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http://dx.doi.org/10.5407/jksv.2022.20.2.021

Prediction of Air Exchange Performance of an Air Purifier by Installation Location using Artificial Neural Network  

Kim, Na Kyong (Department of Mechanical Engineering, Chonnam National University)
Kang, Dong Hee (Department of Mechanical Engineering, Chonnam National University)
Kang, Hyun Wook (Department of Mechanical Engineering, Chonnam National University)
Publication Information
Journal of the Korean Society of Visualization / v.20, no.2, 2022 , pp. 21-27 More about this Journal
Abstract
Air purifiers can be placed where the air cleaning is required, making it easy to manage indoor air quality. The position of the air purifier affects the indoor airflow pattern, resulting in different air cleaning efficiency. Many efforts and strategies have been examined through numerical simulations and experiments to find the proper location of the air purifier, but problems still remain due to the various geometrical indoor spaces and arrangements. Herein, we develop an artificial intelligence model to predict the performance of an air purifier depending on the installation location. To obtain the training data, numerical simulations were performed on the different locations of the air purifiers and airflow patterns. The trained artificial intelligence model predicted the air exchange performance depending on the installation location of the air purifier with a prediction accuracy of 92%.
Keywords
Artificial intelligence; Deep learning; Air purifier; Indoor air quality; Age of air;
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