Air classification of copper granules from recycled electrical cables using a zig-zag separator

Area of Science:

• Metallurgical Engineering
• Materials Science
• Computational Fluid Dynamics

Background:

• Recycling copper electrical power cable scrap is crucial for resource recovery.
• Achieving high purity in recycled copper granules is challenging due to impurities like tin.
• Effective separation methods are needed to enhance the value of recycled copper.

Purpose of the Study:

• To investigate the feasibility of using a zig-zag air classifier for separating tin-contaminated copper granules from pure copper.
• To analyze the separation process using computational fluid dynamics (CFD) simulations.
• To validate the simulation model against experimental results.

Main Methods:

• Numerical computational fluid dynamics (CFD) analyses were performed to simulate the separation process.
• Experimental studies were conducted using a laboratory-scale zig-zag air classifier.
• CFD simulation results were compared with experimental data to validate the model.

Main Results:

• The zig-zag air classifier demonstrated the capability to produce copper granules with a purity exceeding 99% Cu.
• CFD simulations provided insights into the separation dynamics of tin-contaminated copper.
• The study found that the model's error in predicting separation is influenced by the morphology of the copper granules.

Conclusions:

• A zig-zag air classifier is an effective technology for purifying recycled copper electrical power cable scrap.
• CFD modeling, when validated experimentally, can accurately represent the separation process.
• Optimizing the classifier design based on granule morphology can further improve separation efficiency.