Work

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

Year: 2024

Type: article

Abstract: 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.

Source: Applied Sciences

DOI: 10.3390/app142210549

Authors: Minjun Kim, Hyojun Kim, Jinhyun Lee, Younghum Cho

Institution: Yeungnam University

Language: English

Topic: Building Energy and Comfort Optimization

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,728