Xiufeng Chen

To investigate the mechanical performance of large plate girders used in boiler-supporting steel structures under eccentric loading, nine 1:5-scaled closed-section HK-type and open-section π-type specimens were designed and tested. The specimens had a span of 5960 mm, an overall length of 6220 mm, and a depth of 1760 mm. Concentric loading and eccentric loading with eccentricities of 30 mm, 60 mm, and 90 mm were considered. The results show that under eccentric loading, the mid-span displacement increased with increasing eccentricity for both HK-type and π-type specimens. Compared with π-type specimens, HK-type specimens exhibited smaller mid-span displacements and higher secant stiffness under the same eccentric loading conditions, indicating better deformation resistance. At a load level of 3000 kN, the secant stiffness of the HK-type specimen decreased from 192.31 kN/mm to 172.81 kN/mm as the eccentricity increased from 0 mm to 90 mm, while that of the π-type specimen decreased from 156.57 kN/mm to 142.18 kN/mm. The measured transverse brace stresses of π-type specimens were higher than those of HK-type specimens, indicating stronger interaction between the π-type girder and the lateral-restraint system under the applied eccentric-loading conditions. Under the adopted eccentric loading and lateral restraint conditions, the HK-type specimens exhibited smaller mid-span displacements, higher absolute secant stiffness, and lower transverse-brace stresses than the corresponding π-type specimens. This study provides experimental data for understanding the deformation behavior, torsional response, and stiffness degradation of large plate girders in boiler-supporting steel structures.

Disruption management is critical for airline operations, yet existing recovery models often assume deterministic disruption durations, limiting their effectiveness in real-world, uncertain environments. This paper addresses the integrated airline recovery problem under uncertain disruptions. To capture this uncertainty, delay times are modeled as fuzzy variables and a fuzzy chance-constrained programming model is developed, aimed at minimizing total recovery costs. The model is transformed into a deterministic equivalent using trapezoidal fuzzy numbers. An improved Greedy Randomized Adaptive Search Procedure (GRASP) algorithm is designed to efficiently solve the problem, balancing solution quality and computational efficiency through insert, exchange, and cancel. The local search process is enhanced by incorporating the acceptance criteria of the simulated annealing algorithm. The proposed method is validated using real-world airline data. Results show that, compared to the traditional GRASP algorithm, the improved GRASP algorithm can obtain better solutions in a shorter time; the solutions in deterministic scenarios tends to be more conservative, leading to resource waste; the proposed method can achieve airline recovery at the minimum recovery cost. Sensitivity analysis reveals that selecting an appropriate confidence level significantly influences recovery costs. This paper provides a robust framework for enhancing operational resilience and passenger satisfaction under uncertain conditions, offering practical insights for real-world application.