A Hybrid Framework of Quantitative Infrared Thermography and BES-Based Optimization for Cost-Optimal Building Envelope Retrofitting

This study integrates in-situ Quantitative Infrared Thermography (QIRT) and Building Energy Simulation (BES) to optimize the energy performance of an existing multi-story residential building in a temperate climate. QIRT was utilized to diagnose thermal anomalies at the interfaces of uninsulated walls, RC skeleton and fenestration junctions, revealing significant thermal bridging and air infiltration while enabling the calculation of the Temperature Index (TI) at critical interfaces. A key finding of the non-destructive diagnostic phase was the discrepancy between in-situ (UINSITU) and theoretical (UCALC) thermal transmittance values, providing an empirical baseline for subsequent optimi-zations. A multi-objective analysis was conducted using genetic algorithms to evaluate 192 retrofit combinations, involving three insulation materials at four thicknesses and 16 glazing types. The impacts on primary energy consumption, CO₂ emissions, and 30-year global costs (per EN 15459-1:2017) were quantified under the volatile economic conditions. Findings indicate that the energy-optimal solution reduces primary energy by 53% and CO₂ emissions by 51%, while the cost-optimal configuration reduces global costs by 52% relative to the reference case. The Pareto analysis reveals a robust convergence between financial and energy efficiency targets, proving that deep retrofitting is an economically imperative strategy for achieving national decarbonization goals and the 2053 net-zero vision.