An Energy-Data-Anchored Probabilistic Digital-Twin Framework for Coupled Structural–Envelope Degradation and Local Energy-Demand Amplification in Low-Carbon Buildings

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.

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Publication Details

Journal
Green Technology & Innovation
Published
2026-10-14
DOI
https://doi.org/10.65582/gti.2026.018
Primary Topic
Building Energy and Comfort Optimization
Type
article
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article

An Energy-Data-Anchored Probabilistic Digital-Twin Framework for Coupled Structural–Envelope Degradation and Local Energy-Demand Amplification in Low-Carbon Buildings

ASSED NAKED HADDAD, Seyed Reza Samaei, James Riffat
Green Technology & Innovation
Building Energy and Comfort Optimization
article

An Energy-Data-Anchored Probabilistic Digital-Twin Framework for Coupled Structural–Envelope Degradation and Local Energy-Demand Amplification in Low-Carbon Buildings

ASSED NAKED HADDAD, Seyed Reza Samaei, James Riffat
article en

Abstract

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.

Green Technology & InnovationVol. 2
Universidade Federal do Rio de Janeiro (BR), World Society of Sustainable Energy Technologies (GB)
Climate action, Affordable and clean energy, Sustainable cities and communities, Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Building Energy and Comfort Optimization
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