Surface wear reduction of bulk solids handling equipment using bionic design

Guangming Chen

Research output: ThesisDissertation (TU Delft)

47 Downloads (Pure)


Bulk solids handling continues to play an important role in a number of industries. One of the issues during bulk solids handling processes is equipment surface wear. Wear results in high economic loss and increases downtime. Current wear reduction methods such as optimizing transfer conditions or using wear-resistant materials, have brought notable progress. Nevertheless, the wear loss is still significant. Therefore, new solutions for reducing the surface wear must be investigated.
Because wear also occurs to the surfaces of many biological organisms, inspirations for wear reduction can be obtained from biology. In this research, the bionic design method is explored to reduce the surface wear of bulk solids handling equipment.
This thesis firstly illustrates the analytical wear models in bulks solids handling. Hence, the wear phenomena in biology are investigated. Based on the analogies between biology and bulk solids handling, a bionic design method for wear reduction of bulk solids handling equipment surfaces is developed. Furthermore, two bionic models for reducing abrasive and erosive wear respectively, are proposed for the applications of bulk solids handling equipment surfaces.
To model the effects of applying bionic models on the surface wear of bulk solids handling equipment, the discrete element method (DEM) is utilized. Using the parameter values obtained from experiments, the wear of bionic surfaces and conventional smooth surfaces is successfully modeled.
By comparing predicted wear loss from bionic surfaces and smooth surfaces, the effectiveness of reducing wear by application of bionic models are successfully demonstrated. Moreover, parametric studies on geometrical parameters of bionic models were also carried out. The results demonstrate that as biological wear reduction mechanisms are implemented, wear reduction of bulk solids handling equipment surfaces can be achieved. It is shown that abrasive wear loss can be reduced by up to 63% whilst erosive wear loss can be reduced by up to 26%.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
  • Lodewijks, Gabri, Supervisor
  • Schott, D.L., Advisor
Thesis sponsors
Award date27 Jun 2017
Print ISBNs978-90-5584-227-8
Publication statusPublished - 2017

Bibliographical note

TRAIL Thesis Series T2017/8, the Netherlands TRAIL Research School


  • wear prediction
  • discrete element method
  • bulk solids handling
  • bionic design

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