Particle shape;
Wear reduction;
Wear deformation;
Convex pattern surface;
DEM;
DISCRETE ELEMENT METHOD;
FLEXIBLE DEM APPROACH;
LINER WEAR;
TUMBLING MILLS;
POWER DRAW;
SHAPE;
GRAINS3D;
DESIGN;
PERFORMANCE;
STRATEGIES;
D O I:
10.1016/j.powtec.2023.119226
中图分类号:
TQ [化学工业];
学科分类号:
0817 ;
摘要:
A convex pattern surface is proposed and optimized to mitigate the sliding wear of bulk handling equipment caused by interaction with bulk solids. This work investigates the effectiveness of the convex pattern surface on wear reduction during interactions with non -spherical particles. Multiple representative particles, obtained through a sampling method, are reconstructed using a photogrammetry technique. Two contact parameters between particles are calibrated through shear box and drawdown tests to ensure flow behavior similar to the real material. The numerical results indicate that the convex pattern surface can effectively reduce wear compared to a plain sample when involving both spherical and non -spherical particles. For a plain sample, the wear volume remains independent of particle shapes and increases linearly with numerical revolutions. For the convex pattern surface, the wear volume demonstrates a quadratic relationship with the test revolutions as the deformation of convex elements weakens the effectiveness of the sample on wear reduction. The particle flow behavior analysis reveals that the convex pattern surface experiences the lowest wear volume when in contact with non -spherical particles. This can be attributed to the non -spherical particles sliding shorter distances and rotating with higher angular velocities on the convex pattern surface.
机构:
Wuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R ChinaWuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R China
Cheng, Xiaoyong
Cao, Zhixian
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机构:
Wuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R ChinaWuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R China
Cao, Zhixian
Li, Ji
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机构:
Swansea Univ, Fac Sci & Engn, Zienkiewicz Ctr Computat Engn, Swansea SA1 8EN, WalesWuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R China
Li, Ji
Borthwick, Alistair
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机构:
Univ Edinburgh, Inst Infrastruct & Environm, Edinburgh EH9 3JL, Scotland
Univ Plymouth, Sch Engn Comp & Math, Plymouth PL4 8AA, EnglandWuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R China
机构:
Vilnius Gediminas Tech Univ, Sauletekio Al 11, LT-10223 Vilnius, Lithuania
Vilnius Univ, Univ G 3, LT-01513 Vilnius, LithuaniaRuhr Univ Bochum, Univ Str 150, D-44780 Bochum, Germany
机构:
School of Energy and Power Engineering, Jiangsu University, Jiangsu, ZhenjiangSchool of Energy and Power Engineering, Jiangsu University, Jiangsu, Zhenjiang
Cao Q.
Kang C.
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机构:
School of Energy and Power Engineering, Jiangsu University, Jiangsu, ZhenjiangSchool of Energy and Power Engineering, Jiangsu University, Jiangsu, Zhenjiang
Kang C.
Teng S.
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h-index: 0
机构:
School of Energy and Power Engineering, Jiangsu University, Jiangsu, ZhenjiangSchool of Energy and Power Engineering, Jiangsu University, Jiangsu, Zhenjiang
Teng S.
Jiao N.
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机构:
704th Research Institute of CSSC, ShanghaiSchool of Energy and Power Engineering, Jiangsu University, Jiangsu, Zhenjiang
Jiao N.
Ding K.
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机构:
704th Research Institute of CSSC, ShanghaiSchool of Energy and Power Engineering, Jiangsu University, Jiangsu, Zhenjiang