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新しいインテリジェント・フレームワークを用いて太陽エネルギー変換と貯蔵のためのMXeneグラフェンベースの液体の最適化

Mohamed Bechir Ben Hamida1, Ali Basem2, Ala Eldin A Awouda3

  • 1Engineering Sciences Research Center (ESRC), Deanship of Scientific Research, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.

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まとめ

グラフェン/MXeneナノ流体を太陽エネルギーに最適化することで 効率が向上しました ハイブリッドフレームワークは熱伝導性と動的粘度を正確に高め,太陽光アプリケーションのコストを削減します.

キーワード:
エネルギー効率グラフェンMXene について多目的の最適化応答表面の方法論太陽光発電

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科学分野:

  • 材料科学
  • ナノテクノロジー
  • 再生可能エネルギー

背景:

  • グラフェン/MXeneベースの液体は太陽エネルギーシステムの可能性を秘めています
  • 熱物理学的性質を最適化することは 複雑です
  • 熱伝導性 (TC) と動的粘度 (DV) を向上させることが重要です.

研究 の 目的:

  • グラフェン/MXeneナノ流体特性を最適化するためのハイブリッドフレームワークを開発する.
  • 太陽光発電の熱伝導性 (TC) と動的粘度 (DV) を向上させる.
  • 費用対効果の高い正確な方法論を提供すること

主な方法:

  • 予測モデリングのための応答表面方法論 (RSM).
  • ヒューリスティックおよびメタヒューリスティック最適化アルゴリズム (EHC,NSGA-II,MOALO).
  • 意思決定のテクニック (望ましい機能,VIKOR)

主要な成果:

  • RSMモデルは高い精度を示した (R2 > 0.998).
  • 最適な条件は ~60°C,MFの1.5~2%の重量,MXeneの0.47-0.5の比率である.
  • 意思決定の分析は,重量分布に基づくTC/DVのトレードオフを明らかにした.

結論:

  • ハイブリッドフレームワークは ナノ流体の性質を効果的に最適化します
  • 最適なMXene比率は,質量分数と温度に依存しています.
  • このアプローチは,太陽エネルギーアプリケーションの計算と実験室コストを削減します.