Graphical Representation of Climate-Based Daylight Performance to Support Architectural Design
Graphical Representation of Climate-Based Daylight Performance to Support Architectural Design
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DOI：
10.1080/15502724.2008.10747628
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发表时间：
2008-07-01
期刊：
影响因子：
3.6
通讯作者：
Anderson, Marilyne
中科院分区：
文献类型：
--
作者：
Kleindienst, Sian;Bodart, Magali;Anderson, Marilyne
许多传统的日光照明设计工具是有限的，因为每个模拟只代表一年中的一个时间和一天中的一个时间（或一个理论上的阴天条件）。由于日光是如此多变-由于太阳的运动，季节的变化和不同的天气条件-一个时刻很难代表采光设计的整体质量，这就是为什么基于气候的动态性能指标，如日光自主性（DA）和有用的日光照度（UDI）是如此需要。更进一步，性能的年度变化（通过DA和UDI浓缩为百分比）也是有价值的信息，将这些数据与空间可视化和渲染相关联的能力也是如此。试图使用现有工具实现这种分析需求的组合将成为一个过于耗时和乏味的过程。挑战在于以可管理的形式提供早期设计阶段决策所需的所有信息，同时保持年度数据的连续性。本文介绍了一种气候数据简化方法的基础上分裂的一年分为56个时期，在此期间的天气条件是“平均”和模拟使用佩雷斯的ASRC-CIE天空模式，而太阳穿透的信息提供了更高的分辨率。以“时间图”形式产生的数据的图形输出将在视觉上甚至在数字上与使用短时间步长计算并基于Daysim生成的照度数据创建的参考案例图相当。
Many conventional daylighting design tools are limited in that each simulation represents only one time of year and time of day (or a single, theoretical overcast sky condition). Since daylight is so variable - due to the movement of the sun, changing seasons, and diverse weather conditions - one moment is hardly representative of the overall quality of the daylighting design, which is why climate-based, dynamic performance metrics like Daylight Autonomy (DA) and Useful Daylight Illuminance (UDI) are so needed. Going one step further, the annual variation in performance (condensed to a percentage by DA and UDI) is also valuable information, as is the ability to link this data to spatial visualizations and renderings. Trying to realize this combination of analytical needs using existing tools would become an overly time-consuming and tedious process. The challenge is to provide all information necessary to early design stage decision-making in a manageable form, while retaining the continuity of annual data. This paper introduces a climate data simplification method based on a splitting of the year into 56 periods, over which weather conditions are "averaged" and simulated using Perez's ASRC-CIE sky model, while information on sun penetration is provided at a greater resolution. The graphical output of the produced data in the form of "Temporal Maps" will be shown to be visually, and even numerically, comparable to reference case maps created using short time step calculations and based on illuminance data generated by Daysim.