기밀성능 데이터를 이용한 자연상태 침기량 산정을 위한 변환계수 N 도출

초록

The evaluation of natural air infiltration rates in buildings commonly uses the ACH50 value divided by an N-factor, but the standard N-factor of 20, derived from foreign contexts, may not accurately reflect Korean conditions. This study seeks to propose a more suitable N-factor using a theoretical model that incorporates pressure differences arising from the stack effect, wind, and mechanical systems. Pressure differences were calculated by analyzing 25 years of wind speed and outdoor temperature data (2000–2024) and validated through statistical methods, including normality tests. Additionally, Blower Door Test results from over 1,400 residential buildings were analyzed, with outlier removal conducted during preprocessing. The representative pressure differences were applied to leakage functions to compute N-values, and probability density functions were used to calculate weighted representative values. Findings reveal significant variations based on building height and seasonal changes. High-rise buildings are especially impacted by the stack effect, while low-rise buildings show less variation. The highest N-factor was observed in summer, reflecting the smaller temperature difference between indoor and outdoor environments, which results in a lower estimated infiltration rate. Conversely, the larger temperature difference exceeding 10℃ during winter enhances stack-driven infiltration, leading to a lower N-factor.By deriving an N-factor tailored to Korea’s building environment, this study improves the accuracy of natural air infiltration rate calculations and enhances energy modeling efficiency.

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