Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit
Accurate measurement of air flow rate is essential in automatic building control using the variable air volume (VAV) system. In order to solve the problems of the existing air flow measurement method and improve the accuracy of air flow control, this study developed a data-based multiple regression...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/10/2667 |
| _version_ | 1797567036450144256 |
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| author | Hyo-Jun Kim Ji-Hyun Shin Jae Hun Jo Young-Hum Cho |
| author_facet | Hyo-Jun Kim Ji-Hyun Shin Jae Hun Jo Young-Hum Cho |
| author_sort | Hyo-Jun Kim |
| collection | DOAJ |
| description | Accurate measurement of air flow rate is essential in automatic building control using the variable air volume (VAV) system. In order to solve the problems of the existing air flow measurement method and improve the accuracy of air flow control, this study developed a data-based multiple regression air flow prediction model. The independent variables used in the development of the predictive model were selected as the factors used for control and monitoring when operating with variable air flow rate in the existing air conditioning system. Data collection and correlation between independent variables and air flow rate of the terminal unit were analyzed. Using the IBM SPSS statistics version 25, an air flow rate prediction model was developed using multiple regression analysis. Reliability of model was evaluated by comparing the measured airflow. The relative error of −9.3% to 10.4% is shown when comparing the estimated air flow rate by the developed model with the measured air flow rate. |
| first_indexed | 2024-03-10T19:35:54Z |
| format | Article |
| id | doaj.art-aa19b7c6dc434a54bf3a02a757add539 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T19:35:54Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-aa19b7c6dc434a54bf3a02a757add5392023-11-20T01:43:11ZengMDPI AGEnergies1996-10732020-05-011310266710.3390/en13102667Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal UnitHyo-Jun Kim0Ji-Hyun Shin1Jae Hun Jo2Young-Hum Cho3Department of Architectural Engineering, Graduate School of Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, KoreaDepartment of Architectural Engineering, Graduate School of Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, KoreaDivision of Architecture, Inha University, 100 Inha-ro, Incheon 22212, KoreaSchool of Architecture, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, KoreaAccurate measurement of air flow rate is essential in automatic building control using the variable air volume (VAV) system. In order to solve the problems of the existing air flow measurement method and improve the accuracy of air flow control, this study developed a data-based multiple regression air flow prediction model. The independent variables used in the development of the predictive model were selected as the factors used for control and monitoring when operating with variable air flow rate in the existing air conditioning system. Data collection and correlation between independent variables and air flow rate of the terminal unit were analyzed. Using the IBM SPSS statistics version 25, an air flow rate prediction model was developed using multiple regression analysis. Reliability of model was evaluated by comparing the measured airflow. The relative error of −9.3% to 10.4% is shown when comparing the estimated air flow rate by the developed model with the measured air flow rate.https://www.mdpi.com/1996-1073/13/10/2667variable air volume systemterminal unitprediction modelair flow ratemultiple regression |
| spellingShingle | Hyo-Jun Kim Ji-Hyun Shin Jae Hun Jo Young-Hum Cho Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit Energies variable air volume system terminal unit prediction model air flow rate multiple regression |
| title | Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit |
| title_full | Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit |
| title_fullStr | Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit |
| title_full_unstemmed | Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit |
| title_short | Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit |
| title_sort | development of air flow rate prediction model using multiple regression in vav terminal unit |
| topic | variable air volume system terminal unit prediction model air flow rate multiple regression |
| url | https://www.mdpi.com/1996-1073/13/10/2667 |
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