10.1007/s40095-021-00412-1

Numerical study and optimization of air-conditioning systems grilles used in indoor environments

  • Luis Angeles-Rodríguez1,
  • Cesar Celis*2,
  1. Faculty of Mechanical Engineering, Graduate School, Universidad Nacional de Ingeniería (UNI), Lima, 15333, PE
  2. Mechanical Engineering Section, Pontificia Universidad Católica del Perú (PUCP), Lima, Lima 32, PE

Published in Issue 2021-07-18

How to Cite

Angeles-Rodríguez, L., & Celis, C. (2021). Numerical study and optimization of air-conditioning systems grilles used in indoor environments. International Journal of Energy and Environmental Engineering, 12(4 (December 2021). https://doi.org/10.1007/s40095-021-00412-1
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Abstract

Abstract The air flow distribution characterizing conditioned indoor environments obtained following conventional design methodologies does not always guarantee both thermal comfort and indoor air quality (IAQ) for all occupants. This occurs because this air flow distribution depends on factors such as the air supply conditions, the grilles and diffusers position/size, and the environmental conditions. Accordingly, the aim of this work is to numerically study the influence of the air supply conditions and the positioning and size of air-conditioning system grilles on the thermal comfort and IAQ in indoor environments. For this purpose, an optimization scheme involving genetic algorithms and computational fluid dynamics techniques has been initially developed. Three objective functions have been next separately optimized, predicted mean vote—predicted percentage dissatisfied (PMV-PPD), percentage of dissatisfied due to draft (PD) and air change effectiveness (ACE). The optimal indoor environment configuration based on the PPD produces the best results in terms of thermal comfort (PPD = 6.6%, PD = 18.7%) indexes. This configuration also features the second lowest energy consumption (774 W). Furthermore, the configuration based on the ACE both presents PMV (≤ − 1.3) and PD (≥ 20%) values ​​far from the acceptability criteria given by the standards, and involves the highest energy consumption (1832 W). Notice that the optimization of thermal comfort indexes implies indirectly optimizing the related systems energy demand as well. When using indexes such as PPD and PD as the optimization objective functions indeed, the total energy consumption is also reduced.

Keywords

  • Indoor thermal environment,
  • HVAC environment,
  • IAQ,
  • Thermal comfort,
  • CFD

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