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Quantifying airtightness-to-infiltration conversion: A long-term field study under variable temperature differences

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This study reveals that the common "divide-by-20 rule" for estimating building air infiltration rates is inaccurate in Korea. New, seasonally adjusted correlation factors are needed due to significant temperature variations impacting building airtightness.

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Area of Science:

  • Building science
  • Environmental engineering
  • Energy efficiency

Background:

  • Accurate estimation of natural air infiltration is crucial for building energy performance and indoor air quality.
  • Existing methods, like the divide-by-20 rule, may not adequately account for diverse climatic conditions.
  • Korea's significant annual temperature difference (30°C) presents a unique challenge for infiltration modeling.

Purpose of the Study:

  • To investigate the relationship between natural infiltration rates and building airtightness in Korea.
  • To evaluate the suitability of the existing divide-by-20 rule for Korean climatic conditions.
  • To develop and validate new correlation factors for infiltration rate estimation.

Main Methods:

  • Long-term measurements of natural infiltration rates using tracer gas methods.
  • Airtightness performance assessment via blower door tests.
  • Comparison of measured infiltration rates with predicted rates using the divide-by-20 rule and derived factors.

Main Results:

  • Observed airtightness values in test rooms ranged from 0.2-1.0 h⁻¹ (low to moderate).
  • Infiltration rates showed a direct correlation with indoor-outdoor temperature differences and outdoor wind speed.
  • Derived correlation factors (40-122) significantly exceeded the divide-by-20 rule, indicating potential overestimation by the rule.

Conclusions:

  • The divide-by-20 rule may overestimate natural infiltration rates in regions with large temperature fluctuations.
  • Seasonal variations in correlation factors are essential for accurate infiltration estimation in diverse climates.
  • Recommended new correlation factors, segmented by temperature differences for cooling and heating seasons, are proposed for Korea.