Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office
Based on the Response Surface Methodology (RSM), the development of first- and second-order models for predicting the Air Diffusion Performance Index (ADPI) in a displacement-ventilated office is presented. By adopting the technique of Computational Fluid Dynamics (CFD), the new ADPI models develope...
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my.uniten.dspace-309412023-12-29T15:56:15Z Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office Ng K.C. Kadirgama K. Ng E.Y.K. 55310814500 12761486500 7201647536 Air Diffusion Performance Index (ADPI) Air ventilation Computational Fluid Dynamics (CFD) Response Surface Methodology (RSM) Thermal comfort Air Diffusion Optimization Software packages Thermal comfort Ventilation Air diffusion Air ventilation Response Surface Methodology (RSM) Computational fluid dynamics Based on the Response Surface Methodology (RSM), the development of first- and second-order models for predicting the Air Diffusion Performance Index (ADPI) in a displacement-ventilated office is presented. By adopting the technique of Computational Fluid Dynamics (CFD), the new ADPI models developed are used to investigate the effect of simultaneous variation of three design variables in a displacement ventilation case, i.e. location of the displacement diffuser (Ldd), supply temperature (T) and exhaust position (Lex) on the comfort parameter ADPI. The RSM analyses are carried out with the aid of a statistical software package MINITAB. In the current study, the separate effect of individual design variable as well as the second-order interactions between these variables, are investigated. Based on the variance analyses of both the first- and second-order RSM models, the most influential design variable is the supply temperature. In addition, it is found that the interactions of supply temperature with other design variables are insignificant, as deduced from the second-order RSM model. The optimised ADPI value is subsequently obtained from the model equations. � 2007 Elsevier B.V. All rights reserved. Final 2023-12-29T07:56:15Z 2023-12-29T07:56:15Z 2008 Article 10.1016/j.enbuild.2007.04.024 2-s2.0-38749147306 https://www.scopus.com/inward/record.uri?eid=2-s2.0-38749147306&doi=10.1016%2fj.enbuild.2007.04.024&partnerID=40&md5=8618e48bdd8d7d320ef55274ebe8c5f8 https://irepository.uniten.edu.my/handle/123456789/30941 40 5 774 781 Scopus |
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Air Diffusion Performance Index (ADPI) Air ventilation Computational Fluid Dynamics (CFD) Response Surface Methodology (RSM) Thermal comfort Air Diffusion Optimization Software packages Thermal comfort Ventilation Air diffusion Air ventilation Response Surface Methodology (RSM) Computational fluid dynamics |
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Air Diffusion Performance Index (ADPI) Air ventilation Computational Fluid Dynamics (CFD) Response Surface Methodology (RSM) Thermal comfort Air Diffusion Optimization Software packages Thermal comfort Ventilation Air diffusion Air ventilation Response Surface Methodology (RSM) Computational fluid dynamics Ng K.C. Kadirgama K. Ng E.Y.K. Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office |
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Based on the Response Surface Methodology (RSM), the development of first- and second-order models for predicting the Air Diffusion Performance Index (ADPI) in a displacement-ventilated office is presented. By adopting the technique of Computational Fluid Dynamics (CFD), the new ADPI models developed are used to investigate the effect of simultaneous variation of three design variables in a displacement ventilation case, i.e. location of the displacement diffuser (Ldd), supply temperature (T) and exhaust position (Lex) on the comfort parameter ADPI. The RSM analyses are carried out with the aid of a statistical software package MINITAB. In the current study, the separate effect of individual design variable as well as the second-order interactions between these variables, are investigated. Based on the variance analyses of both the first- and second-order RSM models, the most influential design variable is the supply temperature. In addition, it is found that the interactions of supply temperature with other design variables are insignificant, as deduced from the second-order RSM model. The optimised ADPI value is subsequently obtained from the model equations. � 2007 Elsevier B.V. All rights reserved. |
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55310814500 |
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55310814500 Ng K.C. Kadirgama K. Ng E.Y.K. |
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Ng K.C. Kadirgama K. Ng E.Y.K. |
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title |
Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office |
title_short |
Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office |
title_full |
Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office |
title_fullStr |
Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office |
title_full_unstemmed |
Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office |
title_sort |
response surface models for cfd predictions of air diffusion performance index in a displacement ventilated office |
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2023 |
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