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dc.contributor.authorVadali, Madhu
dc.contributor.authorMa, Chao
dc.contributor.authorDuffie, Neil A.
dc.contributor.authorLi, Xiaochun
dc.contributor.authorPfefferkorn, Frank E.
dc.date.accessioned2013-05-09T17:13:48Z
dc.date.available2013-05-09T17:13:48Z
dc.date.issued2011-03-07
dc.identifier.citationICOMM 2011 No. 80en
dc.identifier.urihttp://digital.library.wisc.edu/1793/65462
dc.description.abstractThis project is focused on developing physics-based models to predict the outcome of pulsed laser micro polishing (PL�P). Perry et al. have modeled PL�P as oscillations of capillary waves with damping resulting from the forces of surface tension and viscosity and a one-dimensional spatial frequency domain analysis was proposed. They have also proposed a critical spatial frequency, f_cr, above which a significant reduction in the amplitude of the spatial Fourier components is expected. The current work extends the concept of critical frequency to two dimensional spatial frequency analysis of PL�P. We propose a physics-based pre-diction methodology to predict the spatial frequency content and surface roughness after polishing, given the features of the original surface, the material properties, and laser parameters used for PL�P. The proposed prediction methodology was tested using PL�P line polishing data for stainless steel 316L and area polishing results for pure Nickel, Ti6Al4V, and Al-6061-T6. The predicted average surface roughnesses were within 10% to 12% of the values measured on the polished surfaces. The results show that the critical frequency continues to be a useful predictor of polishing results in the 2-D spatial frequency domain. The laser processing parameters, as represented by the critical frequency, and the initial surface texture can be used to predict the final surface roughness before actually implementing PL�P.en
dc.publisher6th Annual Conference on MicroManufacturing (ICOMM 2011)
dc.subjectpulsed laser polishingen
dc.subjectmodelingen
dc.subjectlaseren
dc.subjectpolishingen
dc.titlePulsed Laser Micro Polishing: Surface Prediction Modelen
dc.typeOtheren


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