| Project/Area Number |
22K14332
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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 22040:Hydroengineering-related
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| Research Institution | Kyushu University |
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Principal Investigator |
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| Project Period (FY) |
2022-04-01 – 2023-03-31
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| Project Status |
Discontinued (Fiscal Year 2022)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2023: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2022: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
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| Keywords | THINC / multiphase / volume of fluid / HPC / Machine learning / multiphase flow |
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| Outline of Research at the Start |
Development of a new Computational Fluid Dynamics (CFD) method for modeling violent free surface flow problems. This is accomplished by enhancing the accuracy and efficiency of the interface-capturing approach with machine learning and GPU computing.
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| Outline of Annual Research Achievements |
Preliminary results for a new formula that will replace the currently employed Tangent Hyperbolic function in the THINC VOF scheme utilized for interface capture treatment in multiphase flow have been achieved. The proposed function, unlike the Tangent Hyperbolic function, can be integrated twice, saving computing costs associated with numerical integration. In a subset of test scenarios, the proposed scheme gives results that are comparable to state-of-the-art THINC techniques at around half the computational cost. However, the current results are still limited to Cartesian (Hexahedral mesh) grids, and there are some difficulties in extending the new approach to different types of unstructured grids.
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