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![](https://wqketang.oss-cn-beijing.aliyuncs.com/zip-unzip/zip-34bcd421-2eee-44b0-939e-7cd86ef6ac71/101237TH-2024-7-1548/files/101237TH-2024-7-1548-gab.jpg?Expires=1725755943&OSSAccessKeyId=STS.NT5eViCkqzTYdbfdqxMkjpyyq&Signature=v2Cq59NK7x4J9wA8S7JfyEELgAo%3D&security-token=CAISywJ1q6Ft5B2yfSjIr5eALuzdrrRQzZayZkTXgHEtQeRGn7zSkzz2IHtKenhsBOsbtfk1mG5W5%2FgZlqJ9SptIAEfJa9d99MzUP%2FpFltCT1fau5Jko1beHewHKeTOZsebWZ%2BLmNqC%2FHt6md1HDkAJq3LL%2Bbk%2FMdle5MJqP%2B%2FUFB5ZtKWveVzddA8pMLQZPsdITMWCrVcygKRn3mGHdfiEK00he8TouufTinpHMskGA1Aell7Mvyt6vcsT%2BXa5FJ4xiVtq55utye5fa3TRYgxowr%2Fwo0v0YpGya5YzHXwcPskvdKZbo78UqLQlla6w%2BGqFJqvPxr%2Fp8t%2Fx5fWJKAezhVgs8cVM8JOjIqKOscIsiJsO71SmqFV55c8Fdm%2BgUooJVgIMhTnduUfAPJAGOxzJitP%2BUVGGphr60TEnBL4rB5MUctfzRp75SXVPUTzDnGoABjuNLcf76FQN6p3t%2BSlCg%2FxR5C72RIk78k%2BUi44L9ZBmFT6F8GV7aXA52D1Ps56knKF6PAnhRivwyTxgsolycBfvccb3t5jGJ24SgY0aYosAECutxAo7sJhSwlwZvGwGDZJsop1vGiZ8eN1MbtZeRRuMeaZ2I%2BQo%2BnVP6Cf%2F0pDsgAA%3D%3D)
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Fluid jet polishing (FJP) is a non-contact polishing technology that can fabricate free-form optical surfaces with sub-micron-level form accuracy and nano-level surface roughness, especially for hard and brittle materials. The surface generation model of FJP can be used to guide the determination and optimization of process parameters and is of great significance for understanding the evolution mechanism of surface microtopography. However, predictive models for the microscopic topography of polished surfaces are still lacking. This study established a macroscopic surface profile model for predicting 3D material removal characteristics and surface texture by combining the 3D computer fluid dynamics (CFD) simulation model and single-particle erosion mechanism. A fractal theory-based erosion model has been built to calculate the material removal caused by the erosion of a single abrasive particle on the rough surface; thus, it predicts the micro-topography and surface roughness of the polished samples. A series of polishing experiments were conducted to analyze the feasibility and accuracy of the model quantitatively and study the influence mechanism of process parameters on the material removal characteristics and surface quality. Results indicated that the models could well predict material removal and surface roughness. The prediction accuracy of the surface roughness Ra and maximum removal depth is better than 91.6% and 90%, respectively. It is also found that the material removal rate of FJP could reach 0.517 mm3/min, and the surface roughness convergence rate could reach 62.9%.
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