2021 Fiscal Year Final Research Report
Stochastic Model Optimization for Improving the Accuracy and Rapidity of Urban Airflow CFD Simulations
| Project/Area Number |
20K14889
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 23020:Architectural environment and building equipment-related
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| Research Institution | Hiroshima University (2021)
Niigata Institute of Technology (2020) |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2022-03-31
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| Keywords | Urban airflow simulation / Stochastic optimization / Accuracy improvement / CFD / Calibration |
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| Outline of Final Research Achievements |
The computational fluid dynamics (CFD) models based on the Reynold-averaged Navier-Stoke (RANS) turbulence modes are frequently used for urban air simulations because of their low computational cost. However, their accuracy is not so high in the weak wind regions in street canyons. The default values of the RANS’ closure coefficients are adapted from other fields, which are not perfectly suitable for urban airflow simulations. Hence, in this study, a systematic approach was proposed to find the optimum values for the RANS’ closure coefficients by using a novel stochastic optimization method to significantly improve the computational accuracy and rapidity of urban CFD simulations. Different benchmarks, ranging from simple buildings to buildings in an actual city were considered to demonstrate the applicability of the proposed framework.
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| Free Research Field |
wind engineering
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| Academic Significance and Societal Importance of the Research Achievements |
This research results help the CFD users to increase the accuracy of their numerical prediction and finally can improve the reliability of practical designs in urban applications in cities to have more sustainable and safe cities.
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