Influence of time resolution and averaging techniques of meteorological data on the estimation of wind-driven rain load on building facades for Canadian climates

被引:11
|
作者
Ge, Hua [1 ]
机构
[1] Concordia Univ, Dept Bldg Civil & Environm Engn, Montreal, PQ H3G 1M8, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Wind-driven rain; Building facades; Semi-empirical models; Meteorological data; Averaging techniques; CFD-based catch ratio method; SIMULATION; VALIDATION; EXPOSURE; MODEL;
D O I
10.1016/j.jweia.2015.04.019
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper investigates the influence of time resolution of meteorological data and the averaging techniques on the quantification of wind-driven rain amount on building facades for Canadian climates using three WDR models, i.e. the ISO and ASHRAE 160P semi-empirical models, and the CFD-based catch ratio method. A cubic low-rise building is used as a case study. Meteorological data i.e. wind speed, wind direction and rainfall intensity are collected at 5-mM intervals at three building sites in Vancouver, Montreal and Fredericton. The 5-min data is used as the reference. The analyses show that when semi-empirical WDR models are used, the arithmetic averaging gives a better estimation while the weighted averaging tends to overestimate the WDR amount. When the detailed CFD-based catch ratio method is used, the weighted averaging technique provides a better estimation, however, the difference between the arithmetic and weighted averaging is within 3-7% for the three Canadian cities investigated. Therefore, the choice of averaging techniques depends on the WDR models to be employed and the climates. (c) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:50 / 61
页数:12
相关论文
共 32 条
  • [31] On the significance of the climate-dataset time resolution in characterising wind-driven rain and simultaneous wind pressure. Part II: directional analysis
    Perez-Bella, Jose M.
    Dominguez-Hernandez, Javier
    Cano-Sunen, Enrique
    del Coz-Diaz, Juan J.
    Rabanal, Felipe P. Alvarez
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2018, 32 (06) : 1799 - 1815
  • [32] Representative meteorological data for long-term wind-driven rain obtained from Latin Hypercube Sampling - Application to impact analysis of climate change
    Bourcet, J.
    Kubilay, A.
    Derome, D.
    Carmeliet, J.
    BUILDING AND ENVIRONMENT, 2023, 228