A coupled electromagnetic-thermal numerical model for predicting disinfection performance in an air-conditioning duct filter microwave disinfection system
Year: 2026
Type: article
Abstract: Microwave disinfection is an efficient, safe, and broad-spectrum physical disinfection technology characterized by strong penetration and selective heating, making it particularly suitable for disinfecting air-conditioning system filters. Currently, numerical tools to predict the disinfection performance of microwave disinfection systems for air-conditioning duct filters are limited. This study proposes a temperature-based approach. First, the temperature rise characteristics of the composite filter in a microwave field are simulated. Then, a relationship model is adopted to link the disinfection rate and temperature during microwave disinfection, predicting the disinfection performance of the system. The accuracy of the developed model is verified through experiments. Results indicate that the coupled electromagnetic-thermal numerical model accurately simulates the temperature rise of the composite filter in a microwave field and predicts disinfection performance. Specifically, with disinfection powers of 600 W and 400 W, the average absolute errors between simulated and measured final steady-state temperatures at measurement points B2, D2 were 1.0 °C, 0.2 °C and 3.4 °C, 1.2 °C, respectively. Based on the simulated and measured temperatures, average absolute errors in predicted disinfection rates were 0.2 %, 0.0 % and 2.3 %, 0.5 % for E. coli , and 0.4 %, 0.0 % and 10.3 %, 1.3 % for S. aureus , respectively. The numerical model provides a robust tool for performance assessment and design optimization of air-conditioning duct filter microwave disinfection systems.
Source: Journal of Building Engineering
Authors: Yuan Zhang, Feifei Wang, Liangwu Wang, Xinhua Xu
Language: English
Subfield: Organic Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,940
Awards: G6165245642, G780129607
OpenAlex ID: W7124856265
