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Research Article

Multi-objective optimization of impinging jet ventilation systems: Taguchi-based CFD method

Samira Haghshenaskashani1, Behrang Sajadi1( ), Mathias Cehlin2
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Department of Building, Energy and Environmental Engineering, Faculty of Engineering and Sustainable Development, University of Gävle, Gävle, Sweden
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Abstract

This paper presents a Taguchi method-based approach that can optimize the operating performance of impinging jet ventilation (IJV) systems with limited computational fluid dynamics (CFD) simulation results. The Taguchi optimization calculation finds the best operating design for the weighted overall objective function as a presenter of the multi-objective function problem. The method is used to optimize the operating characteristics of an IJV system considering the factors of supply air temperature, level of the return air vent and percentage of the air exhausted through the ceiling to achieve an overall best performance of thermal comfort, indoor air quality (IAQ) and system energy performance as the objective functions. The study indicates the contribution percentage for each factor in each objective function. The level of the return air vent, the supply air temperature, and the percentage of air exhausted through the ceiling have a contribution of 35.8%, 28.5%, and 35.8% in the objective functions, respectively. Based on the results, the best performance of the IJV system happens when the inlet air temperature is 18 °C, the height of the return air vent is 2 m above the floor, and the percentage of air exhausted through the ceiling is 22.5%.

Keywords

optimizationindoor air qualitythermal comfortenergy performanceimpinging jet ventilation (IJV)Taguchi method

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Building Simulation
Volume 11 Issue 6,
December 2018
Pages 1207-1214
DOI: 10.1007/s12273-018-0450-z
Cite this article:
Haghshenaskashani S, Sajadi B, Cehlin M. Multi-objective optimization of impinging jet ventilation systems: Taguchi-based CFD method. Building Simulation, 2018, 11(6): 1207-1214. https://doi.org/10.1007/s12273-018-0450-z

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Received: 04 December 2017
Revised: 05 April 2018
Accepted: 19 April 2018
Published: 16 May 2018
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018
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