University library reading spaces face high occupancy and summer cooling demand, making envelope design critical to thermal comfort, energy use, and daylighting. Existing retrofits use uniform window-to-wall ratio (WWR) and shading but seldom consider orientation-dependent photothermal responses or trade-offs between performance preferences and solution suitability. Using northwest-facing Room A and southeast-facing Room D at Hubei University of Technology Library, this study develops a framework integrating measurement-calibrated simulation, orientation-specific multi-objective optimization (MOO), and preference-fit evaluation. Predicted mean vote (PMV) deviation, energy use intensity (EUI), and daylight compliance time were optimized by the non-dominated sorting genetic algorithm II (NSGA-II), followed by entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for scenario-based preference-fit evaluation. West-facing WWR was most sensitive (0.613). PMV–EUI improvement rates were 52.36% and 39.02% for Rooms A and D, respectively. Room D showed strong positive EUI–daylight correlation (r = 0.797), indicating a stronger trade-off. Under PMV–EUI priority, EUI decreased by 4.62% and 3.72%, yielding simulated annual savings of 9.63 and 7.68 MWh and estimated operational carbon reductions of 5.20 and 4.15 tCO2 for Rooms A and D, respectively. Results support differentiated retrofits based on orientation-dependent responses and scenario-specific solution fit.
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Gao et al. (2026) studied this question.
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