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Sustainability-Based Development of a Remote Technique to Assess the Effectiveness of Thermal Insulation in Households in West Virginia

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  • Prateek Vaish

    (Department of Mechanical, Materials and Aerospace Engineering West Virginia University, Morgantown, WV 26506, USA)

  • Ken Means

    (Department of Mechanical, Materials and Aerospace Engineering West Virginia University, Morgantown, WV 26506, USA)

  • Bhaskaran Gopalakrishnan

    (Department of Industrial and Management Systems Engineering, West Virginia University, Morgantown, WV 26506, USA)

  • Hailin Li

    (Department of Mechanical, Materials and Aerospace Engineering West Virginia University, Morgantown, WV 26506, USA)

  • John James Recktenwald

    (Department of Mechanical, Materials and Aerospace Engineering West Virginia University, Morgantown, WV 26506, USA)

Abstract

As structures age, air leaks naturally form and can remain undetected for years, resulting in increased utility bills and, in severe cases, structural damage. The traditional method to determine if a structure has developed these leaks is through an energy audit, including blower door testing, which is costly and disturbs normal use of the building. A numerical approach to indicate the presence of air leaks, for instance, a simple mathematic formula requiring only simple building information available to any layman, would be of great value. Within this paper, a formula was developed for climate Zone 5 regions using multiple linear regression models to infer the presence of air leaks using only four input variables. To validate the model, this framework was applied to a series of 700–770 square foot (65.03–71.54 m 2 ) apartment units in Morgantown, West Virginia, USA. The model was determined to be able to accurately estimate the energy consumption of a given unit within this size range with 20% accuracy, which can then be used to ascertain sub-optimal, and thus unsustainable, consumption of energy. This framework can be applied in additional climate zones to create a more robust and generally applicable formula.

Suggested Citation

  • Prateek Vaish & Ken Means & Bhaskaran Gopalakrishnan & Hailin Li & John James Recktenwald, 2025. "Sustainability-Based Development of a Remote Technique to Assess the Effectiveness of Thermal Insulation in Households in West Virginia," Sustainability, MDPI, vol. 17(5), pages 1-28, February.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:1845-:d:1596842
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    References listed on IDEAS

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    1. Emery, A.F. & Kippenhan, C.J., 2006. "A long term study of residential home heating consumption and the effect of occupant behavior on homes in the Pacific Northwest constructed according to improved thermal standards," Energy, Elsevier, vol. 31(5), pages 677-693.
    2. Mattsson, Björn, 2006. "The influence of wind speed, terrain and ventilation system on the air change rate of a single-family house," Energy, Elsevier, vol. 31(5), pages 719-731.
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