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Computational investigation of the effect of microstructure on the scratch resistance of tungsten-carbide nickel composite coatings
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- Author(s) / Creator(s)
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Sliding wear was simulated for tungsten carbide-nickel (WC-Ni) composites with different WC particle sizes and volume fractions under various normal forces. Johnson-Cook and Johnson-Holmquist models were employed to simulate the mechanical behaviour of the Ni and WC phases, respectively. Using high-powered parallel computing, a detailed parametric study was conducted to understand the effects of normal force, WC particle size, WC particle volume fraction, and their interaction on the worn volume and the material removal mechanisms in WC-Ni metal matrix composite coating materials. This allowed for investigation of the competition and transition between microploughing, microcutting, and microfatigue. The results revealed that the stress was distributed better in the composite coating with higher particle volume fraction and smaller particle size, which increased the ability of the composite coating to resist deformation and wear. It was also found that the material removal mechanism changed from microploughing to microcutting with an increase in particle volume fraction. The worn volume was calculated for different combinations of intrinsic (e.g., WC particle size and volume fraction) and external (e.g., normal force) parameters considered in this study. The data obtained was used to train a machine learning-based model using artificial neural networks. The trained model was further employed to predict the worn volume, and the results revealed that a mechanistic modelling approach can predict worn volume reasonably well.
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- Date created
- 2021-08-15
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- Type of Item
- Article (Draft / Submitted)