@article{Ali2026, 
author = {Eslam Ali and Liangzhu Leon Wang and Fuad Baba and Cheng-Chun Lin and Ibrahim Reda and Dahai Qi},
title = {Novel data assimilation-assisted calibrations on high-rise multizone airflow analysis by ensemble Kalman filter and Sobol sensitivity method},
year = {2026},
journal = {Building Simulation},
volume = {19},
number = {7},
pages = {1761-1777},
keywords = {Sobol sensitivity analysis, ensemble Kalman filter, CONTAM, auto-calibration multizone, airflow models},
url = {https://www.sciopen.com/article/10.1007/s12273-026-1458-4},
doi = {10.1007/s12273-026-1458-4},
abstract = {Accurate airflow modeling is essential for understanding airflow patterns and for designing effective ventilation systems. However, calibration of airflow models remains challenging due to complex inter-zonal interactions, limited availability of airflow measurements, and uncertainty in input parameters. Additionally, few studies have focused on multizone airflow calibration. In this study, a novel calibration framework is proposed that combines global sensitivity analysis (GSA) using the Sobol method with the Ensemble Kalman Filter (EnKF) for multizone airflow modeling by CONTAM. A Python tool is developed to perform Sobol analysis, and a Java interface is applied to automate the coupling between simulation and calibration workflows. The framework is applied to a 16-story institutional building where CO2 tracer gas experiments were conducted to characterize both inter-zone and inter-floor airflow behavior. A detailed CONTAM model representing three floors is developed and calibrated using the EnKF approach. GSA is applied to identify the most influential parameters affecting peak CO2 concentrations, enabling a reduction in calibration variables. Results indicate that in the source room, when the air-conditioning (AC) system is turned off, the initial indoor CO2 concentration and generation rate account for 94% of the variance in peak CO2 levels. When the AC is enabled, their contribution decreases to 62%, while the influence of door opening and undercut increases to 25% and 11%, respectively. In adjacent rooms, initial concentration and generation rate also dominate. The EnKF-based calibration substantially improved the prediction accuracy with up to 6% CVRMSE of multizone airflow modeling, achieving reliable agreement with measurements for both room-to-room and floor-to-floor tests.}
}