Chemical Engineering
基于CFD-DEM-ML和多尺度决策的搅拌槽稀土浸出能效-质量优化
Energy-efficiency-quality optimization of REE leaching in stirred tank based on CFD-DEM-ML and multiscale decision-makingA multiscale decision-making framework integrating Computational Fluid Dynamics (CFD), Discrete Element Method (DEM), and Machine Learning (ML) to optimize the leaching process of Rare Earth Elements (REE) in stirred tanks, balancing energy efficiency and product quality. / 一种集成计算流体动力学(CFD)、离散元法(DEM)和机器学习(ML)的多尺度决策框架，用于优化搅拌槽中稀土元素的浸出过程，平衡能效与产品质量。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-01 16:06:09
Sub-knowledge points
CFD-DEM-ML couplingMultiscale decision-makingREE leaching processStirred tank reactor optimization
Higher-order knowledge points
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Main parameters and performance indicators
CFD-DEM-ML: Integrated simulation and optimization methodologyMultiscale decision-making: Hierarchical optimization strategyREE leaching: Rare Earth Element extraction processStirred tank: Reactor vessel typeEnergy-efficiency-quality: Dual optimization objectives
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Related literature
ranked by community starsEnergy-efficiency-quality optimization of REE leaching in stirred tank based on CFD-DEM-ML and multiscale decision-makingOpen source
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1 recordsRecord title: Energy-efficiency-quality optimization of REE leaching in stirred tank based on CFD-DEM-ML and multiscale decision-making.
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