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Design optimization of building geometry and fenestration for daylighting and energy performance

机译:针对日光和能源性能的建筑几何形状和开窗设计优化

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摘要

With the increasing demand for sustainable design and green buildings, building performance is having a greater influence on design decisions. Design decisions on building envelop, especially on building geometry, window and skylight size and placement are essential in the early design stage. This research proposes a building performance optimization process that can help designers simultaneously evaluate the daylighting and energy performance of numerous design options and generate optimized design. The proposed method utilizes parametric design, building simulation modeling, and genetic algorithms. A case study of a small office building is conducted to test and verify the effectiveness of the optimization process. The geometry of the case study building is optimized in three different climates, Miami, Atlanta, and Chicago. After the optimization, the daylighting performance metric UDI is increased by 38.7%, 31.6%, and 28.8%, and the energy performance metric EUI is decreased by 20.2%, 18.5%, and 17.9% compared to average performance values. Sensitivity analysis is performed to analyze the relationship between design variables and performance metrics. The skylight width and length are the most important variables for all locations, while the influence of the other variables varies greatly.
机译:随着对可持续设计和绿色建筑的需求不断增加,建筑性能对设计决策的影响更大。在早期设计阶段,关于建筑物外墙的设计决策,尤其是关于建筑物几何形状,窗户和天窗尺寸及位置的设计决策至关重要。这项研究提出了一种建筑性能优化过程,可以帮助设计师同时评估众多设计方案的采光和能源性能,并生成优化的设计。所提出的方法利用参数设计,构建仿真模型和遗传算法。进行了一个小型办公楼的案例研究,以测试和验证优化过程的有效性。案例研究大楼的几何形状在迈阿密,亚特兰大和芝加哥这三种不同的气候条件下进行了优化。优化之后,与平均性能值相比,采光性能指标UDI分别提高了38.7%,31.6%和28.8%,而能源性能指标EUI则分别降低了20.2%,18.5%和17.9%。进行敏感性分析以分析设计变量和性能指标之间的关系。天窗的宽度和长度是所有位置上最重要的变量,而其他变量的影响差异很大。

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