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Elevated temperature material properties are essential in predicting structural member's behavior in high-temperature exposures such as fire. Even though experimental methodologies are available to determine these properties, advanced equipment with high costs is required to perform those tests. Therefore, performing those experiments frequently is not feasible, and the development of numerical techniques is beneficial. A numerical technique is proposed in this study to determine the temperature-dependent thermal properties of the material using the fire test results based on the Artificial Neural Network (ANN)-based Finite Element (FE) model.

An ANN-based FE model was developed in the Matlab program to determine the elevated temperature thermal diffusivity, thermal conductivity and the product of specific heat and density of a material. The temperature distribution obtained from fire tests is fed to the ANN-based FE model and material properties are predicted to match the temperature distribution.

Elevated temperature thermal properties of normal-weight concrete (NWC), gypsum plasterboard and lightweight concrete were predicted using the developed model, and good agreement was observed with the actual material properties measured experimentally. The developed method could be utilized to determine any materials' elevated temperature material properties numerically with the adequate temperature distribution data obtained during a fire or heat transfer test.

Temperature-dependent material properties are important in predicting the behavior of structural elements exposed to fire. This research study developed a numerical technique utilizing ANN theories to determine elevated temperature thermal diffusivity, thermal conductivity and product of specific heat and density. Experimental methods are available to evaluate the material properties at high temperatures. However, these testing equipment are expensive and sophisticated; therefore, these equipment are not popular in laboratories causing a lack of high-temperature material properties for novel materials. However conducting a fire test to evaluate fire performance of any novel material is the common practice in the industry. ANN-based FE model developed in this study could utilize those fire testing results of the structural member (temperature distribution of the member throughout the fire tests) to predict the material's thermal properties.

In this study, the insulation fire ratings of lightweight foamed concrete, autoclaved aerated concrete and lightweight aggregate concrete were investigated using finite element modelling.

Lightweight aggregate concrete containing various aggregate types, i.e. expanded slag, pumice, expanded clay and expanded shale were studied under standard fire and hydro–carbon fire situations using validated finite element models. Results were used to derive empirical equations for determining the insulation fire ratings of lightweight concrete wall panels.

It was observed that autoclaved aerated concrete and foamed lightweight concrete have better insulation fire ratings compared with lightweight aggregate concrete. Depending on the insulation fire rating requirement of 15%–30% of material saving could be achieved when lightweight aggregate concrete wall panels are replaced with the autoclaved aerated or foamed concrete wall panels. Lightweight aggregate concrete fire performance depends on the type of lightweight aggregate. Lightweight concrete with pumice aggregate showed better fire performance among the normal lightweight aggregate concretes. Material saving of 9%–14% could be obtained when pumice aggregate is used as the lightweight aggregate material. Hydrocarbon fire has shown aggressive effect during the first two hours of fire exposure; hence, wall panels with lesser thickness were adversely affected.

Finding of this study could be used to determine the optimum lightweight concrete wall type and the optimum thickness requirement of the wall panels for a required application.

Light-Gauge Steel Frame (LSF) structures are popular in building construction due to their lightweight, easy erecting and constructability characteristics. However, due to steel lipped channel sections negative fire performance, cavity insulation materials are utilized in the LSF configuration to enhance its fire performance. The applicability of lightweight concrete filling as cavity insulation in LSF and its effect on the fire performance of LSF are investigated under realistic design fire exposure, and results are compared with standard fire exposure.

A Finite Element model (FEM) was developed to simulate the fire performance of Light Gauge Steel Frame (LSF) walls exposed to realistic design fires. The model was developed utilising Abaqus subroutine to incorporate temperature-dependent properties of the material based on the heating and cooling phases of the realistic design fire temperature. The developed model was validated with the available experimental results and incorporated into a parametric study to evaluate the fire performance of conventional LSF walls compared to LSF walls with lightweight concrete filling under standard and realistic fire exposures.

Novel FEM was developed incorporating temperature and phase (heating and cooling) dependent material properties in simulating the fire performance of structures exposed to realistic design fires. The validated FEM was utilised in the parametric study, and results exhibited that the LSF walls with lightweight concrete have shown better fire performance under insulation and load-bearing criteria in Eurocode parametric fire exposure. Foamed Concrete (FC) of 1,000 kg/m3 density showed best fire performance among lightweight concrete filling, followed by FC of 650 kg/m3 and Autoclaved Aerated Concrete (AAC) 600 kg/m3.

The developed FEM is capable of investigating the insulation and load-bearing fire ratings of LSF walls. However, with the availability of the elevated temperature mechanical properties of the LSF wall, materials developed model could be further extended to simulate the complete fire behaviour.

LSF structures are popular in building construction due to their lightweight, easy erecting and constructability characteristics. However, due to steel-lipped channel sections negative fire performance, cavity insulation materials are utilised in the LSF configuration to enhance its fire performance. The lightweight concrete filling in LSF is a novel idea that could be practically implemented in the construction, which would enhance both fire performance and the mechanical performance of LSF walls.

Limited studies have investigated the fire performance of structural elements exposed to realistic design fires. Numerical models developed in those studies have considered a similar approach as models developed to simulate standard fire exposure. However, due to the heating phase and the cooling phase of the realistic design fires, the numerical model should incorporate both temperature and phase (heating and cooling phase) dependent properties, which was incorporated in this study and validated with the experimental results. Further lightweight concrete filling in LSF is a novel technique in which fire performance was investigated in this study.