| 摘要: |
| 近年来，随着我国城市高层、高密
度建筑群的发展，城市通风、热岛效应、空
气污染以及行人热舒适度等已经成为研究
城市高层建筑群体设计的重要课题。同时，
环境性能化模拟与实验工具的不断发展，针
对城市风环境影响进行初期概念设计决策
的作用愈加凸显。本文首先介绍了以物理风
洞为模拟工具的实验平台，包括数据采集、
性能可视化设计方法探索；然后开发了一套
针对高密度城市高层建筑群体的机械生形
装置，打通建筑几何生成与城市风环境数
据参数的关联；在此基础上，提出了一种将
神经网络算法应用于高层建筑群场景的建
筑几何生成设计优化算法。由此，实现城市
设计导向的、基于城市高密度风环境性能化
的、高层建筑形体预测与生成方法研究 |
| 关键词: 物理风洞 神经网络算法 动态
模型 城市高层建筑 环境性能化生形 |
| DOI：10.13791/j.cnki.hsfwest.20190103 |
| 分类号: |
| 基金项目:国家重点研发计划资助（2016YFC0702104）；
国家自然科学基金资助（51578378）；中德科
学中心国际合作项目（GZ1162）；上海市科学
技术委员会项目（16DZ1206502，16DZ2250500，
17DZ1203405） |
|
| Research on High-Rise Building Group Morphology Generative Design Method Based on PhysicalWind Tunnel and Neural Network Algorithm |
|
YUAN Feng,LIN Yuqiong
|
| Abstract: |
| In recent years, with the rapid development of urban high-rise and high-density
buildings in China, urban ventilation, heat island effect, air pollution and thermal comfort at
pedestrian level is becoming an important topic in the study of high-density and high-rise urban
design. Since the environmental assessment in the design stage can have a direct and significant
impact on the final quality of the city, it is particularly important to rethink the relationship
between architectural form and urban micro climate, especially the internal logic between
urbanmorphology and natural ventilation, and to explore the design method driven by wind
environment optimization in the early design stage. Therefore, with the continuous development
of environmental performance simulation and experimental tools, the past “trial-and-error”
passive design method is gradually replaced by logical generation design, and the role of
early conceptual design decision-making for urban wind environment impact is becoming
increasingly prominent. However, at present, a large number of performance simulation tools
are subject to the tradeoff between simulation accuracy and time consumption, which makes it
difficult to bring timely feedback in the early stage of design. In fact, the iterative generation
method based on digital simulation tools only chooses the best among the limited random
solutions, not from the environmental performance to the inverse solution of the scheme
form. This “post-evaluation” paradigm cannot really satisfy the architect’s comprehensive
requirements for the environmental performance design.
Firstly, this paper introduces the experimental platform using physical wind tunnel as
simulation tool, including data acquisition and performance visualization design method
exploration. It has the advantages of easy operation, controllable cost, and stable flow field and
so on, guided by the initial shape generation design of the scheme. Its perception and real-time
acquisition of environmental data make the wind environment simulation change from the postdesign
verification to the front-end design exploration.After that, this study summarizes several
commonly appliedurban morphologydesign strategies for wind environment performance
optimization of high-rise buildings in high-density cities, including rotation, twisting, concaveconvex,
hollowing, lifting-up, and develops a set of dynamic model devices for high-rise
buildingsfor physical wind tunnel test. In the experiment of urban morphology generation in
physical wind tunnel, firstly, the method of optimizing the layout of ventilated buildings is
adopted, and then the angle between building orientation and wind direction is determined by
wind tunnel experiment under the condition that the building layout is initially determined by
sunshine. Finally, the specific form is determined to achieve the optimal control of the overall
wind environment of the block. The dynamic model controls the parameters of different servosdirectly by the program, and uses the servos and gears to drive each building model to move. It constantly changes the orientation and shape of
the building, including the size of the hollow facade, the external shape of distortion or indentation, and the height of the overhead. The dynamic
model has the possibility of generating a large number of different morphology data instantaneously, which meets the needs of machine learning
for massive sample data, and opens up the relationship between building geometry generation and urban wind environment data.On this basis, an
optimization algorithm of building geometry genera?摩敯獮椠条湮? design based on neural network algorithm is proposed in this paper. The generation
system based on neural network includes four parts: morphology optimization strategy, mechanical dynamic system, simulation evaluation system
and intelligent prediction system. The parameter logic can be described as the data circulation process of “geometric parameter group - mechanical
parameter group - environmental parameter group”. In this study, the twisting form in high-rise buildings are selected for wind tunnel experiments
under different plane and elevation strategies, and the mechanical parameters of each morphology scheme and the corresponding environmental
data obtained from experiments are taken as sample data to construct a neural network regression model to predict the optimal morphology of
twisted buildings under the control of various wind environment independently.
Thus, this paper presents a design-oriented, performance-based, high-rise building group morphology generation, prediction and optimization
design method based on natural wind environment in high-density urban districts. The application of physical wind tunnel is trying to solving
the problems of complex operation and feedback timeconsumption of using CFD (computational fluid dynamics) software. The introduction of
dynamic model makes it possible to obtain a large number of entity building models in a short time. The combination of neural network algorithm
maximizes the application of wind tunnel test data to realize the direct conversion of design-oriented from environmental performance to
architectural geometry. It has found that, in the early stage of urban design, the optimal control of urban form according to the wind environment
can be realized, which may avoid the economic and resource losses caused by the repeating modified design based on the local wind environment
criteria and pedestrians’ requirement in the later adjustment stage of design, which overturns the “post-evaluation” mode of environmental
performance of contemporary architectural |
| Key words: Physical Wind Tunnel Neural Network Algorithms Dynamic Model Environmental Performance Building Morphology Generation |
