| Project/Area Number |
17K06167
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Fluid engineering
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| Research Institution | Tokai University |
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Principal Investigator |
Fukuda Kota 東海大学, 工学部, 准教授 (60401684)
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| Co-Investigator(Kenkyū-buntansha) |
野々村 拓 東北大学, 工学研究科, 准教授 (60547967)
高橋 俊 東海大学, 工学部, 准教授 (60553930)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | DNS / 混相乱流 / 高マッハ数 / LESモデル / 混相流 / 直接解析 / 乱流混合 / 騒音 |
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| Outline of Final Research Achievements |
In this study, high-Mach-number and low-Reynolds-number flow around a sphere was numerically calculated by direct numerical simulation (DNS) of the three-dimensional compressible Navier-Stokes equations in order to examine the effect of small particles in high-Mach-number flows. The effects of Mach number, Reynolds number, and temperature ratio on the flow properties, drag coefficient, and Nusselt number were examined from the calculation results. The flow characteristics were cleared and the DNS database was constructed. Furthermore, flow around multiple small particles was calculated by a newly developed numerical method based on Immersed Boundary method. Large scale calculation was carried out with the method, and various information on clustering behavior in the multiphase flow was obtained.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の目的であった高マッハ数固気混相乱流の現象解明を行うためには、これまで計算法や計算機資源の問題で実施できなかった粒子を含めたDNSが必要となる。そこで、本研究ではDNS解析を実施し、現象解明に繋がる多くの知見を得た。
本研究で得られた成果は、ロケット音響問題や爆風の予測問題、高速固気混相燃焼問題など実用問題が多い当該分野における詳細な物理現象の理解に大きく貢献すると考えられる。また、これまでは、実験データに基づき経験的なマクロモデルを構築する手法が採用されてきたが、本研究で明らかとなったミクロレベルでの物理現象は、経験的なマクロレベルの物理現象理解を大幅に向上することが期待できる。
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