Multi-objective optimization of indoor comfort, contamination, and energy in mixed ventilated buildings using Taguchi and ANOVA methods

The indoor occupant comfort, contamination, and building energy demand depend on the multiple factors that run the mixed-ventilated (MV) buildings. The efforts have been taken to optimize the multi-objective function of the MV building using the Taguchi design and analysis of variance (ANOVA) method. The five independent parameters of the MV building with three levels have been selected for the analysis. Taguchi design method has been employed to reduce the number of cases from 243 (35) to 27 (L27-array). Further, the well-validated numerical model outcomes have been used to analyze and optimize the indoor comfort, contamination and energy using Taguchi and ANOVA methods. The inlet vent height contributes to altering the Particle Residence Time (PRT) by 55.78%, which is higher than ACH in NV buildings. While inlet vent width contributes 47.05% in deciding the Predicted Percentage Dissatisfied (PPD) index for occupants. ACH significantly impacts indoor air velocity with contribution of 64.46%, leading to cold drafts, and contributes 48.38% to energy use. The findings also suggest that a statistical method can optimize indoor comfort factors with 90% confidence, reducing the need for extensive experiments or simulations.