地下スーパーマーケットにおけるエネルギー使用・熱的快適性・炭素排出の多目的最適化
Multi-Objective Optimization of Energy Use, Thermal Comfort, and Carbon Emissions in an Underground Supermarket (原題)
Zhongcheng Duan, Pengju Li, Dongdong Zhu
🤖 gxceed AI 要約
日本語
中国徐州の地下スーパーマーケットを対象に、エネルギー使用強度・在室時不快時間比率・炭素排出（資材A1–A3および運用B6）の三目的を同時最適化した研究。2000件のラテン超方格サンプリングとRhino-Grasshopper/Ladybug-Honeybee、BPニューラルネットワーク代理モデル、Morris感度分析、NSGA-III、エントロピー重み付きTOPSISを組み合わせた。妥協解はEUIを50.9%、炭素排出を44.6%削減し、DTRを49.29%から23.96%に低減した。外壁断熱厚がEUIとDTRに、屋根断熱厚が炭素性能に最も強く影響した。
English
This study optimizes energy use, thermal comfort, and carbon emissions for an underground supermarket in Xuzhou, China. Using 2000 Latin hypercube samples, a Rhino-Grasshopper/Ladybug-Honeybee workflow, BP neural-network surrogates, Morris sensitivity analysis, NSGA-III, and entropy-weight TOPSIS, the compromise solution cut EUI by 50.9% and carbon emissions by 44.6%, while reducing discomfort time ratio from 49.29% to 23.96%. External-wall insulation thickness most influenced EUI and DTR, while roof insulation thickness most affected carbon performance.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のGX文脈では、商業建築物の省エネ・脱炭素改修はScope 1/2削減やZEB化目標に直結する。特に地下空間という特殊条件下での多目的最適化手法は、都市部の再開発や既存ストック活用における炭素削減戦略に示唆を与える。
In the global GX context
Globally, this work contributes to building decarbonization literature by integrating embodied and operational carbon in retrofit optimization for underground commercial spaces. It aligns with ISSB/TCFD disclosure of Scope 1/2 emissions and supports science-based targets for real estate portfolios.
👥 読者別の含意
🔬研究者:多目的最適化と機械学習代理モデルを組み合わせた建築脱炭素研究の手法として参考になる。
🏢実務担当者:地下商業施設の改修において、断熱材厚の選択が炭素排出と快適性のトレードオフを生むことを示唆。
🏛政策担当者:建築物の省エネ基準や炭素排出規制を設計する際、地下空間特有の負荷特性を考慮する必要性を示す。
📄 Abstract（原文）
Underground supermarkets are characterized by high occupant density, long operating hours, and substantial internal loads, creating competing demands for energy efficiency, thermal comfort, and carbon reduction. This study investigates the coordinated optimization of these performance objectives for a single-level underground supermarket in Xuzhou, China. Energy use intensity (EUI), occupied-hour discomfort time ratio (DTR), and carbon emissions from retrofit-material production (A1–A3) and operational energy use (B6) were adopted as objectives. Eleven envelope, overburden, morphology, and operational variables were evaluated using 2000 Latin hypercube samples through a Rhino-Grasshopper/Ladybug Tools-Honeybee workflow. Independent back-propagation neural-network surrogate models were combined with Morris sensitivity analysis and NSGA-III, and entropy-weight TOPSIS was used to rank Pareto solutions. The selected compromise solution reduced EUI by 50.9% and carbon emissions by 44.6%, while decreasing DTR from 49.29% to 23.96% relative to the baseline. External-wall insulation thickness had the strongest influence on EUI and DTR, whereas roof insulation thickness most strongly affected carbon performance because of the trade-off between operational energy savings and material-related emissions. These results demonstrate the need for coordinated envelope and operational strategies when balancing energy, comfort, and carbon performance in underground commercial buildings.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/en19194642first seen 2026-10-03 05:01:54
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