Size Effect on Surface Roughness of Very Thin Brass Sheets in Biaxial Stretching

Anand, Dhruv; Shrivastava, Archit; Kumar, Deepak

doi:10.1016/j.matpr.2019.07.093

Cited by 2 publications

(2 citation statements)

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“…One such property is the grain size, and the other is the specimen size. Both of these factors lead to a change in the ratio of thickness to the grain sizes of the specimen [11]. When the size of the workpiece is gradually reduced close to the grain size, the grain number in the workpiece is less, and a "size effect" occurs.…”

Section: Introductionmentioning

confidence: 99%

“…At a particular scale, the surface roughness increases with grain sizes. In the biaxial tensile deformation study, Anand et al [11] suggested that the ratio of sheet thickness to grain size (t/d) significantly affects surface roughness due to the size effect. For thin brass sheets, the ratio of thickness to grain size has a significant role in increasing the roughness during biaxial tension.…”

Section: Introductionmentioning

confidence: 99%

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Study on Size Effect of Surface Roughness Based on the 3D Voronoi Model and Establishment of Roughness Prediction Model in Micro-Metal Forming

et al. 2022

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The primary purpose of this paper is to study the size effect of surface roughness and realize the quantitative description of the surface roughness in micro-forming process. This work is a continuation of the previous work by the authors. The effects of the initial surface roughness of the specimen, the grain size, and grain orientations on the surface roughness of micro-upsetting products were investigated. The ratio of the number of grains of the surface layer to the total number of grains was adopted to characterize the size effect. The variation of the size effect on the contact normal pressure during the compression process was also analyzed. And the quantitative description of the evolution law of surface roughness for micro-formed parts was realized. The corresponding micro compression experiment was done in order to testify the prediction model.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%