Wind loading on a transmission tower structure is jointly influenced by the wind field, structural parameters, and the geo-spatial configuration of the transmission line. Considering the multi-parametric effect, this paper aims at developing a limit capacity model for transmission towers under strong winds. To this end, the limit capacity of the tower is expressed via two equivalent means: one is the limit wind speed as a function of the wind angle of attack and the span of transmission line; the other is a limit capacity surface with three fundamental wind load components as the principal axes. An adaptive kriging surrogate modeling is constructed to approximate the function/surface with structural uncertainties considered. The performance of the surrogate model is improved by adding support points and then evaluated by the overall accuracy validation and local error check. A numerical example demonstrating the feasibility of the surrogate modeling for the limit capacity of the transmission tower under winds is presented. Finally, a fragility assessment concerning a practical transmission line and towers subjected to typhoons is accomplished using the established limit capacity model of the tower.

Urban London plane (Platanus × acerifolia) street trees require efficient and interpretable methods for identifying individuals that warrant closer inspection within large roadside inventories. This study developed a two-layer screening framework for 2022 London plane trees along six urban roads in Nanjing, China. First, wind-tunnel tests of five standardized crown geometries were used to derive geometry-specific drag-moment coefficients and calculate aerodynamic crown-loading potential (ACLP), a relative indicator of crown-related aerodynamic demand. ACLP was calculated only for trees within the tested crown height-to-width range. Second, measurements from 19 windthrown London plane trees after Typhoon Bebinca were used to derive a local lower-quartile root-plate reference and calculate a root-plate reference aperture ratio (RPAR) from recorded tree-pit width. Of the 2022 inventoried trees, 1273 (63.0%) fell within the tested crown-geometry range, and 128 were identified as high-ACLP candidates using a 90th-percentile screening threshold. These candidates were strongly concentrated on two roads, and the principal road-level pattern remained stable across alternative percentile thresholds. The post-storm analysis provided a separate local reference for identifying tree-pit apertures that were comparatively small relative to observed root-plate dimensions. ACLP and RPAR should therefore be interpreted as distinct first-stage screening indicators rather than as predictors of windthrow probability or anchorage capacity. The framework provides a transparent basis for prioritizing follow-up field inspection and allocating limited urban tree-management resources.