A DEM‐based method for predicting the wear evolution of structural boundary composed of spherical boundary elements
Summary In the discrete element method (DEM) simulation for wear prediction, structural boundary is now represented extensively by triangular meshes with high resolution, which brings a huge computational cost. A DEM‐based method for predicting the wear evolution of structural boundary has been deve...
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Veröffentlicht in: | International journal for numerical methods in engineering 2020-12, Vol.121 (24), p.5667-5695 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Summary
In the discrete element method (DEM) simulation for wear prediction, structural boundary is now represented extensively by triangular meshes with high resolution, which brings a huge computational cost. A DEM‐based method for predicting the wear evolution of structural boundary has been developed for computational efficiency. The structural boundary subjected to wear is represented by the spherical boundary elements in the DEM simulation in combination with the inside triangles and fitting curved surface in wear prediction. Wear prediction is performed through a series of evolution steps. In each evolution step, the collision energies by particles at structural boundary are collected via the DEM simulation and assigned to the boundary elements. Then, the volume losses of structural boundary are predicted across each relevant boundary element. Finally, the new geometry of structural boundary in response to wear is described by moving the boundary elements along the depths of wear individually. Through converting the contact detection between structural boundary and particles into between spherical boundary elements and particles, our method greatly reduces the computational cost in the DEM simulation. Through two numerical tests, our method has been verified to be an efficient and accurate method for the wear prediction of structural boundaries with different resolutions. |
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ISSN: | 0029-5981 1097-0207 |
DOI: | 10.1002/nme.6517 |