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SU Wei, GAO Xiaojun, REN Chuang, LAI Qinghui. A simulation prediction method of suspension speed of seed particle swarm[J]. Journal of South China Agricultural University, 2016, 37(1): 110-116. DOI: 10.7671/j.issn.1001-411X.2016.01.018
Citation: SU Wei, GAO Xiaojun, REN Chuang, LAI Qinghui. A simulation prediction method of suspension speed of seed particle swarm[J]. Journal of South China Agricultural University, 2016, 37(1): 110-116. DOI: 10.7671/j.issn.1001-411X.2016.01.018

A simulation prediction method of suspension speed of seed particle swarm

More Information
  • Received Date: March 07, 2015
  • Available Online: May 17, 2023
  • Objective 

    To stimulate and predict suspension speed of notoginseng seed particle swarm, and to provide a reference for simulating gas-solid two-phase flow.

    Method 

    The suspension speeds of seed particles swarm were surveyed by the PS-20 material floating speed test bed. Bench test were stimulated by coupling discrete element method with computation fluid mechanics, and the influences of seed particle swarm volume fraction on the flow field were stimulated. The suspension speed analog values under different volume fractions were validated using the pulanuofusiji modified formula.

    Result 

    Volume fractions of seed particle swarm had significant effects on flow field. When the particle volume fraction was zero, the seed particle swarm suspension speeds ranged from 7.14 to 9.32 m·s-1 and the mean value was 8.23 m·s-1, while simulation speeds ranged from 7.08 to 9.30 m·s-1 and average of 8.19 m·s-1. When particles volume fractions were 2.58%, 3.87%, 5.16% and 7.74%, the simulation results were 8.52, 8.72, 8.96 and 9.46 m·s-1 respectively, while the theoretical calculated values were 8.53, 8.79, 9.06 and 9.71 m·s-1 respectively with the maximum error of 2.6%.

    Conclusion 

    The particle swarm suspension speed predicted model can be built using stimulated technology when particles volume fraction is below 9.03%. The particle swarm suspension speeds under different volume fractions can be predicted by coupling discrete element method with computation fluid mechanics.

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