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Research Papers

Efficient Multiscale Modeling and Validation of Residual Stress Field in Cutting

[+] Author and Article Information
F. Wang

School of Mechanical Engineering,
Shandong University,
Jinan 250061, China

Z. Y. Liu

Department of Mechanical Engineering,
The University of Alabama,
Tuscaloosa, AL 35487

Y. B. Guo

Department of Mechanical Engineering,
The University of Alabama,
Tuscaloosa, AL 35487
e-mail: yguo@eng.ua.edu

J. Zhao, Z. Q. Liu

School of Mechanical Engineering,
Shandong University,
Jinan 250061, China

1Corresponding author.

Manuscript received December 1, 2016; final manuscript received April 28, 2017; published online June 22, 2017. Assoc. Editor: Guillaume Fromentin.

J. Manuf. Sci. Eng 139(9), 091004 (Jun 22, 2017) (11 pages) Paper No: MANU-16-1622; doi: 10.1115/1.4036714 History: Received December 01, 2016; Revised April 28, 2017

Residual stress (RS) has significant impact on cutting process optimization. However, conventional process modeling approaches are limited to only single cutting pass on very short length and time scales due to the exceedingly high computational cost. This work provides a new concept of equivalent loading which enables an efficient modeling approach to predict RS in an actual machined surface by incorporating multiple cutting passes and crossing different length and time scales. The predicted residual stress profiles are validated in turning Inconel 718 superalloy under different edge geometries and process conditions.

Copyright © 2017 by ASME
Topics: Stress , Cutting
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References

Figures

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Fig. 1

Schematic of plowed depth and material stagnation in a cutting process [25]

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Fig. 2

Efficient multiscale FEA modeling approach and validation

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Fig. 3

Tool geometry in experiment

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Fig. 4

Geometry models, mesh design, and FEA implementation procedure: (a) microscale single‐pass cutting, (b) spatial resolution, (c) equivalent loading, and (d) residual stress fields

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Fig. 5

Boundary conditions for the single-pass model

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Fig. 6

Transient stresses and temperatures predicted by the single-pass model

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Fig. 7

Simulation setup for the multipass model

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Fig. 8

Residual stresses predicted by the multipass model

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Fig. 9

Residual stress distribution: single-pass model versus multipass model: (a) single‐pass at cutting direction, (b) single‐pass at feed, (c) multipass at cutting direction, and (d) multipass at feed dir

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Fig. 10

Single-pass versus multipass cutting model with a sharp tool

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Fig. 11

Single-pass versus multipass with worn tool

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Fig. 12

Residual stress in feed direction for different edge radii

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Fig. 13

Residual stress in cutting direction for different edge radii

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Fig. 14

The effect of tool wear on residual stress

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Fig. 15

The effect of feed on residual stress with sharp tool

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Fig. 16

The effect of feed on residual stress with worn tool

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Fig. 17

The effect of cutting speed on residual stress with sharp tool

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Fig. 18

The effect of cutting speed on residual stress with worn tool

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Fig. 19

Comparison between the prediction and the experimental data for sharp tools

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Fig. 20

Comparison between the prediction and the experimental data for worn tools

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