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An attached cantilever scaffold, which mainly consists of a cantilever horizontal steel beam and a diagonal bar, is a new type of cantilever scaffold. The upper end of the diagonal bar is attached to an upper floor slab by a hinge, while the lower end is connected to a cantilever beam. Therefore, the position of the lower suspension point has a significant impact on the overall mechanical performance. However, current research on this topic is limited. Thus, in this study, we aim to optimize the mechanical behavior by changing the lower suspension point position. An optimization methodology based on the genetic algorithm is proposed. This methodology has been demonstrated to be efficient and accurate enough to determine the optimal lower suspension point position of a diagonal bar. The effects of different beam cross-sections, diagonal bar diameters, and upper suspension point positions are further investigated. The bearing capacity is shown to improve by more than 100% and 30% for hinged and rigidly connected cantilever beams when the proposed optimization methodology is adopted. The analysis in this study can serve as a reference for the optimal design of an attached cantilever scaffold and can provide a theoretical basis for developing related design software.

This study proposes an improved mixed-variable quantum particle swarm optimization (QPSO) algorithm capable of optimizing both continuous and discrete variables. The algorithm is applied to the wind resistance optimization of a cable-stiffened, single-layer spherical reticulated shell (SLSRS), optimizing discrete variables like member dimensions and cable dimensions alongside continuous variables such as cable prestress. Through a computational case study on an SLSRS, the optimization results of the proposed QPSO method are compared with other optimization techniques, validating its accuracy and reliability. Furthermore, this study establishes a mathematical model for the wind resistance optimization of cable-stiffened SLSRSs and outlines the wind resistance optimization process based on the mixed-variable QPSO algorithm. The optimization of these structures reveals the strong stability and global search capabilities of the proposed algorithm. Additionally, the comparison of section optimization and shape optimization highlights the significant impact of the shell shape on steel usage and costs, underscoring the importance of shape optimization in the design process.

Cable-stiffened steel columns (CSSC) have a high load-carrying capacity and strong stability compared to ordinary steel columns. In practical engineering, the connection between the crossarm and main column of a CSSC is usually welded. However, the welding-residual stress adversely affects the steel column. In this study, pre-cast CSSCs, with a pinned connection between the crossarm and main column, are presented. The new type of pre-cast CSSCs avoid the welding-residual and are easy to disassemble. A model test and numerical analysis of its global stability behavior under eccentric compression is conducted. Based on the analysis, the buckling modes of these columns are defined and a method for determining the governing imperfection in a nonlinear buckling analysis is proposed. The effects of slenderness ratio, cross-arm length, cable diameter, and other parameters on the load-carrying capacities of the columns are investigated using the proposed method. The results of this study can be used as a reference for the engineering designs and specifications of pre-cast CSSCs.