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多中庭形态对寒区商场碳排放的影响机理

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为揭示当代寒区大型商场多中庭形态对碳排放的影响机理,以哈尔滨某集中式中庭的商场为例,采用BP神经网络预测结合敏感性分析和相关性分析的方法,探究中庭数量(n)、主次中庭面积比(r)、主次中庭距离(d0)、天窗面积占比(S0)、中庭面积占比(S1)五个要素对碳排放的影响机制.研究结果表明,S0、S1、r、d0、n对碳排放的影响程度依次递减,其中S0、S1、r、d0为关键影响要素,且均与总碳排放呈正向关系,适当减小中庭面积占比和天窗面积占比、增加中庭聚集度和面积均匀度有利于建筑减碳.
INFLUENCE MECHANISM OF MULTI-ATRIUM SHAPE ON CARBON EMISSION OF SHOPPING MALLS IN COLDREGION
A shopping mall with centralized atrium in Harbin is taken to study the influence mechanism of multiple atrium forms on carbon emissions of large shopping malls in cold areas,in which BP neural network prediction com-bined with sensitivity analysis and correlation analysis are adopted.The influence mechanism of five factors on car-bon emission is explored,including number of atriums(n),area ratio of primary and secondary atriums(r),distance between primary and secondary atriums(d0),skylight area ratio(S0),and area ratio of atrium(S1).The results show that the influence of S0,S1,r,d0 and n on carbon emission decreases successively,in which S0,S1,r and d0 are the key influencing factors,and all of them are positively correlated with total carbon emission.It is conducive to building carbon reduction by reducing the proportion of atrium area and skylight area and by increasing the concentration and uniformity of atrium area.

multiple atrium configurationsbuilding carbon emissionsBP neural networksobol sensitivity analy-sisshopping mall

安雪男、李铁军、史小蕾、高枫

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哈尔滨工业大学建筑学院,寒地城乡人居环境科学与技术工业和信息化部重点实验室,哈尔滨 150006

哈尔滨工业大学建筑设计研究院,哈尔滨 150090

哈尔滨工业大学建筑设计研究院寒地建筑与环境理论研究中心,哈尔滨 150001

哈尔滨理工大学建筑工程学院,哈尔滨 150086

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多中庭形态 建筑碳排放 BP神经网络 Sobol敏感性分析 寒区大型商场

黑龙江省重点研发计划项目黑龙江省博士后科学基金项目

2022ZX01A33LBH-Z22190

2024

低温建筑技术
黑龙江省寒地建筑科学研究院

低温建筑技术

影响因子:0.237
ISSN:1001-6864
年,卷(期):2024.46(2)
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