## 1 Introduction
### Buildings Leakage Evaluation
Additionally, [PERSON] [30] collected a database of the airtightness performance, measured through the blower door test, in 58 residential buildings built from 1912 to 2013 and analyzed this data to develop a predictive model for airtightness performance based on window characteristics. These studies required large databases for model  
Figure 1: Blower door test. Figure 2: Air-handling unit (AHU) system of a test bed. development and did not consider changing airflow as a predictor of the airtightness values in the building envelope. [PERSON] [31] developed a model to predict air infiltration in single-zone buildings with high airtightness through experimental methods. The results revealed the higher accuracy of the proposed model in predicting air infiltration compared to existing models, effectively using the building airtightness and pressure difference as key variables to predict air infiltration rates in high airtightness buildings. These studies built models based on region-specific data, but because they are static models, they are limited in their ability to reflect real-time variability over time. Therefore, it is necessary to install pressure sensors to continuously monitor the indoor-outdoor pressure difference to estimate the actual leakage airflow rate in real time. The location of the building exterior wall pressure sensors that measure the indoor-outdoor pressure difference affects the measurement uncertainty; thus, it is recommended to install them in areas where drafts occur or away from other buildings or obstacles [32; 33]. However, it is difficult to find such spaces in urban buildings; moreover, there are physical and economic limitations to permanently installing pressure sensors on every exterior wall or space in an operating building. Therefore, it is necessary to consider alternatives to pressure sensors during the operational phase of a building. Another author, [PERSON] [34], predicted air leakage based on pressure fields. By analyzing pressure fields, the paper aimed to complement traditional leakage estimation methods, which are only measured at fixed pressure differences. Specifically, airflow and leakage paths were analyzed and predicted by directly measuring the pressure field distribution inside the building. By measuring the internal and external pressure fields of the building and tracing the leakage paths, the study contributed to our understanding of the leakage structure of complex buildings. However, while previous research has mainly focused on analyzing the relationship between pressure fields and leakage paths, it has been limited in utilizing real-time airflow data generated by mechanical systems such as air conditioning systems. Therefore, these existing studies do not reflect the instantaneous airflow changes in various environmental conditions and need to be supplemented for real-time monitoring and prediction. Variable air volume (VAV) systems, one of the air conditioning systems found in buildings, regulate the indoor environment by changing the supply airflow according to the indoor load. Using the supply and return air volumes of the air conditioning system to predict leakage actually contributes to the prediction of airflow in a building. This goes beyond simply predicting leakage and offers the potential to manage and optimize leakage in the future through a direct linkage with the HVAC system. This study aims to utilize the supply and return of an air conditioning system as a means to predict the leakage of a building during building operation and verify it through experiments. For this purpose, a university laboratory with a VAV system was selected as the test bed, and the relationship between the airflow of the VAV system and the indoor-outdoor pressure difference was analyzed through experiments.