基于径向基函数与正交试验的高层住宅被动式节能设计多元因素分析

张辉; 韩啸霖; 弓南; 朱富城

doi:10.13204/j.gyjzG20042002

基于径向基函数与正交试验的高层住宅被动式节能设计多元因素分析

doi: 10.13204/j.gyjzG20042002

湖北工业大学土木建筑与环境学院, 武汉 430068

基金项目:

国家自然科学基金项目（51508169）；中国国家留学基金委"地方合作项目"资助（202008420322）。

详细信息

作者简介:
张辉,男,1980年出生,博士,副教授,硕士生导师。电子信箱:zhhust@163.com

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出版历程
- 收稿日期: 2020-04-20
- 网络出版日期: 2021-08-19

MULTI-FACTOR ANALYSIS OF PASSIVE ENERGY SAVING DESIGN FOR HIGH-RISE RESIDENCE BASED ON RBF AND ORTHOGONAL EXPERIMENT

School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China

摘要

摘要: 节能设计目标和建筑性能要求的不断提升，给节能设计提出了更高要求。影响节能设计的多元因素非线性关系无疑增加了进一步挖掘节能设计潜力的难度。针对高层住宅被动式设计优化问题，引入径向基函数（RBF）神经网络和正交试验设计极差法，探讨了高层住宅节能50%、65%、75%不同目标下的被动式设计因素对能耗的影响关系。通过建立性能分析模型，选取外墙、外窗、屋顶、楼板、内墙、窗墙比、建筑朝向和建筑层数等因素，采用径向基函数（RBF）神经网络建立采暖制冷能耗快速反应模型，并通过正交试验设计极差法，探讨不同节能目标下，影响因素对采暖制冷等能耗状况的影响关系以及优先度排序。试验表明：65%和75%的节能目标使高层住宅外墙和外窗的节能影响更为突出；节能目标的提高，改变了被动式因素的影响排序；从50%到75%节能要求的提升使得被动式因素对节能率的影响从3%降低为0.5%。
- 高层住宅 /
- 被动式节能设计 /
- RBF神经网络 /
- 正交试验设计
Abstract: The goal of energy conservation design and the requirement of building performance have been constantly improved, which has put forward higher requirements for energy conservation design. Moreover, the nonlinear relationship of multiple factors that affect the energy saving design undoubtedly increases the difficulty of further tapping the potential of energy saving design. Aiming at the optimization of passive design of high-rise residential buildings, the paper introduced radial basis function (RBF) neural network and orthogonal experiment design range method, and discussed the influence of passive design factors on energy consumption of high-rise residential buildings under different energy saving targets of 50%, 65% and 75%. In this research, analysis model was set up, and different factors, such as exterior wall, exterior window, roof, floor, interior wall, window-wall ratio, building orientation and number of floors were selected. Meanwhile, based on radial basis function (RBF) neural network, the heating and cooling energy consumption rapid response model was established to explore different energy-saving targets, the influencing factors on the heating and cooling energy consumption relations as well as the influence of the priority order, through the orthogonal experiment design process. The experiment showed that 65% and 75% of the energy saving targets could make the energy saving effect of the outer wall and the outer window of the high-rise residence more prominent. The improvement of energy saving target had changed the influence ranking of passive factors, and the increase in energy efficiency requirements from 50% to 75% reduced the impact of passive factors on energy efficiency from 3% to 0.5%.
- high-rise residence /
- passive energy-saving design /
- radial basis function neural network /
- orthogonal experiment design

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