2023ICERD8-C12 -- Inverse Uncertainty Analysis to Compute Indeterministic Building Design Parameters Based on Detailed Energy Monitoring Measurements in Hot Climates

This study employs the inverse uncertainty analysis method to identify uncertain parameters based on comprehensive monitored data. The method allows for the prediction of various indeterminate design parameters, including thermal bridges, system performance, and infiltration. By integrating previous study findings and expert knowledge, the range of uncertain parameters is accurately defined. The research procedure involves measuring deterministic design parameters such as lighting, equipment, hot water boiler, and air-conditioning system using energy meters. A building energy model representing the studied house is calibrated against the measured data. Range values of undetermined design parameters related to envelope, fenestration and air-conditioning performances, and infiltration rate are defined. The significant influence of the undetermined design parameters is then obtained using inverse uncertainty analysis. The analysis indicated that infiltration has the most significant influence, with a preferred value of around 2.0 air-changes per hour (ACH). The thermal bridge in the external wall and floor plays a crucial role and must be not simplified during building energy model. The glazing type has minimal impact, fluctuating among possible solutions. The coefficient of performance (COP) of the air-conditioning system averages was around 2.5, indicating its efficiency was not degraded much from the installed capacity performance. The roof thermal bridge showed minimal effects unlike thermal bridge impact of the external wall. The adjusted indeterministic design parameters improved the calibration of the energy model to show less than a 2% difference from the actual measurement.