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Thermomechanical finite element simulation and correlation analysis for orthogonal cutting of normalized AISI 9310 steels

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Abstract

A coupled thermomechanical finite element analysis is performed in order to simulate orthogonal cutting of normalized AISI 9310. Damage parameters are optimized to define the behavior of the material subjected to orthogonal cutting. AISI 1045, AISI 4140, and A2024-T351 are selected as precursors to validating the present finite element approach for orthogonal cutting of normalized AISI 9310. The numerical results obtained in this study include the average cutting force, residual stresses and strains, chip morphology, and tool temperature. These results are validated for each material with experimental results found in literature. The current study optimizes the Johnson–Cook damage parameters for steel materials in order to capture physical chip morphology. A correlation analysis is then performed using the validated finite element model for the AISI 9310 material to better understand the effect of specific input parameters such as the damage parameters, coefficient of friction, fracture energy, heat generation fractions and tool velocity on output results such as stresses and strains in the workpiece, chip thickness ratio and tool temperature. This analysis provides input-output relations for a physically reasonable range of input parameters and supports that the damage parameters, coefficient of friction, and fracture energy have a very strong influence on the residual stresses and strains, and the chip morphology. The coefficient of friction has a strong influence of tool temperature. Correlation analysis results can help manufacturers in understanding the nature of residual stresses and distortion, and in choosing optimized process parameters suitable for and applicable to the specific workpiece material. Tool wear that is observed in actual cutting of normalized AISI 9310 is also discussed. This study will benefit the manufacturing industry with the understanding of how specific cutting processing parameters will impact the distortions and residual stresses in the machined AISI 9310 parts.

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Data Availability

Not applicable.

Abbreviations

\( \overline{\sigma} \) :

Equivalent stress

\( \dot{\overline{\varepsilon_{eq}}} \) :

Equivalent plastic strain

\( \dot{\overline{\varepsilon_0}} \) :

Reference strain rate

T room :

Room temperature

T melt :

Melting temperature

T :

Current temperature

A :

Material yield strength in the Johnson–Cook constitutive model

B :

Hardening modulus in the Johnson–Cook constitutive model

C :

Coefficient of strain rate sensitivity in the Johnson–Cook constitutive model

n :

Hardening coefficient in the Johnson–Cook constitutive model

m :

Thermal softening coefficient in the Johnson–Cook constitutive model

D1 and D2 :

Void nucleation strain fitting parameters in the Johnson–Cook damage model

D3 :

Stress triaxiality coefficient in the Johnson–Cook damage model

D4 :

Strain rate coefficient in the Johnson–Cook damage model

D5 :

Thermal coefficient in the Johnson–Cook damage model

ω :

Damage indicator

\( {\overline{\varepsilon}}_{0i} \) :

Equivalent plastic strain at the onset of damage

G f :

Fracture energy

u f , :

Displacement at failure

K Ic and K IIc :

Fracture toughness for the chip serration and separation

τ fr :

Interface frictional stress

σ n :

Normal stress

\( {\overline{\tau}}_{max} \) :

Equivalent shear stress limit

\( {\overline{\sigma}}_s \) :

The Von-Mises equivalent stress

\( {\dot{q}}_p \) :

Volumetric heat flux due to plastic work

ƞ p :

Fraction coefficient of energy converted to heat for plastic work

σ eqv :

Equivalent stress

\( {\dot{\varepsilon}}^{pl} \) :

Plastic strain rate

\( {\dot{q}}_f \) :

Volumetric heat flux due to frictional work

f f :

Fraction of thermal energy conducted in the chip

ƞ f :

Fraction coefficient of energy converted to heat for frictional work

\( \dot{\gamma} \) :

Slip rate

ρpc :

Pearson’s correlation coefficient

cov (.):

Covariance of paired datasets

σ(.):

Standard deviation of single dataset

E(.):

Expectation operator

ρsc :

Spearman’s correlation coefficient

\( \Delta {r}_i^2 \) :

Difference between ranks of corresponding two data points

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Acknowledgements

We thank Jeffrey Knecht and Patrick Brueckner from Aero Gear, Inc based in Windsor, CT for their help and support. We gratefully acknowledge the Air Force Research Laboratory, Materials and Manufacturing Directorate (AFRL/RXMS) for support via contract FA8650-18-C-5700.

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Not applicable.

Funding

We gratefully acknowledge the Air Force Research Laboratory, Materials and Manufacturing Directorate (AFRL/RXMS) for support via contract FA8650-18-C-5700.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, University of Connecticut, 261 Glenbrook Rd., U-3037, Storrs, CT, 06269, USA

    Lilia Miller & Jeongho Kim

  2. Department of Mechanical Engineering, University of Connecticut, 191 Auditorium Rd, Storrs, CT, 06269, USA

    Kai Zhou & Jiong Tang

  3. Department of Materials Science & Engineering, University of Connecticut, 97 North Eagleville Road, Storrs, CT, 06269, USA

    Lesley D. Frame, Rainer J. Hebert, Lakshmi Ravi Narayan, S. Pamir Alpay & Alexandra Merkouriou

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  1. Lilia Miller
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Contributions

Lilia Miller conceptualization, methodology, data curation, investigation, writing - original draft.

Kai Zhou methodology, formal analysis, writing - original draft.

Jiong Tang methodology, formal analysis, writing - original draft.

Lesley Frame investigation, validation, writing - original draft.

Rainer Hebert investigation, validation

Lakshmi Ravi Narayan investigation, validation.

S. Pamir Alpay project administration, writing - review & editing.

Alexandra Merkouriou project administration, investigation.

Jeongho Kim conceptualization, methodology, writing - review & editing.

Corresponding author

Correspondence to Jeongho Kim.

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Miller, L., Zhou, K., Tang, J. et al. Thermomechanical finite element simulation and correlation analysis for orthogonal cutting of normalized AISI 9310 steels. Int J Adv Manuf Technol 114, 3337–3356 (2021). https://doi.org/10.1007/s00170-021-07130-2

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