ハステロイC276のデータ駆動型加工パラメータ最適化:PSOおよびTLBOフレームワークを用いた手法
Mosleh M Abualhaj1, B Venkatesh2, Kiran D Parmar3
1Department of Networks and Cybersecurity, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
Scientific reports
|January 15, 2026
まとめ
クライオジェニックCO₂冷却はハステロイC276の加工性を大幅に向上させ、表面粗さと切削力を低減する。粒子群最適化(PSO)のような進化的最適化アルゴリズムは、これらの持続可能な加工戦略をさらに強化する。
背景:
- ハステロイC276は、航空宇宙および化学産業において重要な高性能合金です。
- その優れた特性は、高い強度と加工硬化により、加工上の大きな課題をもたらします。
- 環境負荷を低減するために、持続可能な加工慣行がますます重要になっています。
結論:
- クライオジェニックCO₂支援加工は、ハステロイC276の加工性を向上させるための効果的かつ持続可能な戦略を提供します。
- NMQLは、潤滑性を向上させることで適度な利点をもたらします。
- 進化的最適化アルゴリズムは、困難な合金の最適な加工パラメータを決定するための貴重なツールです。
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