Modeling Supply Air Jet of Split Air Conditioner Based on Abramovich Jet Theory and Bayesian Markov Chain Monte Carlo Algorithm

Abstract

Aim: This study aims to develop supply air jet models for split air conditioners. Background: Designing and operating an air conditioning system based on the unique characteristics of the supply air jet is essential to control the draft risk. Motivation: Due to the distinct differences in air supply characteristics of the split air conditioners caused by the intermittent operation and the complex design of supply air outlets, the existing supply air jet models designed for central air conditioning systems are unsuitable for split air conditioners. Significant results: In this study, models for the trajectory position, velocity, and temperature of the supply air jet for split air conditioners are established based on the Abramovich jet theory and Bayesian Markov Chain Monte Carlo (MCMC) algorithm. The effectiveness of the proposed models is demonstrated via comparison with the training dataset from the experimentally validated Computational Fluid Dynamics simulation of a split air conditioner. For the model testing dataset, the RMSEs of trajectory position, velocity, and temperature are 0.01 m, 0.09 m/s, and 0.09 °C, respectively, with a low supply air velocity and 0.01 m, 0.25 m/s, and 0.03 °C with a high supply air velocity. The proposed models of velocity and temperature of the supply air jet are general for various supply air conditions, while coefficients in the trajectory position model of the supply air jet need to be recalibrated with the proposed Bayesian MCMC algorithm for different supply air conditions. The proposed models provide valuable guidance for the operation of split air conditioners.