Comparing methods of modeling air infiltration through building entrances and their impact on building energy simulations

被引:31
|
作者
Goubran, Sherif [1 ]
Qi, Dahai [1 ]
Saleh, Wael F. [2 ]
Wang, Liangzhu [1 ]
机构
[1] Concordia Univ, Dept Bldg Civil & Environm Engn, Ctr Zero Energy Bldg Studies, 1455 Maisonneuve Blvd West, Montreal, PQ H3G 1M8, Canada
[2] Assiut Univ, Dept Mech Engn, Assiut 71516, Egypt
关键词
Air infiltration; Entrance doors; Vestibules energy savings; Experimental validation; Airflow and energy simulations;
D O I
10.1016/j.enbuild.2016.12.071
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Building entrance doors are a major source of air infiltration and energy loss in commercial buildings. Previous studies have calculated entrance doors air infiltration and energy saving potential of vestibules with the simplified method which is based on pressure factors. However, challenges are still faced in estimating the pressure difference and the resultant infiltration rates across doors as well as validating the used airflow coefficients under different flow conditions. In this paper, an experimental study is used to validate the airflow coefficient for a fully open single door under both infiltration and exfiltration conditions. The study presents four methods for modeling air infiltration across automatic single and vestibule doors for two reference building models: two methods use the pressure factors and the two others are based on airflow simulations. Energy simulations are then conducted using the air infiltration rates obtained from each method. The results revealed that the design methods overestimate the pressure difference across doors, the air infiltration rates as Well as the vestibule savings potentials in comparison to the simulation methods. In conclusion, airflow simulations were found to provide more realistic estimates of pressure differences and infiltration rates across entrance doors when compared to the widely-used design methods. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:579 / 590
页数:12
相关论文
共 50 条
  • [41] Building Energy Performance Modeling through Regression Analysis: A Case of Tyree Energy Technologies Building at UNSW Sydney
    Tahmasebinia, Faham
    He, Ruihan
    Chen, Jiayang
    Wang, Shang
    Sepasgozar, Samad M. E.
    BUILDINGS, 2023, 13 (04)
  • [42] Interoperability from building design to building energy modeling
    Garcia, Elizabeth Guzman
    Zhu, Zhenhua
    JOURNAL OF BUILDING ENGINEERING, 2015, 1 (33-41) : 33 - 41
  • [43] Italian TRYs: New weather data impact on building energy simulations
    Lupato, Giorgio
    Manzan, Marco
    ENERGY AND BUILDINGS, 2019, 185 : 287 - 303
  • [44] Quantifying the Impact of Urban Microclimate in Detailed Urban Building Energy Simulations
    Kyriakodis, Georgios-Evrystheas
    Bozonnet, Emmanuel
    Riederer, Peter
    PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA, 2020, : 3714 - 3721
  • [45] Influence of infiltration on energy consumption of a winery building
    Sun H.
    Yang Q.
    Frontiers in Energy, 2014, 8 (1) : 110 - 118
  • [46] Impact of ELA Calibration Methods on Building Energy Model Fidelity
    Althobaiti, Mohanned
    Augenbroe, Godfried
    PROCEEDINGS OF BUILDING SIMULATION 2021: 17TH CONFERENCE OF IBPSA, 2022, 17 : 1611 - 1618
  • [47] Building simulations help to save energy
    Voelker, Conrad
    Vogel, Albert
    BAUPHYSIK, 2022, 44 (06) : 309 - 310
  • [48] Neural model of residential building air infiltration process
    Technical University of Wroclaw, Institute of Air-Conditioning and District Heating, 4/6 Norwida Street, 50-370 Wroclaw, Poland
    不详
    不详
    不详
    不详
    不详
    不详
    J. Civ. Eng. Manage., 2006, 1 (83-88):
  • [49] Energy Consumption Optimization through Dynamic Simulations for an Intelligent Energy Management of a BIPV Building
    Papas, Ilias
    Estibals, Bruno
    Ecrepont, Christelle
    Alonso, Corinne
    2018 7TH INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATIONS (ICRERA), 2018, : 853 - 857
  • [50] How close are urban scale building simulations to measured data? Examining bias derived from building metadata in urban building energy modeling
    Bass, Brett
    New, Joshua
    Clinton, Nicholas
    Adams, Mark
    Copeland, Bill
    Amoo, Charles
    APPLIED ENERGY, 2022, 327