Instability-Constrained Lifecycle Optimisation of Low-Carbon Buildings under Structural–Envelope Degradation and Energy Feedback

Lifecycle retrofit optimisation can favour interventions that perform well in conventional cost–carbon terms while leaving coupled deterioration–energy dynamics insufficiently controlled. This study introduces an instability-constrained lifecycle decision framework that jointly optimises intervention timing, deterioration reset, envelope restoration, and HVAC coefficient-of-performance improvement against expected risk-adjusted lifecycle cost, lifecycle carbon, and the 95% conditional value-at-risk (CVaR95) of cumulative instability exposure. Instability is quantified using a coupled-state eigenvalue indicator (CSEI), which represents positive local modal amplification within the reduced-order deterioration–envelope–energy model and is not a measure of structural failure, code compliance, or physical safety. The framework is demonstrated using a 12,000 m2 office-building reference case anchored to Building Data Genome Project 2 electricity data and evaluated under uncertain degradation and climate conditions using separate training and independent 5,000-scenario out-of-sample evaluation sets. Relative to no intervention, the selected instability-aware strategy reduced expected risk-adjusted lifecycle cost by 23.41%, lifecycle carbon by 6.28%, and mean instability exposure by 99.799%, while persistent instability decreased from 96.38% to 1.60% of scenarios. Cost- and carbon-oriented strategies achieved superior performance in their respective conventional objectives but retained materially greater tail instability, demonstrating that cost and carbon alone do not recover the full lifecycle risk ordering. Across nine deterministic parameter perturbations, the fixed selected package consistently reduced operational carbon and produced no positive nominal CSEI interval through year 25. These findings establish instability-related risk as a distinct and decision-relevant dimension of lifecycle retrofit optimisation, revealing vulnerabilities that conventional cost–carbon assessment can overlook while defining a clear pathway toward monitoring-informed, asset-specific application.