低炭素建築物における構造・外皮劣化と地域エネルギー需要増幅の連成に対するエネルギー・データ基盤の確率的デジタルツイン枠組み
An Energy-Data-Anchored Probabilistic Digital-Twin Framework for Coupled Structural–Envelope Degradation and Local Energy-Demand Amplification in Low-Carbon Buildings (原題)
Seyed Reza Samaei, ASSED NAKED HADDAD, James Riffat
🤖 gxceed AI 要約
日本語
建物の運用エネルギーと物理的劣化を独立扱いする従来モデルに対し、構造・外皮劣化・熱負荷記憶を連成する確率的デジタルツインを構築。実オフィスビルの2016年時間別電力データで検証しR2=0.933を達成。25年参照シナリオで双方向連成によりライフサイクル電力・炭素が約16%増加し、CSEI指標が17.58年で非負に転じることを示した。
English
A probabilistic digital-twin framework couples structural, envelope-degradation, and thermal-load states in buildings, calibrated on 2016 hourly electricity data from a 12,365 m2 office (R2=0.933). In a 25-year reference scenario, bidirectional coupling raised lifecycle electricity and carbon by 16.7% and 15.8%. A Coupled Structural–Energy Instability Index flags transition onset at ~17.6 years across 5,000 realisations.
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
日本では省エネ法・建築物省エネ法やZEB化、長期修繕計画と脱炭素投資の整合が課題。本枠組みは劣化を織り込んだライフサイクル炭素評価の精緻化に寄与し、不動産・建設のGX投資判断に示唆を与える。
In the global GX context
As ISSB/CSRD push building-level lifecycle emissions into scope, this work argues that degradation-aware energy modelling materially changes reported carbon trajectories. It offers a probabilistic method for transition-risk and retrofit-timing analysis relevant to real-estate decarbonisation and green-building finance.
👥 読者別の含意
🔬研究者:建物ライフサイクル炭素評価に劣化連成を取り込む確率的枠組みとCSEI指標の妥当性検証に関心を持つ研究者に有用。
🏢実務担当者:不動産・建設の脱炭素担当が、外皮劣化を織り込んだ長期エネルギー・炭素予測と改修タイミング検討に活用できる。
🏛政策担当者:建築物の長期省エネ・脱炭素規制や改修政策の評価に、劣化連成を考慮したライフサイクル推計の必要性を示唆。
📄 Abstract（原文）
Long-horizon building-performance models commonly treat operational energy use and physical deterioration as independent processes, despite the potential for envelope degradation to increase thermal demand and for sustained HVAC operation to alter thermal–moisture exposure. This study develops an energy-data-anchored probabilistic digital-twin framework that integrates three coupled lifecycle states: structural/support-condition loss, envelope thermal and leakage loss, and thermal-load memory. A Coupled Structural–Energy Instability Index (CSEI), defined as the spectral abscissa of the frozen local Jacobian, is introduced as a deliberately bounded local modal-transition diagnostic. An autoregressive grey-box observation model was calibrated using 2016 hourly electricity data and independently evaluated one step ahead against the complete 2017 record of a 12,365.4 m2 office building, achieving R2 = 0.933, CV(RMSE) = 6.65%, and NMBE = 0.029%. Within a 25-year, 12,000 m2 reference scenario, bidirectional coupling increased lifecycle electricity consumption and operational carbon emissions by 16.7% and 15.8%, respectively, relative to the energy-decoupled configuration. On the monthly evaluation grid, CSEI first became non-negative at 17.58 years. Across 5,000 parameter–climate realisations, mean lifecycle electricity consumption and carbon emissions were 32.091 GWh and 11.552 ktCO2e, respectively; 98.36% of trajectories crossed the CSEI transition boundary by year 25, with a conditional median onset of 17.67 years. In 100 correctly specified synthetic recovery experiments, median state RMSEs were 0.00205, 0.00121, and 0.00785, and the median absolute onset-reconstruction error was 0.56 years. Collectively, the results provide empirical validation of the energy-observation layer and demonstrate numerical, probabilistic, and inference consistency of the coupled framework. The reported lifecycle trajectories and CSEI onset times remain conditional reference-scenario outputs and should not be interpreted as field-validated deterioration predictions or structural-safety criteria.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.65582/gti.2026.018first seen 2026-10-16 04:57:17
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