Simulation model optimization for bonnet polishing considering consistent contact area response

Abstract

Simulation model optimization plays a crucial role in the accurate prediction of material removal function in bonnet polishing processes, but model complexity often poses challenges to the practical implementation and efficiency of these processes. This paper presents an innovative method for optimizing simulation model parameters, focusing on achieving consistent contact area and the accurate prediction of the material removal function while preventing increase in model complexity. First, controllable and uncontrollable factors in bonnet simulations are analyzed, and then a simplified contact model is developed and applied under constant force conditions. To characterize the bonnet’s contact performance, a contact area response curve is introduced, which can be obtained through a series of single spot contact experiments. Furthermore, a rubber hyperelastic parameter optimization model based on a neural network is proposed to achieve optimal matching of the contact area between simulation and experiment. The average deviation of the contact area under different conditions was reduced from 22.78% before optimization to 3.43% after optimization, preliminarily proving the effectiveness of the proposed simulation optimization model. Additionally, orthogonal experiments are further conducted to validate the proposed approach. The comparison between the experimental and predicted material removal functions reveals a high consistency, validating the accuracy and effectiveness of the proposed optimization method based on consistent contact response. This research provides valuable insights into enhancing the reliability and effectiveness of bonnet polishing simulations with a simple and practical approach while mitigating the complexity of the model.

Graphical abstract

Keywords

bonnet polishing / simulation / contact area / tool influence function / optimization

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant Nos. 52235004, 51991371, and 52205495) and the Natural Science Foundation of Sichuan Province, China (Grant Nos. 2023NSFSC0026 and 2022NSFSC1927). This work was also supported by the Fundamental Research Funds for the Central Universities, China (Grant No. 2682023GF025).

Conflict of Interest

Linmao QIAN is a member of the Editorial Board of Frontiers of Mechanical Engineering, who was excluded from the peer-review and all editorial decisions related to the acceptance and publication of this article. Peer-review was handled independently by the other editors to minimize the bias.

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