The multi-strip method is often used to establish a demand model for fragility analysis. Using the multi-strip method to scale the ground motion record may cause uncertainty and bias in structural response calculation and fragility assessment. It is necessary to analyze the effect of differences in the amplitude scaling range in different strips on structural seismic response calculation and seismic fragility assessment. In this paper, the multi-strip method was used to analyze the seismic demand bias based on four multi-story reinforced concrete frame structures subjected to eight ground motion record sets. The bias, variance, and coefficient of variation in different strips in each group of ground motion records were obtained. The effect of different strips on the demand bias was investigated by analysis of variance (ANOVA). Uncertainty quantification of structural demand and fragility curves was carried out using the bootstrap sampling method. The results for structures in different ground motion record sets verify that the differences between the demand bias for different strips by amplitude scaling are statistically insignificant for a 95% confidence level. These findings will contribute to the use of scaling methods for ground motion record sets in a probabilistic seismic demand assessment, allowing for a more reliable prediction of structural seismic fragility.

A significant challenge in probabilistic seismic demand analysis lies in selecting appropriate intensity measures and investigating their relationships with demand parameters to ensure accurate seismic fragility predictions. A single ground motion intensity measure is insufficient to capture the complex characteristics of ground motion, leading researchers to focus on compound intensity measures. It is essential to investigate the selection of ground motion features and the number of features included in the construction of compound intensity measures, as these measures cannot comprise an unlimited set of ground motion features. This study focused on machine learning feature selection methods to select ground motion features for compound intensity measures, utilizing mutual information for feature selection. Considering the symmetry and asymmetry requirements of this process, optimized features were selected. Based on the selected features, the compound ground motion intensity measure was constructed to evaluate structural seismic fragility. The compound ground motion intensity measure was evaluated against scalar intensity measure in terms of correlation, efficiency, practicality, proficiency, and sufficiency. A comprehensive comparative analysis demonstrates the applicability of the compound intensity measure. The study’s findings support fragility analysis and performance evaluation using compound intensity measures. The corresponding results can be applied in the risk analysis aspect of performance-based earthquake engineering.

A transfer–purge chamber (TPC) is a double-steel-plate, heavy-concrete, curved-surface composite structure composed of steel plates, heavy concrete, and shear connectors. It is an important facility in the external refueling system of a nuclear power plant (NPP), providing a safe and reliable biological shielding space for reactor refueling operations. Temperature load is one of the most important factors that must be considered in the design of NPP structures. The temperature loads experienced by the TPC during its life cycle include those encountered in both normal and abnormal operation, which are distinct. In this study, we investigated the steady state and transient-state temperature fields and stresses of a TPC structure under normal operation and after 48 h of abnormal operation, respectively, which were calculated using Abaqus finite element software and the directly coupled method. During normal operation, the temperature field of the structure shows relatively uniform changes, and the temperature gradient of the internal concrete in the direction of its thickness has a constant value of 0.245 °C/cm. At the junction between the transfer and purge sub-chambers of the TPC, under the influence of wall curvature and deformation constraints, the maximum tensile strain of heavy concrete is 8.84 × 10⁻³, the maximum compressive strain is 2.04 × 10⁻³, the peak stress of the steel plate is 98.305 MPa, and the peak stress of the stud is 306.725 MPa. After 48 h of abnormal operation, the temperatures of the inner surface of the heavy concrete of the wall, the inner steel plate of the wall, the outer surface of the heavy concrete of the wall, and the inner steel plate of the wall increased by 8.12, 8.11, 0.31, and 0.30 °C, respectively. The tensile strain of the heavy concrete of the wall increased significantly by 52.64%, and the compressive strain of the concrete increased by 67.33%, whereas the stresses of the studs and steel plates increased by only 1.57% and 6.79%, respectively. These results show that the change in the temperature field greatly influences the stress and strain on the TPC structure. As measures for mitigating the development of this unfavorable situation of temperature stress concentration, the temperature operating range should be rationally controlled or the junction structure between the transfer and purge sub-chambers of the TPC optimized accordingly. The results of our study can provide basic data for a dynamic analysis of the TPC under conditions of combined earthquake and temperature loads.

Earthquake damage to urban highway system can cause major traffic disruption which can adversely impact post-earthquake emergency response, repair, and reconstruction operations, and the economy of region will be also greatly affected. In present paper, the seismic risk analysis of urban transportation networks is presented, which focuses on the development of seismic risk analysis simulation system for urban transportation networks. By applying several numerical analysis methods, seismic response simulation of components in a highway system (e.g., bridges, roadways, etc.) is carried out. With the aid of the latest WebGIS technology, the results of all simulations are published to the network so that residences and government officials can share a common recognition of earthquake hazard and disaster. Moreover, combined with the city’s real-time traffic status, the system can be used as a command platform for the post-earthquake emergency rescue.