遗传算法
计算机科学
被动式太阳能建筑设计
数学优化
建筑工程
建筑设计
太阳增益
帕累托原理
太阳能
工程类
数学
机器学习
电气工程
作者
Longwei Zhang,Lingling Zhang,Yuetao Wang
出处
期刊:Solar Energy
[Elsevier BV]
日期:2016-03-14
卷期号:132: 38-50
被引量:142
标识
DOI:10.1016/j.solener.2016.02.053
摘要
In the severe cold zones of China, solar radiation is one of the most important issues in architectural design. The design seeks to make buildings receive more direct sunlight within the limits of the user’s comfort and simultaneously save energy and space. So far in China, the design of solar radiation has usually been qualitative, not quantitative, and it is often implemented by architects with experience or those following convention. This rough and rigid design approach is not accurate or efficient, particularly in the design of free-form buildings, which comprise a class of irregular-form buildings popular in current architectural design. Moreover, solar radiation is not the only thing that needs to be considered; shape coefficient and space efficiency should also be considered in free-form building design. This study proposes a method for a free-form building that receives more solar radiation though shape optimization and takes into account the other two objectives mentioned above. This paper provides a method with a “Modeling–Simulation–Optimization” framework. In the process of applying this method, parametric modeling with Rhinoceros and Grasshopper is used to build up the free-form building model, and the shape optimization of the building is processed by using the multi-objective genetic algorithm to make sure the three objectives—i.e., to maximize solar radiation gain, to maximize space efficiency, and to minimize the shape coefficient—are all achieved. Finally, a Pareto frontier is generated to show the optimal solutions and to assist designers in making final decisions. The case study shows that compared with the cube-shaped reference building, the total solar radiation gain of the optimized free-form shape building is 30–53% higher, and the shape coefficient value is reduced by 15–20%, with a decrease of less than 5% of the space-efficiency values. The proposed method, according to the basic process of architecture design, uses a performance-driven approach to find solutions that satisfy the requirements. It can be used in real architectural design to solve practical optimization problems.
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