Material properties at elevated temperatures are important factors in the fire safety design and numerical analysis of cold-formed steel structures. Most of the previous research on material properties at high temperatures has adopted the steady-state test method. However, the transient-state test method is more realistic for actual fire conditions. This paper presents a detailed experimental investigation of Q345 cold-formed steel with a nominal yield strength of 345 MPa and a thickness of 1.5 mm under transient- and steady-state conditions. Both the flat and corner parts of Q345 cold-formed steel sections are considered. The results showed that the steady-state method was not equivalent to the transient-state method for Q345 steel; in addition, current standards provided overestimations for the mechanical properties of Q345 steel under elevated temperatures. An empirical equation was proposed to estimate the reduction factors for the yield and ultimate strength and the elastic modulus of Q345 st...

For structural health monitoring (SHM), a complete dataset is crucial for further modal identification analysis and risk warning. Unfortunately, data loss can occur due to sensor failure, transmission system interruption, or hardware failure, which can lead to missing data. Therefore, this study proposes a bidirectional long short-term memory neural network (Bi-LSTM) response recovery method based on variational mode decomposition (VMD) and sparrow search algorithm (SSA) optimization that utilizes the structural response data between multiple sensors and can simultaneously consider temporal and spatial correlations. A dataset containing approximately half a month of monitoring data was collected from a certain project for training, validation, and testing. A publicly available dataset was also referenced to validate the proposed method in this paper. Using the public dataset, under 13 different data loss rates, the VMD + SSA + Bi-LSTM model reduced the RMSE of data reconstruction by an average of 65.01% and 45.35% compared to the Bi-LSTM model and the VMD + Bi-LSTM models, respectively, while the coefficient of determination increased by 62.21% and 11.19%. The data reconstruction method proposed in this paper can accurately reconstruct the variation trends of missing data without the manual optimization of hyperparameters, and the reconstruction results are close to the real data.

The fire resistance of cold-formed steel (CFS) structures is receiving increasing concern in fire safety design. With the purpose of improving both fire performance and construction efficiency, a new CFS joist–autoclaved lightweight concrete (ALC) composite floor was developed, and a detailed fire experiment on five full-scale floor assemblies was performed. The results showed that the fire resistance of the floor assembly with a double layer of gypsum plasterboard ceiling and a load level of $2.0\mathrm{kN}/{\mathrm{m}}^2$ was extended from 75 to 83 min by the use of 35-mm thick rock wool insulation that was laid firmly between adjacent steel joists during construction; heat transfer to the compression flange of the steel joists was delayed significantly under fire conditions. The fire resistance of floor assemblies increased with decreasing load levels, but such behavior might become insignificant once the steel joists were directly exposed to fire as the ceiling finish fell off. It also was determined that the fire performance of Bolivian magnesium board was considerably better than that of gypsum plasterboard, extending fire resistance approximately 30 min in the tests. All assemblies experienced local compression failure of the top flange and the adjacent lip and web at the midspan of joists, and showed the fire resistance ratings beyond 60 min. The CFS composite floor with a ceiling configuration of only a single layer of Bolivian magnesium board demonstrated substantial competitive advantage in cost and efficiency, and was recommended for potential applications in midrise CFS structures.

This paper presents a simplified method to predict the thermal and mechanical behavior of a new cold-formed steel floor system at room and elevated temperatures. A four-point bending test of such a floor assembly was performed at room temperature, and an efficient method to estimate the elastic rigidity and strength of the floor system was verified. The temperature progression of the floor section in a fire situation was well predicted based on the implicit finite difference method, taking into account the effects of ceiling materials falling off. A thermal-mechanical model was then developed by simplifying the floor system to a laterally restrained joist subject to constant vertical load and a non-uniform temperature distribution. The time-dependent vertical deflection of the floor joist was well predicted, whereas the response in the final stage of fire exposure was overestimated, probably due to the severe joist degradation and the neglected contribution of the autoclaved lightweight concrete s...