Preparation of an Indoor Air Quality Baseline Model for School Retrofitting Using Automated and Semi-Automated Calibrations: The Case Study in South Korea

Abstract

School retrofitting should aim to not only improve its energy performance, but also maintain a good IAQ. An optimal combination of retrofitting measures must be selected by considering the transient state changes of the outdoor and built environments. Although a simulation is an effective platform to evaluate a combination of the retrofitting measure candidates, there is a general lack of practical methods for practitioners to collect the field data and prepare a reliable IAQ baseline model within a project timeline. This study suggests a suite of tools to generate a classroom IAQ baseline, which includes standardized diagnostic scenarios based on common retrofitting practices and measurement protocols of classroom IAQs; the diagnostic scenarios intend to quantify the dilution and filtration capabilities of classrooms through deposition, infiltration, and natural/mechanical ventilations when a high concentration is observed; the first principle model is developed to normalize the measurement, which is fitted against the measurement by adjusting its parameter values. In order to save time and effort for practitioners, automated and semi-automated calibrations that run in a short time are also developed. While the automated calibrations performed better in some cases, the semi-automated calibrations performed better than the automated ones in many cases, the CV-RMSE were smaller, by between −7% and −0.5%. Meanwhile, it took a comparably larger effort and longer time (>1 h for the worst cases) for the heuristic calibrations to have a similar accuracy with the machine-driven calibrations. If the model structure suffers a problem with the measurement, the modeler must intervene in the calibrations. In this case, semi-automation can be a diagnostic tool for a practitioner to intuitively determine from which variables to start the calibration.