Akademik Veri Yönetim Sistemi
Journal of Building Physics, 2026 (SCI-Expanded, Scopus)
Building energy simulation is a robust approach for assessing building energy performance, ensuring occupant comfort, and supporting a sustainable built environment. Calibrated simulation models accurately represent the actual performance of new and existing buildings. Yet, research on calibrated simulation models of heritage buildings is limited due to challenges such as a lack of restoration records, difficulties in estimating the physical properties of envelope components after interventions, and restrictions on data collection. The present study addresses these challenges and their implications for simulation accuracy, employing an iterative manual calibration approach to obtain the energy performance simulation model of a heritage building. It integrates empirical field measurements and simulation modeling to develop a validated and reliable energy model. The energy performance of a heritage building in Eskisehir, Turkey, was monitored using temperature, humidity, and occupancy data loggers, as well as on-site U-value measurements. These data were incorporated into DesignBuilder to obtain a baseline simulation model, and the discrepancies between measured and simulated data led to an iterative calibration process. The calibration framework was structured into 8 main steps, comprising 22 adjustment runs, which revised single and incremental parameter integration using Root Mean Square Error (RMSE) and Mean Bias Error (MBE) evaluations against ASHRAE Guideline 14 (2014) benchmarks. The findings highlighted the sensitivities of occupant behavior, building airtightness, and the thermal properties of historic materials in model calibration. Results showed that the baseline model significantly underestimated energy consumption, with an MBE deviation exceeding −24.0% in main zones. The calibrated model obtained through incremental parameter adjustments achieved RMSE and MBE values within ASHRAE benchmarks. Adjustments to U-values reduced prediction errors, highlighting the limitations of relying solely on field measurements or standardized material properties. This study contributes novel insights into heritage building energy modeling, presenting a well-documented iterative calibration approach to enhance simulation reliability.