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A platform for research: civil engineering, architecture and urbanism
The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings
https://orcid.org/0000-0002-2432-964X
Abstract We present a method that can be used to optimize CFD analyses of ventilation performance in buildings; the method was successfully applied in other disciplines. In the method, three statistical methods are used - the Taguchi method, ANOVA, and Grey Relational Analysis (GRA) to achieve optimization. We then model the risk of draft and the mean age of air in a two-dimensional benchmark test case to exemplify the application of the method. We use five independent variables for modeling: temperature, air velocity, and three room dimensions, each with five levels. In short, the method is implemented as follows: At first, using an L25 orthogonal array in the Taguchi method, we decreased the total number of cases to be modeled from 3125 (55) to 25. Then, we modeled the 25 cases with CFD and used the Taguchi method and ANOVA analyses to find the best solutions for draught risk or the age of air, while with the GRA method we found the best solution for both of them considered jointly. Finally, new CFD models for the variables describing the best solutions were run to confirm their superiority within the 25 cases selected for modeling within the orthogonal L25 array. They were not compared against all possible 3125 cases because the computational time would have been prohibitive. Nevertheless, we believe, that the results are credible in identifying the best solutions. This is based on experience in other disciplines. We, therefore, propose that the presented method is considered when complex problems are analyzed related to ventilation performance requiring large computational power.
Highlights It is confirmed that Taguchi, ANOVA and GRA methods are useful for numerical indoor ventilation studies. It is possible to find optimum solutions for the same set of parameters even if the resulting functions are found to have different sensitivity to the parameters examined. The data that can be obtained from the results of a large number of cases (3125) that are not feasible to solve was obtained with a low error level despite the significantly reduced number of cases (25). Although the mathematical relationship between the investigated parameters and the resulting functions is not known, it has been shown that the optimization can be done successfully.
The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings
https://orcid.org/0000-0002-2432-964X
Abstract We present a method that can be used to optimize CFD analyses of ventilation performance in buildings; the method was successfully applied in other disciplines. In the method, three statistical methods are used - the Taguchi method, ANOVA, and Grey Relational Analysis (GRA) to achieve optimization. We then model the risk of draft and the mean age of air in a two-dimensional benchmark test case to exemplify the application of the method. We use five independent variables for modeling: temperature, air velocity, and three room dimensions, each with five levels. In short, the method is implemented as follows: At first, using an L25 orthogonal array in the Taguchi method, we decreased the total number of cases to be modeled from 3125 (55) to 25. Then, we modeled the 25 cases with CFD and used the Taguchi method and ANOVA analyses to find the best solutions for draught risk or the age of air, while with the GRA method we found the best solution for both of them considered jointly. Finally, new CFD models for the variables describing the best solutions were run to confirm their superiority within the 25 cases selected for modeling within the orthogonal L25 array. They were not compared against all possible 3125 cases because the computational time would have been prohibitive. Nevertheless, we believe, that the results are credible in identifying the best solutions. This is based on experience in other disciplines. We, therefore, propose that the presented method is considered when complex problems are analyzed related to ventilation performance requiring large computational power.
Highlights It is confirmed that Taguchi, ANOVA and GRA methods are useful for numerical indoor ventilation studies. It is possible to find optimum solutions for the same set of parameters even if the resulting functions are found to have different sensitivity to the parameters examined. The data that can be obtained from the results of a large number of cases (3125) that are not feasible to solve was obtained with a low error level despite the significantly reduced number of cases (25). Although the mathematical relationship between the investigated parameters and the resulting functions is not known, it has been shown that the optimization can be done successfully.
The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings
https://orcid.org/0000-0002-2432-964X
Abstract We present a method that can be used to optimize CFD analyses of ventilation performance in buildings; the method was successfully applied in other disciplines. In the method, three statistical methods are used - the Taguchi method, ANOVA, and Grey Relational Analysis (GRA) to achieve optimization. We then model the risk of draft and the mean age of air in a two-dimensional benchmark test case to exemplify the application of the method. We use five independent variables for modeling: temperature, air velocity, and three room dimensions, each with five levels. In short, the method is implemented as follows: At first, using an L25 orthogonal array in the Taguchi method, we decreased the total number of cases to be modeled from 3125 (55) to 25. Then, we modeled the 25 cases with CFD and used the Taguchi method and ANOVA analyses to find the best solutions for draught risk or the age of air, while with the GRA method we found the best solution for both of them considered jointly. Finally, new CFD models for the variables describing the best solutions were run to confirm their superiority within the 25 cases selected for modeling within the orthogonal L25 array. They were not compared against all possible 3125 cases because the computational time would have been prohibitive. Nevertheless, we believe, that the results are credible in identifying the best solutions. This is based on experience in other disciplines. We, therefore, propose that the presented method is considered when complex problems are analyzed related to ventilation performance requiring large computational power.
Highlights It is confirmed that Taguchi, ANOVA and GRA methods are useful for numerical indoor ventilation studies. It is possible to find optimum solutions for the same set of parameters even if the resulting functions are found to have different sensitivity to the parameters examined. The data that can be obtained from the results of a large number of cases (3125) that are not feasible to solve was obtained with a low error level despite the significantly reduced number of cases (25). Although the mathematical relationship between the investigated parameters and the resulting functions is not known, it has been shown that the optimization can be done successfully.
The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings
Yuce, Bahadir Erman (author) / Nielsen, Peter Vilhelm (author) / Wargocki, Pawel (author)
Building and Environment ; 225
2022-09-06
Article (Journal)
Electronic Resource
English
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