• Research Article

    An Integrated Passive and Active Strategy for Achieving ZEB 3 in Mid- and High-rise Wood Buildings

    중고층 목조건축물의 ZEB 3등급 달성을 위한 패시브·액티브 통합 전략

    Kang, Yujin, Park, Ji Hun, Kang, Seong Taek, Kim, Sumin

    강유진, 박지훈, 강성택, 김수민

    Pursuit of Zero Energy Building (ZEB) 3 in Korean mid- and high-rise wood buildings is evaluated using the national energy assessment tool … + READ MORE
    Pursuit of Zero Energy Building (ZEB) 3 in Korean mid- and high-rise wood buildings is evaluated using the national energy assessment tool ECO2, coupling an envelope–climate matrix (four wall assemblies × four climate zones encompassing six regional weather files, with continuous insulation variation) and three stepwise renewable scenarios geothermal; geothermal + rooftop photovoltaics (PV); and geothermal + rooftop PV + building-integrated PV (BIPV). In the coldest zone (Central 1), demand proved highly sensitive to wall thermal transmittance (U-value); elevated loads were driven primarily by the SIP wall_2 (U = 0.213 W/m²·K) exceeding the Central 1 requirement (U ≤ 0.170 W/m²·K). After normalizing all walls to this criterion, performance differences became negligible, while thinner SIP walls retained design/constructability advantages over cross-laminated timber (CLT). For the renewable cases (Daejeon, SIP wall_1), primary energy and self-sufficiency improved from 118.8 kWh/m²·yr, 7.21% (geothermal) to 83.9, 34.49% (geothermal+PV) and 70.0, 45.36% (geothermal+PV+BIPV); none reached ZEB 3 (≥60% self-sufficiency or <50 kWh/m²·yr). Scenarios (2)–(3) did, however, satisfy Renewable Portfolio Standard (RPS) thresholds for 2025 (34%) and 2030 (40%). The findings indicate that additional demand-side reductions, notably high-performance glazing (U ≤ 1.0 W/m²·K; shading coefficient, shading coefficient (SC) 0.25–0.40) and mechanical, electrical, plumbing (MEP) design/control optimization paired with expanded PV/BIPV capacity, are required to realize a practical pathway to ZEB 3. - COLLAPSE
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    30 August 2025

  • Research Article

    Identification and Validation of Causal Structure to Weather Data

    인과구조 식별 및 구조 신뢰성 검정: 기상 데이터 중심으로

    Chu, Han-Gyeong, Kim, Hye-Gi, Kim, Deuk-Woo

    추한경, 김혜기, 김덕우

    To enable rapid analysis of building energy, data-driven approaches—which allow for swift model construction with a minimal number of input variables—are commonly … + READ MORE
    To enable rapid analysis of building energy, data-driven approaches—which allow for swift model construction with a minimal number of input variables—are commonly employed. However, conventional machine learning models primarily focus on correlations among data and often lack sufficient consideration of the causal relationships that drive changes in outcomes. To overcome these limitations, causal inference methods have been introduced to systematically uncover cause-and-effect relationships among variables. Nevertheless, it is impractical for researchers to define all causal relationships solely based on domain knowledge. Therefore, a data-driven approach using causal discovery methods is necessary to identify causal structures directly from the data. In this study, two causal discovery algorithms—PC and FCI—were applied to weather data, and the resulting causal structures were comparatively analyzed. Additionally, two validation methods were proposed to evaluate the statistical reliability of the discovered structures. The analysis showed that both algorithms provided meaningful insights into the causal relationships among variables, and revealed discrepancies between the causal structure designed based on the researcher’s domain knowledge and the structure discovered by the algorithms. Finally, the proposed validation approaches proved effective in confirming the statistical reliability of the discovered structures. - COLLAPSE
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    30 August 2025

  • Research Article

    Optimizing Flush-Out Processes for a Newly Built Daycare Centers Using Simulation

    시뮬레이션을 이용한 신축 어린이집의 플러쉬아웃 최적화에 관한 연구

    Lee, Ki-Yong, Park, Jun-Seok

    이기용, 박준석

    Formaldehyde and volatile organic compounds (VOCs) emitted from finishing materials and paints in newly constructed buildings can contribute to sick building syndrome, … + READ MORE
    Formaldehyde and volatile organic compounds (VOCs) emitted from finishing materials and paints in newly constructed buildings can contribute to sick building syndrome, posing greater health risks to children with underdeveloped immune systems. This study employed the indoor air quality simulation tool CONTAMW to evaluate flush-out effect for formaldehyde and toluene in a nursery room of a newly built daycare center. The simulation results showed that HCHO concentrations were reduced by 10–24%, and toluene by 48.0–78.7%, depending on the flush-out conditions. Moreover, extended flush-out periods with lower air change rates were more effective in reducing pollutant concentrations. These findings offer insights into effective ventilation strategies for preventing symptoms of sick building syndrome and are expected to serve as foundational data for managing indoor air quality in newly built daycare centers, which are not yet subject to mandatory measurement. - COLLAPSE
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    30 August 2025

  • Research Article

    Analysis of Building Heating and Cooling Load Disaggregation using Monthly Energy and Hourly Outdoor Temperature

    월별 에너지와 시간 단위 외기온도 데이터를 이용한 건물 냉난방 부하 분리 분석

    Ahn, Ki-Uhn, Kim, Deuk-Woo, Kim, Hye-Gi

    안기언, 김덕우, 김혜기

    This study introduces a novel data-driven methodology to assess the integrated heating and cooling performance of buildings while simultaneously separating heating, cooling, … + READ MORE
    This study introduces a novel data-driven methodology to assess the integrated heating and cooling performance of buildings while simultaneously separating heating, cooling, and base loads, using only monthly energy consumption and hourly outdoor temperature data. Unlike conventional approaches that require detailed building physical parameters and extensive sub- metering, the proposed method optimizes building-specific base temperatures for both heating and cooling through an R2 maximization process. Using these optimal base temperatures, Heating and Cooling Degree Hours (HDH/CDH) are calculated and aggregated into an Intrinsic Degree Hour (IDH) index, which serves as the sole predictor in a single linear regression model. This model yields two key parameters: a unified performance coefficient, representing the combined responsiveness of the building to both heating and cooling loads, and a base load constant, representing non-weather-dependent energy use. The methodology enables accurate decomposition of monthly energy consumption into its constituent load types, offering a practical, scalable solution for large-scale building stock analysis without detailed building data. - COLLAPSE
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    30 August 2025

  • Research Article

    Intrinsic Degree Hour (IDH) Methodology for Data-Driven Urban Building Energy Modeling (UBEM)

    데이터 기반 도시 건물 에너지 모델링(UBEM)을 위한 Intrinsic Degree Hour (IDH) 방법

    Ahn, Ki-Uhn, Kim, Deuk-Woo, Kim, Hye-Gi

    안기언, 김덕우, 김혜기

    This study proposes a data-driven Urban Building Energy Modeling (UBEM) framework designed to efficiently and reliably assess the energy performance of buildings … + READ MORE
    This study proposes a data-driven Urban Building Energy Modeling (UBEM) framework designed to efficiently and reliably assess the energy performance of buildings at the urban scale. The framework is based on the Intrinsic Degree Hour (IDH) methodology, which utilizes only monthly energy consumption and hourly outdoor temperature data. Building-specific optimal base temperatures for heating and cooling are determined through an R² maximization process, after which degree hours are computed and aggregated into the IDH index. A single linear regression model is then applied to estimate a unified performance coefficient ( U ' ' ), which comprehensively reflects the combined effects of envelope thermal performance, HVAC system efficiency, and operational characteristics, representing the building’s overall responsiveness to climate-sensitive loads. The proposed methodology was applied to 140 buildings participating in Korea’s Green Remodeling (GR) program, and the results show that, on average, the slope of U ' ' decreased after remodeling, indicating improved integrated performance. Furthermore, the IDH analysis module was implemented within a data-driven UBEM platform, enabling large-scale building stock performance evaluation and post-retrofit monitoring. Due to its low data requirements and computational simplicity, the proposed framework offers a practical and scalable tool for diagnosing building performance and supporting energy efficiency policy-making, even in contexts with limited detailed building information. - COLLAPSE
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    30 August 2025
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Journal Informaiton Journal of Korean Institute of Architectural Sustainable Environment and Building Systems Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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