## 5 Conclusions and Prospect  
This study focuses on a new type of prefabricated modular RCS hybrid structural node. By designing a RCS composite node that considers the combined effect of floor slabs, we used the finite element software ABAQUS for detailed modeling. The effectiveness and reliability of the adopted research methods were verified through comparison with existing experimental data. We further analyzed the seismic performance of prefabricated modular RCS nodes with or without floor slab involvement, and explored the impact of various parameters such as the axial compression ratio, bolt preload, reinforcement ratio, and floor slab concrete strength on the seismic performance of the nodes through numerical simulations. Based on the above research, we draw the main conclusions. First of all, the comparison between the results of the low-cycle repetitive loading failure mode, hysteresis curve and skeleton curve of the finite element simulation, and the existing test data shows that the failure position is consistent, the curve shape is similar, and the nodes show good seismic performance in line with the design principle of \"strong column and weak beam\". Additionally, the participation of the floor transforms the steel beam into a composite section formed by the concrete slab and the steel beam, significantly increasing the effective height and stiffness, thereby greatly improving the seismic performance of the RCS composite joints. The hysteresis loops of the RCS joints accounting for the floor slab exhibit fuller shapes compared to those without a floor slab, demonstrating an enhanced energy dissipation capacity, ultimate load capacity, and stiffness. Although ductility experiences a slight decrease, it still meets practical application requirements. Our research has revealed that both the axial compression ratio and the concrete strength of the slab significantly influence the seismic performance of the joints. A moderate increase in the axial compression ratio can enhance the core confinement and shear capacity of the joint. However, excessively high axial compression ratios may lead to concrete failure, thereby compromising the seismic performance. At the same time, increasing the strength of the slab concrete can improve compressive performance, but too much strength can result in stiffness mismatch, reducing energy dissipation and ductility. Therefore, it is necessary to reasonably select relevant parameters during design to achieve optimal performance. The thickness of the slab, reinforcement ratio, and bolt preload are equally crucial for the seismic performance of the joints. Increasing the slab thickness enhances the effective height of the composite beam section, thereby improving both the load-carrying capacity and energy dissipation capabilities. Elevating the reinforcement ratio bolsters the tensile strength of the concrete, which improves performance under negative loading. Additionally, increasing the bolt preload directly influences the stability of the connections, enhancing the seismic performance of the joints. Therefore, a rational combination of these design parameters will contribute to optimizing the seismic performance of the joints. Despite the phased achievements of the research, further exploration is still needed in the following areas: First, the current model does not consider the impact of assembly errors within a certain range during construction on the long-term performance of nodes. Future studies could integrate digital twin technology to conduct lifecycle performance evolution research. Second, this study primarily relies on finite element simulation. In the future, experimental validation should be combined to enhance the reliability of conclusions. Third, machine learning algorithms such as neural networks can be integrated to intelligently optimize hundreds of parametric samples, breaking through the efficiency bottleneck of traditional trial-and-error methods.