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Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Two: Integrating the Indoor Air Quality, Moisture, and Thermal Comfort

Author

Listed:
  • Seyedmohammadreza Heibati

    (Department of Construction Engineering, École de Technologie Supérieure (ÉTS), University of Québec, Montréal, QC H3C 1K3, Canada)

  • Wahid Maref

    (Department of Construction Engineering, École de Technologie Supérieure (ÉTS), University of Québec, Montréal, QC H3C 1K3, Canada)

  • Hamed H. Saber

    (Prince Saud Bin Thuniyan Research Center, Mechanical Engineering Department, Jubail University College, Al Jubail 35716, Saudi Arabia)

Abstract

In this paper, an integrated model that coupled CONTAM and WUFI was developed to assess the indoor air quality (IAQ), moisture, and thermal comfort performance. The coupling method of CONTAM and WUFI is described based on the exchange of airflow rate control variables as infiltration, natural and mechanical ventilation parameters between heat and moisture flow balance equations in WUFI and contaminant flow balances equations in CONTAM. To evaluate the predictions of the integrated model compared to single models of CONTAM and WUFI, four scenarios were used. These scenarios are airtight-fan off, airtight-fan on, leaky-fan off, and leaky-fan on, and were defined for a three-story house subjected to three different climate conditions of Montreal, Vancouver, and Miami. The measures of the simulated indoor CO 2 , PM 2.5 , and VOCs obtained by CONTAM; the simulated indoor relative humidity (RH), predicted percentage of dissatisfied (PPD), and predicted mean vote (PMV) obtained by WUFI; and those obtained by the integrated model are compared separately for all scenarios in Montreal, Vancouver, and Miami. Finally, the optimal scenarios are selected. The simulated results of the optimal scenarios with the integrated model method (−28.88% to 46.39%) are different from those obtained with the single models. This is due to the inability of the single models to correct the airflow variables.

Suggested Citation

  • Seyedmohammadreza Heibati & Wahid Maref & Hamed H. Saber, 2021. "Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Two: Integrating the Indoor Air Quality, Moisture, and Thermal Comfort," Energies, MDPI, vol. 14(16), pages 1-40, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4915-:d:612559
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    References listed on IDEAS

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    1. Seyedmohammadreza Heibati & Wahid Maref & Hamed H. Saber, 2019. "Assessing the Energy and Indoor Air Quality Performance for a Three-Story Building Using an Integrated Model, Part One: The Need for Integration," Energies, MDPI, vol. 12(24), pages 1-18, December.
    2. Zhang, Fan & de Dear, Richard & Hancock, Peter, 2019. "Effects of moderate thermal environments on cognitive performance: A multidisciplinary review," Applied Energy, Elsevier, vol. 236(C), pages 760-777.
    3. Seyedmohammadreza Heibati & Wahid Maref & Hamed H. Saber, 2021. "Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Three: Development of Integrated Model and Applications," Energies, MDPI, vol. 14(18), pages 1-31, September.
    4. Mehrdad Rabani & Habtamu Bayera Madessa & Natasa Nord, 2021. "Building Retrofitting through Coupling of Building Energy Simulation-Optimization Tool with CFD and Daylight Programs," Energies, MDPI, vol. 14(8), pages 1-23, April.
    5. Jerzy Sowa & Maciej Mijakowski, 2020. "Humidity-Sensitive, Demand-Controlled Ventilation Applied to Multiunit Residential Building—Performance and Energy Consumption in Dfb Continental Climate," Energies, MDPI, vol. 13(24), pages 1-20, December.
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    Cited by:

    1. Wenhui Ji & Yanping Yuan, 2022. "Development of Assessing the Thermal Comfort and Energy Performance for Buildings," Energies, MDPI, vol. 15(16), pages 1-2, August.
    2. Seyedmohammadreza Heibati & Wahid Maref & Hamed H. Saber, 2021. "Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Three: Development of Integrated Model and Applications," Energies, MDPI, vol. 14(18), pages 1-31, September.
    3. Jeeheon Kim & Yongsug Hong & Namchul Seong & Daeung Danny Kim, 2022. "Assessment of ANN Algorithms for the Concentration Prediction of Indoor Air Pollutants in Child Daycare Centers," Energies, MDPI, vol. 15(7), pages 1-17, April.

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