書誌事項
- タイトル別名
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- Wake-Integral Region Estimation Using Deep Learning for Block-Structured Cartesian Mesh.
- Part 1: On the Accuracy of Drag Estimation
- その1:抵抗推算精度について
説明
<p>Cartesian-Mesh CFD solvers have a problem of inaccurate drag force calculation because the grid does not conform to the object. This is attributed to the fact that near-field drag calculations are performed on the surface of the object, which is represented as a staircase. To avoid this problem, the wake integration method, which calculates the drag from the wake region, has been proposed. However, It is not easy to determine the appropriate integration region. In this research, in order to simplify the selection of the wake region in the drag calculation of the Block-Structured Cartesian Mesh using the wake integration method, deep learning was performed using 70 visualized entropy drag image data. As a result, the prediction worked well for some test data. However, we found that further validation is needed to improve a generalization capability of the network model.</p>
収録刊行物
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- 北陸信越支部総会・講演会 講演論文集
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北陸信越支部総会・講演会 講演論文集 2021.58 (0), E011-, 2021
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390289532559211520
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- NII論文ID
- 130008092491
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- ISSN
- 24242772
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可