Commercially available Computational Fluid Dynamics (CFD) software have been applied in indoor environmental design in recent years, but the prediction accuracy depends on an understanding of fluid dynamics fundamentals, in setting appropriate boundary and numerical conditions. This study aims to provide practical modelling information related to prediction accuracy and problematic areas in CFD applications in air conditioning and ventilation, through a series of benchmark tests and reported the results. Six commercial CFD codes were evaluated while two benchmark test cases were performed on isothermal/non-isothermal flow in 2D and 3D room models. The influence of mesh design, and turbulence models showed that using a standard k-ε model on a coarse mesh could provide sufficiently accurate results for practical purposes, by reducing the relaxation coefficient. Evaluation using different CFD programs on a non-isothermal room airflow showed different performances in predicting temperature distributions. The OpenFOAM code showed the closest matching results between three codes tests.
Recent indoor environmental design is requested to create comfortable and safety space in addition to the maximizing the energy conservation performance in buildings. In this point of view, it is important to enhance the prediction accuracy of indoor environmental quality in design stage. Commercial Computational Fluid Dynamics (CFD) software is practically applied in indoor environmental design recent years but the prediction accuracy of CFD simulation depends on the understanding for the fundamentals of fluid dynamics and the setting of appropriate boundary and numerical conditions as well. The series of this study aimed to provide with the practical information such as prediction accuracy and problematic areas related to CFD applications in indoor environment, air conditioning and ventilation, and then performed benchmark tests and reported the results. Especially in this Part 3, benchmark test results for numerical thermal manikins were introduced. SST k-ω model with fine mesh could provide sufficient accurate results and showed good agreement with experimental results.
Commercial Computational Fluid Dynamics (CFD) software is practically applied in indoor environmental design recent years but the prediction accuracy of CFD simulation depends on the understanding for the fundamentals of fluid dynamics and the setting of appropriate boundary and numerical conditions as well. Additionally, deeper understanding to a specific problem regarding indoor environment is also requested. The series of this study aimed to provide with the practical information such as prediction accuracy and problematic areas related to CFD applications in indoor environment, air conditioning and ventilation, then performed benchmark tests and reported the results. In this Part 2, benchmark test results for cross-ventilation airflows and floor heating systems were introduced.
The highest reproducibility of the predicted results compared with the wind tunnel results occurred when the Z0-type wall function was used as the floor-surface boundary condition and the SST k–ω for the turbulence model in case of cross-ventilation flow and SST k–ω model showed also the closest matching results with experiment in case of natural convection in a room with floor heating.
Computational Fluid Dynamics (CFD) has become practical design tool for indoor environment recent years and the application cases have been increasing. Though the improvement of the prediction accuracy of CFD is needed in connection with the upgrade of design quality in indoor environment and Heating, Ventilation and air-conditioning (HVAC) system, the prediction accuracy of CFD simulation depends on the understanding for the fundamentals of fluid dynamics and the setting of appropriate boundary and numerical conditions as well. Additionally, deeper understanding to a specific problem regarding indoor environment is also required. The series of this study aimed to provide with the practical information such as prediction accuracy and problematic areas related to CFD applications in air conditioning and ventilation, then performed benchmark tests and reported the results. Especially in this Part 4, benchmark test results for Air-conditioning airflows, Residential kitchen airflows and Fire-induced flow were introduced and discussed.
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