Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection
Because of the recent COVID-19 pandemic, the problem of preventing and containing the diffusion of pathogens spread through air has become a main topic of research. The problem is particularly important for specific environments, such as dental or other medical practices, where the aerosol treatment...
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MDPI AG
2024-10-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/21/9901 |
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| author | Igor Carli Carlo Poloni Alberto Clarich Rosario Russo |
| author_facet | Igor Carli Carlo Poloni Alberto Clarich Rosario Russo |
| author_sort | Igor Carli |
| collection | DOAJ |
| description | Because of the recent COVID-19 pandemic, the problem of preventing and containing the diffusion of pathogens spread through air has become a main topic of research. The problem is particularly important for specific environments, such as dental or other medical practices, where the aerosol treatments in open-mouth patients, combined with closed and crowded rooms, raise the risk of infection. As an efficient countermeasure, in this study we propose a solution that is able to remove the risk at the source, through the aspiration of the aerosol and the neutralization of the bacterial load by means of a UV-C LED filter, which releases the sterilized air in the environment. To maximize the efficiency of the solution, in this study we performed a numerical multi-disciplinary optimization (MDO) of the filter, coupling numerical simulations of multiple disciplines (CFD and electromagnetics) by the process automation and optimization environment modeFRONTIER of ESTECO. Geometrical parameters of the filter are updated for each candidate solution proposed by the optimization algorithm, and their performance in terms of viral neutralization efficiency and air mass flow rate are evaluated by the simulations, until the optimal solution is found. The methodology and results of the study are presented. |
| format | Article |
| id | doaj-art-cfd5d96fdddc4bff9767caec43e73e5f |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-cfd5d96fdddc4bff9767caec43e73e5f2024-11-08T14:33:45ZengMDPI AGApplied Sciences2076-34172024-10-011421990110.3390/app14219901Multi-Disciplinary Optimization of UV-C Filter for Air DisinfectionIgor Carli0Carlo Poloni1Alberto Clarich2Rosario Russo3Department of Engineering and Architecture, University of Trieste, 34100 Trieste, ItalyDepartment of Engineering and Architecture, University of Trieste, 34100 Trieste, ItalyEsteco SpA, 34149 Trieste, ItalyEsteco SpA, 34149 Trieste, ItalyBecause of the recent COVID-19 pandemic, the problem of preventing and containing the diffusion of pathogens spread through air has become a main topic of research. The problem is particularly important for specific environments, such as dental or other medical practices, where the aerosol treatments in open-mouth patients, combined with closed and crowded rooms, raise the risk of infection. As an efficient countermeasure, in this study we propose a solution that is able to remove the risk at the source, through the aspiration of the aerosol and the neutralization of the bacterial load by means of a UV-C LED filter, which releases the sterilized air in the environment. To maximize the efficiency of the solution, in this study we performed a numerical multi-disciplinary optimization (MDO) of the filter, coupling numerical simulations of multiple disciplines (CFD and electromagnetics) by the process automation and optimization environment modeFRONTIER of ESTECO. Geometrical parameters of the filter are updated for each candidate solution proposed by the optimization algorithm, and their performance in terms of viral neutralization efficiency and air mass flow rate are evaluated by the simulations, until the optimal solution is found. The methodology and results of the study are presented.https://www.mdpi.com/2076-3417/14/21/9901optimizationCFDray tracing simulationUV-C filterair pathogens neutralization |
| spellingShingle | Igor Carli Carlo Poloni Alberto Clarich Rosario Russo Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection Applied Sciences optimization CFD ray tracing simulation UV-C filter air pathogens neutralization |
| title | Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection |
| title_full | Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection |
| title_fullStr | Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection |
| title_full_unstemmed | Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection |
| title_short | Multi-Disciplinary Optimization of UV-C Filter for Air Disinfection |
| title_sort | multi disciplinary optimization of uv c filter for air disinfection |
| topic | optimization CFD ray tracing simulation UV-C filter air pathogens neutralization |
| url | https://www.mdpi.com/2076-3417/14/21/9901 |
| work_keys_str_mv | AT igorcarli multidisciplinaryoptimizationofuvcfilterforairdisinfection AT carlopoloni multidisciplinaryoptimizationofuvcfilterforairdisinfection AT albertoclarich multidisciplinaryoptimizationofuvcfilterforairdisinfection AT rosariorusso multidisciplinaryoptimizationofuvcfilterforairdisinfection |