Building upon the analytical study of the structural configuration and prestress state of the drum-shaped quad-strut cable dome, we conducted further investigation into its structural configuration. By employing the nodal equilibrium equations to solve the prestress state analysis of the cable dome, we compared the effects of two different cable laying methods on the prestress state of the cable dome structure. These methods include equal length of the radial horizontal projection of the upper chord ridge cables and equal radial chord length of the upper chord ridge cables. The analysis results show that the radial length of the top chord and its corresponding radial horizontal projection length of the cable dome structure can effectively reflect the trend of the prestress state of the structural configuration. Furthermore, by using a rise-to-span ratio of 0.11 as a threshold, the cable dome configuration is categorized into the flat spheroidal structural configuration and the small hemispheroidal structural configuration. When the structure is analyzed using a small rise-to-span ratio, the difference in prestress calculations between the two structural configurations is found to be less than 10%. Additionally, the structure exhibits a more uniform distribution of prestress, with the prestress gradually increasing from the inner circle to the outer circle. However, when the rise-to-span ratio increases, the difference between the prestress calculation results of the two configurations also increases, emphasizing the need to deploy upper chord ridge cables based on equal radial chord lengths (arc lengths). The research presented in this paper provides a novel insight into the structural topological form and prestress state calculation of cable domes with this configuration.

The drum-shaped honeycomb-type cable dome departs from traditional concepts and incorporates the idea of multiple strut configurations. It is the most diverse type of cable dome structure. Both cables and struts serve as the main load-bearing components. Analyzing the effects of local component failure is crucial for designing large-scale cable domes able to resist continuous collapse. A numerical analysis model using the ANSYS finite element method with a 120 m span is established. Dynamic analysis methods are employed to study the response of structural internal forces and displacements during the failure of different component types. By defining the internal force dynamic coefficient and change coefficient, the structural continuity collapse resulting from component failure is determined based on computational results and observation of structural deformations. Furthermore, the importance of the various components within the overall structure is classified. The research findings indicate that the failure of individual components does not cause overall instability of the structure. The importance level of the ring cables and some upper chord ridge cables is higher than that of the inclined cables. Class a struts have a higher importance level than class b struts. Additionally, the importance level of outer ring components is higher than that of inner ring components.

Previous research has confirmed that the newly proposed pentagonal three–four strut hybrid cable dome exhibits superior static performance compared to traditional cable domes, though its dynamic characteristics still require further study. Cable domes are wind-sensitive structures, and the results of a wind-induced vibration analysis are beneficial for the selection and construction of cable domes. In this study, a finite element model of a new open-type cable dome with a span of 120 m is established. The MATLAB 2017a programming language is employed to simulate pulsating winds, followed by a nonlinear dynamic analysis to analyze the wind-induced vibrations of the structure. The reliability of the pulsating wind model is confirmed by comparing the simulated spectrum with the target spectrum. Moreover, a wind-induced vibration time history analysis is performed to obtain the node displacement and internal force of components wind vibration coefficients, aiding in the approximation of pulsating winds with average winds in a wind-resistant design. Furthermore, a parametric analysis is carried out, ranking nodes and components based on sensitivity. The result shows that the structure exhibits the strongest wind resistance when the rise–span ratio is $\mathrm{f}/\mathrm{l}=0.07$ and the thickness–span ratio is $\mathrm{h}/\mathrm{l}=0.08$. Notably, the outer upper chord node, $2\mathrm{a}$, and the inner lower chord hoop cable, ${\mathrm{H}}_1$, are identified as the most sensitive node and component within the structure, respectively. Overall, the structure demonstrates excellent wind resistance performance, and the maximum wind vibration coefficient value remains below 3.

Automatic building extraction plays an important role in various remote sensing applications, such as seismic disaster investigation, seismic hazard risk assessment, urban planning, and photogrammetry. Despite the substantial progress, state-of-the-art building extraction methods are still limited by two issues: (i) existing approaches leverage convolutional layers or non-local self-attention to encode the position-aware dependencies, while they cannot flexibly adapt to the complex background contexts and varied structure patterns of buildings; and (ii) the local details cannot be well preserved by existing hierarchical decoders due to the imperfect feature aggregation, yielding unsatisfactory segmentation outputs in the local adjacent region. To address these issues, we propose Relative Position Aggregated Transformer (RPAFormer), which is capable of modeling the relative position dependencies of buildings and producing accurate local details using a dual attention transformer network. Specifically, we propose a Relative Position-aware Self-attention (RPSA) framework to learn the token dependencies within the local window. A transformer decoder network consisting of multiple Cross Masked Attention (CMA) blocks is also introduced to fuse the multi-scale features. Extensive experiments demonstrate the superior performance of the proposed method and its great promise for real-world engineering deployment.