Study of multi-objective optimization of overall ventilation performance for an impinging jet ventilation system using Taguchi-based grey relational analysis

Abstract

Impinging jet ventilation (IJV) system is believed to combines the advantages of good indoor air quality (IAQ) and high energy efficiency. However, there is few study about the optimization of multiple performance characteristics and the significance of design variables on the ventilation performance is not clear for IJV. This study addresses an approach based on Taguchi method with grey relational analysis for optimizing an IJV system with multiple performance characteristics (including draught discomfort (PD), temperature difference between the head and ankle level (ΔT), air change efficiency (ACE) and energy utilization coefficient (EUC)). The supply inlet height, supply velocity, supply temperature and return outlet height are selected as factors that affecting the ventilation performance of IJV and L9 (43) orthogonal array is employed to design the experiments. First, the optimal combinations for PD, ΔT, ACE and EUC are determined separately by Taguchi method coupled with numerical simulations and the significance of the studied factors in promoting each evaluation index is revealed and ranked through main effect analysis and ANOVA. Second, the optimal combination of design variables corresponding to the best overall performance for IJV is determined by converting multi-objective into a single-objective according to Taguchi-based grey relational analysis. Then the important factors influencing the overall performance is ranked and the heights of supply inlet and return device are found to be significant factors in improving the overall performance. Finally, a confirmatory test is conducted to verify the improvement of performance characteristics and satisfactory results are obtained.