Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD

The purpose of this study was to determine the annual energy consumption that can be attributed to heating, ventilation, and air conditioning (HVAC) systems’ mixing temperature error. To develop a mixing temperature prediction model for a single-duct variable air volume (VAV) system, the mixing temp...

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Main Authors: Minjun Kim, Hyojun Kim, Jinhyun Lee, Younghum Cho
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/14/22/10549
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author Minjun Kim
Hyojun Kim
Jinhyun Lee
Younghum Cho
author_facet Minjun Kim
Hyojun Kim
Jinhyun Lee
Younghum Cho
author_sort Minjun Kim
collection DOAJ
description The purpose of this study was to determine the annual energy consumption that can be attributed to heating, ventilation, and air conditioning (HVAC) systems’ mixing temperature error. To develop a mixing temperature prediction model for a single-duct variable air volume (VAV) system, the mixing temperature was measured using 15 temperature sensors installed in an HVAC mixing chamber as well as the existing air handling unit’s (AHU) mixing temperature sensor. The mixing chamber was modeled using computational fluid dynamics (CFD), and a coefficient of variation of the root-mean-square error of 7.927% indicated that the model was reliable. Next, CFD simulation cases were formulated, and the temperature distribution of the mixing chamber was analyzed. This revealed that the amount of outdoor airflow input and the change in the temperature distribution of the mixing chamber were directly proportional to each other and that the mixing temperature measurements for the mixing chamber were not accurate. The mixing temperature prediction model was developed through multiple regression analysis and was successfully applied and verified. Compared with the measurements provided by existing mixing temperature sensors, the mixing temperature prediction model indicated an absolute error of 0.008–0.42 °C, confirming the model’s prediction performance.
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id doaj-art-f4b62d97d9884a8885cd29903dd13407
institution Kabale University
issn 2076-3417
language English
publishDate 2024-11-01
publisher MDPI AG
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series Applied Sciences
spelling doaj-art-f4b62d97d9884a8885cd29903dd134072024-11-26T17:49:13ZengMDPI AGApplied Sciences2076-34172024-11-0114221054910.3390/app142210549Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFDMinjun Kim0Hyojun Kim1Jinhyun Lee2Younghum Cho3Department of Architectural Engineering, Graduate School of Yeungnam University, Gyeongsan 38541, Republic of KoreaR&D Center, BETECH, Daegu 41228, Republic of KoreaArchitecture Research Institute, Yeungnam University, Gyeongsan 38541, Republic of KoreaSchool of Architecture, Yeungnam University, Gyeongsan 38541, Republic of KoreaThe purpose of this study was to determine the annual energy consumption that can be attributed to heating, ventilation, and air conditioning (HVAC) systems’ mixing temperature error. To develop a mixing temperature prediction model for a single-duct variable air volume (VAV) system, the mixing temperature was measured using 15 temperature sensors installed in an HVAC mixing chamber as well as the existing air handling unit’s (AHU) mixing temperature sensor. The mixing chamber was modeled using computational fluid dynamics (CFD), and a coefficient of variation of the root-mean-square error of 7.927% indicated that the model was reliable. Next, CFD simulation cases were formulated, and the temperature distribution of the mixing chamber was analyzed. This revealed that the amount of outdoor airflow input and the change in the temperature distribution of the mixing chamber were directly proportional to each other and that the mixing temperature measurements for the mixing chamber were not accurate. The mixing temperature prediction model was developed through multiple regression analysis and was successfully applied and verified. Compared with the measurements provided by existing mixing temperature sensors, the mixing temperature prediction model indicated an absolute error of 0.008–0.42 °C, confirming the model’s prediction performance.https://www.mdpi.com/2076-3417/14/22/10549computational fluid dynamics (CFD)variable air volume (VAV) systemair handling unit (AHU)mixing chambermixing air temperatureprediction model
spellingShingle Minjun Kim
Hyojun Kim
Jinhyun Lee
Younghum Cho
Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
Applied Sciences
computational fluid dynamics (CFD)
variable air volume (VAV) system
air handling unit (AHU)
mixing chamber
mixing air temperature
prediction model
title Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
title_full Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
title_fullStr Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
title_full_unstemmed Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
title_short Development of Mixing Temperature Prediction Model for Single-Duct Variable Air Volume System Using CFD
title_sort development of mixing temperature prediction model for single duct variable air volume system using cfd
topic computational fluid dynamics (CFD)
variable air volume (VAV) system
air handling unit (AHU)
mixing chamber
mixing air temperature
prediction model
url https://www.mdpi.com/2076-3417/14/22/10549
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AT hyojunkim developmentofmixingtemperaturepredictionmodelforsingleductvariableairvolumesystemusingcfd
AT jinhyunlee developmentofmixingtemperaturepredictionmodelforsingleductvariableairvolumesystemusingcfd
AT younghumcho developmentofmixingtemperaturepredictionmodelforsingleductvariableairvolumesystemusingcfd