Advances in calculation theory of wind and rain loads and failure estimation for transmission tower-line systems

Typhoon landing is frequent in coastal areas of China. In the existing cases of transmission line collapse caused by the typhoon, most of the reasons are attributed to strong wind, and there are few discussions on the factors of rain loads. This paper systematically summarized the research progress of domestic and foreign research teams on the combined effect of wind and rain, which included: according to the wind speed and rainfall data, a conversion model of rain intensity with different time resolutions was proposed, and then established a joint probability distribution model of wind speed and rain intensity, revealing the correlation of wind speed and rain intensity. Based on the Lagrangian equations of motion of the solid particle, the evolution mechanism of single raindrop motion was revealed, which put forward the concept of wind rain velocity ratio, and found out the mechanism that the horizontal velocity of the raindrop was greater than the wind speed at the corresponding position at first. Two kinds of rain load models were summarized from the perspective of the acting mechanism: collision force model and aerodynamic model, and their calculation methods and wind tunnel test verification were introduced in detail. The method for calculating the fragility and the failure probability of transmission tower structure under wind and rain excitation was established. The existing research results show that the collapse of engineering structures often occurs in a few minutes or even tens of seconds. When calculating the combined wind and rain loads, the short-term rain intensity should be considered. When considering the multi-disaster effects of wind and rain, the failure probability of engineering structure is significantly greater than that of wind load alone. The climate difference in different regions is significant, so the joint probability distribution model of wind and rain should be established according to the locally measured meteorological data for analysis. © 2023 Science Press. All rights reserved.