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Numerical prediction of machining-induced surface residual stress for TC4 cryogenic turning

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Abstract

Liquid nitrogen(LN2) cryogenic machining is a green, sustainable, and high-performance machining technology. LN2 cryogenic machining of TC4 can significantly strengthen the local cooling environment of cutting, accelerate the heat dissipation, thus effectively reduce the cutting temperature, and suppress the generation of thermal stress, reduce the residual tensile stress on the workpiece surface. In this paper, a finite element model(FEM) of numerical prediction is established to analyze the effect of LN2 cryogenic machining on residual stress distribution. Firstly, mechanism analysis of surface residual stress is carried out to explore the source of residual stress during TC4 cryogenic turning. Next, to observe residual stress distribution clearly, the cutting zone separation model is designed, and then, the material model is built to reflect the change of material properties. Then, a FEM of the numerical prediction made up of explicit dynamic solution module and standard static solution module is established to simulate residual stress distribution; after that, residual stress can be ultimately acquired by linear superposing the above two module simulation results. Based on FEM proposed in this paper, the effect of LN2 cryogenic machining on surface residual stress distribution of TC4 is analyzed, and it is indicated that LN2 cryogenic machining can reduce the residual tensile stress effectively. Finally, the experiment is carried out, and the results show that the general trend of the prediction model is the same as that of the experimental results, which greatly verify the availability of the prediction model. Research provides some reference for the numerical prediction and suppression of residual stress in the future.

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Data availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

F :

Friction force

τ :

Effective shear strength

A t :

Actual contact area

n,k :

Constants about friction force

μ :

Friction coefficient

N :

Normal load

p y :

Yield stress of the contact material

σ mech, σ therm, σ total :

Mechanical, thermal, and total stress

p(s):

Load stress distribution along the feed direction

q(s):

Load stress distribution in the vertical feed direction

q h :

Heat intensity of the heat loss

\( \overline{h} \) :

Average convective heat transfer coefficient

T f, T w :

Average tool temperature and ambient temperature

Nu :

Nusselt number

Le :

Effective cooling strength

k air :

Air heat transfer coefficient

\( {\overline{h}}_e \) :

Actual heat transfer coefficient

λ :

Cryogenic friction correction coefficient

E :

Elastic modulus

ν :

Poisson’s ratio

α :

Thermal diffusion coefficient

h :

Thermal conductivity

ρ :

Density

C s :

Specific heat

G xh,G xv,G zh,G zv,G xzh,G xzv :

Plane strain Green function

\( \overline{\sigma},\overline{\varepsilon} \) :

Equivalent stress and plastic strain

T :

Cutting heat

T m, T r :

The melting point of the material and the room temperature

A, B, C, m, n :

Material constants in Johnson-Cook model

\( \Delta \frac{\cdotp }{\varepsilon^p} \) :

Equivalent plastic strain increment

\( \overline{\varepsilon_f^p} \) :

Equivalent plastic strain

d 1, d 2, d 3, d 4, d 5 :

Failure constant

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Funding

This work is supported by the National Natural Science Foundation of China (No. U20B2033), the National Key Research and Development Project (No. 2019YFB2005400), the Natural Science Foundation of Liaoning (No. 2020-YQ-09), and the Changjiang Scholar Program of Chinese Ministry of Education (No. T2017030).

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Authors and Affiliations

  1. Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, 116024, China

    Haibo Liu, Chengxin Wang, Kuo Liu, Shaowei Jiang & Yongqing Wang

  2. Hebei HanGuang Industry Co., Ltd., Handan, 056017, China

    Zhaohuan Liu

Authors
  1. Haibo Liu
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  2. Chengxin Wang
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  3. Zhaohuan Liu
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  4. Kuo Liu
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  5. Shaowei Jiang
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  6. Yongqing Wang
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Contributions

Haibo Liu and Kuo Liu: mechanism analysis of residual stress. Yongqing Wang, Chengxin Wang, and Shaowei Jiang: residual stress prediction using FEM for cryogenic turning. Zhaohuan Liu: experiment.

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Correspondence to Yongqing Wang.

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Liu, H., Wang, C., Liu, Z. et al. Numerical prediction of machining-induced surface residual stress for TC4 cryogenic turning. Int J Adv Manuf Technol 114, 131–144 (2021). https://doi.org/10.1007/s00170-021-06805-0

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