Multi-objective optimization of window configuration and furniture arrangement for the natural ventilation of office buildings using Taguchi-based grey relational analysis
Abstract
Natural window ventilation plays a key role in energy-efficient building design to achieve the Sustainable Development Goal 11. However, window ventilation effectiveness has often been overestimated in past studies because indoor obstacles were not considered. This study investigated the improvement of natural window ventilation efficiency for an office room in a humid subtropical climate area. Various design parameters were simultaneously investigated, including the window type, opening percentage, position, and furniture arrangement, with several factor levels. The Taguchi method provided quantitative data from an L27 orthogonal array, so the effects of these variables on multiple objectives such as the air change rate and ventilation efficiency were determined and ranked. The signal-to-noise ratio calculations further confirmed the relevant importance of examined parameters, and the percentage contribution of each parameter was defined by analysis of variance (ANOVA). Additionally, grey relational analysis (GRA) based on grey system theory was used to determine the multiple-optimization design. A confirmation test showed that the optimal combination case enhanced the room air change rate (ACR) and air exchange efficiency (AEE) by up to 0.00293 s-1 and 1.09%, respectively.
- Publication:
-
Energy and Buildings
- Pub Date:
- October 2023
- DOI:
- 10.1016/j.enbuild.2023.113385
- Bibcode:
- 2023EneBu.29613385Y
- Keywords:
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- Natural ventilation;
- Window;
- Furniture layout;
- Computational fluid dynamics;
- Taguchi method;
- Grey relational analysis