A Study on Optimization of Combustion Chamber Geometry in Large Diesel Engines Using CFD and Machine Learning Analysis of the Optimal Shape that Reflects the Design Intent
数値熱流体計算と機械学習を組み合わせた大型ディーゼルエンジンの燃焼室形状の最適化手法の研究 設計意図を反映した最適形状の解析
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266324
- Paper/Info type
- Proceedings (Autumn)
No.159-26
- Pages
- 1-2(Total 2 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- Japanese
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) 松前 諒大, 2) 松田 知紘, 3) 草鹿 仁 |
|---|---|
| Author(E) | 1) Ryo Matsumae, 2) Tomohiro Matsuda, 3) Jin Kusaka |
| Affiliation(J) | 1) 早稲田大学, 2) 早稲田大学, 3) 早稲田大学 |
| Affiliation(E) | 1) Waseda University, 2) Waseda University, 3) Waseda University |
| Abstract(J) | PSOで最適化した2種の燃焼室形状の筒内現象を解析し，性能向上の要因を調査した．両立型は流速抑制により壁面熱損失を低減し，効率と排出ガス低減を両立した．熱効率特化型は流動強化と燃料噴霧のリップ部衝突により初期燃焼と後期酸化を促進した．PSOの重み設定により，特定の燃焼戦略を実現可能であることを示した． Translation |
| Abstract(E) | This study evaluates the in-cylinder phenomena of two combustion chamber shapes optimized using Particle Swarm Optimization (PSO). For the balanced shape, suppressing excessive flow velocity reduced wall heat loss, achieving both low emissions and high thermal efficiency. In contrast, the efficiency-priority shape enhanced initial combustion and late-stage oxidation through increased turbulence and fuel spray collision with the lip edge. These results provide a physical basis for PSO-optimized designs and demonstrate that specific combustion strategies can be realized by adjusting the weighting factors of the objective functions in the PSO evaluation. |
