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This paper focuses on analyzing the ice and wind conditions for a high voltage transmission line system going over mountainous terrain in British Columbia, Canada. After analyzing sixteen surrounding weather stations, an Artificial Neural Network (ANN) is performed for wind speed predictions, the Inverse Distance Weighted Interpolation method (IDW) is used for temperature estimations, and the K Nearest Neighbor Imputation (KNNI) is performed for precipitation rate on the unsampled site of interest. In-cloud icing is estimated using a simple empirical equation proposed by Makkonen & Ahti (1995), in addition to the ice accretion model proposed by Makkonen (2000). The weather data from the described procedure is compared with data from a Weather Research and Forecast model (WRF) reported in previous studies. The wind speed and ice accretion data are fitted to the Weibull and Generalized Pareto distributions, respectively, and five hundred years of data pairs are simulated in addition to the historical data based on those distributions. Finally, hazard contours are drawn, and the results are compared with the combined wind and ice values proposed in the National Standard of Canada (CSA-C22.3) for different reliability levels. • Provides weather analysis of 16 weather stations for a specific site of interest located in mountainous terrain. • Analyzes ice accretion on transmission lines. • Characterizes joint wind and ice hazard. • Provides a comparison with the standard CSA-C22.3 for three different hazard levels. [ABSTRACT FROM AUTHOR]

Since 1976, I have had the opportunity to meet Dr. Davenport frequently for courses, the code committee (ISO TC 98), international conferences, and private meetings. In 1979, I spent 3 weeks as an academic visitor at Boundary Layer Wind Tunnel Laboratory of The University of Western Ontario. It was the starting point for a lot of exchanges. I had the chance to organize a course in 1983, in which he taught together with Barry Vickery. In the framework of the ISO TC 98 norm committee, Dr. Davenport wrote, in a few hours in Vienna, a new and very simple type of code of practice for the wind loads on buildings. This was the basis for the Swiss Code and now for the simplified method of the Eurocode. Much of our experimental work is the extension of Davenport''s ideas, which he developed in his works and through private discussions. I plan to report on all these developments in this paper.Three years ago, Dr. Davenport acted as an expert for the C. Alexandrou Thesis. Whenever in Switzerland, Alan never forgets to contact us.This paper is also written in the context of the elaboration of the Eurocode. It gives us the opportunity to recall some useful basic concepts well known among the wind engineering specialists. Finally, two original and recent works of the author''s wind engineering group are presented. [Copyright &y& Elsevier]

The performance and durability of wall assemblies are greatly affected by the moisture load to which they may be subjected, in particular those arising from Wind-Driven Rain (WDR). Standard approaches for estimating such moisture loads assume 1% of the WDR load, whereas these loads have also been assessed from watertightness tests, although these assumed loads have been determined based on limited climate information. To more accurately estimate the moisture loads to which wall assemblies may be subjected over their service life, an analysis of historical WDR loads was completed for 11 cities across Canada. The magnitude, probability of occurrence of WDR loads in different cities and correlations between WDR related climate parameters, are discussed in this paper. Also, a novel WDR severity index is introduced, referred to as the Wind-Driven Rain Pressure Index, to permit quantifying the real-time and simultaneously occurring effects of WDR intensity and Driving Rain Wind Pressure (DRWP). To estimate the WDR intensity and DRWP with a specific probability of occurrence, an Extreme Value Analysis (EVA) was completed for a climate dataset of 31 years (1986–2016) using the Generalized Extreme Value and Gumbel distributions. • There is no correlation between the Wind-Driven Rain (WDR) load and concurrent Driving Rain Wind Pressure (DRWP). • A novel Wind-Driven Rain Pressure Index (WDRPI) is proposed. • Current watertightness test protocols are not reflecting most of the WDR conditions. • Gumbel distribution is a better option to generate the Intensity-Duration-Frequency curve for the WDR and WDRPI. • WDR conditions in different cities varies greatly. [ABSTRACT FROM AUTHOR]