标准摘要
[中文适用范围]: 本部分ISO 15927规定了两种程序,用于估算可能撞击任何给定朝向墙面的水量。它考虑了地形、局部遮蔽以及建筑物和墙体的类型。第一种方法(见第3章),基于重合的小时降雨量和风速数据,定义了计算以下内容的途径:- 年度平均指数,影响吸湿表面(如砖石)的含水量;- 雨溅指数,影响雨水通过砖石和其他墙体系统接缝渗透的可能性。第二种方法(见第4章),基于平均风速数据和定性记录的降雨存在及强度(当前天气代码),定义了计算吸湿材料(如砖石)被润湿的时段的方法,该时段在任何一年中被超过的概率为10%(通常称为平均重现期为10年)。第D章给出了两种方法的比较。给出了对两种方法的结果进行地形、局部遮蔽以及建筑物和墙体类型校正的程序。本部分ISO 15927中包括的方法不适用于:a) 有陡峭悬崖或深峡谷的山区;b) 年降雨量中超过25%来自严重对流风暴的地区;c) 降水主要由雪或冰雹组成的地区和时期。 [外文原描述]: ISO 15927-3:2009 specifies two procedures for providing an estimate of the quantity of water likely to impact on a wall of any given orientation. It takes account of topography, local sheltering and the type of building and wall. The first method, based on coincident hourly rainfall and wind data, defines the method of calculation of the annual average index, which influences the moisture content of an absorbent surface, such as masonry, and the spell index, which influences the likelihood of rain penetration through masonry and joints in other walling systems. The second method, based on average wind data and a qualitative recording of the presence and intensity of rain (the present weather code for rain), defines a method for calculating the spell length during which an absorbent material such as masonry is moistened, having a 10 % probability of being exceeded in any year (commonly referred to as having a mean return period of 10 years). ISO 15927-3:2009 provides a comparison between the two methods. ISO 15927-3:2009 gives procedures to correct the results of both methods for topography, local sheltering and the type of building and wall. The methods included in ISO 15927-3:2009 do not apply in mountainous areas with sheer cliffs or deep gorges, in areas in which more than 25 % of the annual rainfall comes from severe convective storms, and in areas and during periods when a significant proportion of precipitation is made up of snow or hail.
英文名称Hygrothermal performance of buildings - Calculation and presentation of climatic data — Part 3: Calculation of a driving rain index for vertical surfaces from hourly wind and rain data