modelled to demonstrate the modelling strategy. The work as preliminary attempts has shown the necessity of introducing additional variables when describing the natural fire impact, and this framework can be further improved in future by including more fire dynamics research and full-scale fire test input.

Automated summary

Understanding fire behavior in buildings is crucial for structural fire safety design practice. The paper introduces a new modeling infrastructure in OpenSees to estimate thermal response of structural members to various fires, and provides an interface to capture natural fire models. Validation against fire tests and incorporating more fire dynamics research is suggested for future improvement.