This paper presents the experimental and finite element analyses of the behaviours of stub circular and square concrete-filled double steel tubular (CFDST) columns intermittently welded with plate stiffeners under axial compression. The plate stiffeners are welded to the inner surface of the outer tube through predrilled holes. Twenty specimens consisting of two concrete-filled steel tubular (CFST), two unstiffened CFDST, and sixteen stiffened CFDST were tested under axial compression to determine the failure patterns and obtain the load versus axial shortening curve. The key variables are the distance of weld spacing and the dimension of the plate stiffeners. Based on the experiment results, the authors have identified the possible local buckling locations, including the peak load of the specimens that were significantly affected by the intermittently welded plate stiffeners. The developed finite element model is verified by comparing the current and previous experimental results, and it provides an acceptable mean ratio of 1.01 and a standard deviation of 0.04. The validated FE model is employed in a parametric study to investigate the effects of critical parameters, including the two shapes of the specimens, dimension of the plate stiffeners, and weld spacing, on the load-carrying capacity. The findings of the parametric study can be used to justify the optimum dimensions of plate stiffeners for the best stiffened CFDST performance.

Compressive strength performance of concrete after exposure to the elevated temperature is important for evaluating and repairing concrete structures. This paper presents an experimental study to determine the residual compressive strength of concrete used in tunnel lining after exposed to tunnel fire. Two types of concrete tunnel lining segments are evaluated in this study. One of it was constructed using a patented fire-resistant concrete (MYC) containing high volume fly ash and nanosilica (HVFANS). Another concrete tunnel lining segment was constructed using concrete containing silica fume normally used in the current construction, coded as SPC concrete. The drilled core results show that, after exposure to tunnel fire temperature up to around 1045°C, the compressive strength of MYC has dropped to 66% of the design strength. In comparison, the SPC concrete showed a decrease in compressive strength to 62% of design strength. The experimental results confirmed that the SPC segments have shown slightly lower residual compressive strength compared to the MYC segments. However, the MYC tunnel segment shows high resistance to the spalling of cover concrete compared to the SPC tunnel segment. Therefore, it can be said that the residual strength alone is not sufficient to compare the damage of concrete exposed to tunnel fire; the spalling damage observation is similarly important as it is one of the important serviceability criteria for designing concrete structures.

Interlocking Inter-Module Connections (IMCs) in Modular Steel Buildings (MSBs) have garnered significant interest from researchers. Despite this, the optimisation of plate thicknesses in such structures has yet to be extensively explored in the existing literature. Therefore, this paper focuses on optimising the thickness of interlocking IMCs in MSBs by leveraging established experimental and numerical simulation methodologies. The study developed various numerical models for IMCs with plate thicknesses of 4 mm, 6 mm, 10 mm, and 12 mm, all subjected to compression loading conditions. The novelty of this study lies in its comprehensive parametric analysis, which evaluates the slip prediction model. A random forest regression model, trained using the ‘TreeBagger’ function, was also implemented to predict slip values based on applied force. Sensitivity analysis and comparisons with alternative methods underscored the reliability and applicability of the findings. The results indicate that a plate thickness of 11.03 mm is optimal for interlocking IMCs in MSBs, achieving up to 8.08% in material cost reductions while increasing deformation resistance by up to 50.75%. The ‘TreeBagger’ random forest regression significantly enhanced slip prediction accuracy by up to 7% at higher force levels.