Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets

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JURENDIĆ, Sebastijan ;GAIANI, Sivlia .
Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 59, n.3, p. 148-155, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/numerical-simulation-of-cold-forming-of-%ce%b1-titanium-alloy-sheets/>. Date accessed: 05 dec. 2021. 
doi:http://dx.doi.org/10.5545/sv-jme.2012.415.
Jurendić, S., & Gaiani, S.
(2013).
Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets.
Strojniški vestnik - Journal of Mechanical Engineering, 59(3), 148-155.
doi:http://dx.doi.org/10.5545/sv-jme.2012.415
@article{sv-jmesv-jme.2012.415,
	author = {Sebastijan  Jurendić and Sivlia  Gaiani},
	title = {Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {59},
	number = {3},
	year = {2013},
	keywords = {α-titanium; HCP metals; Numerical simulation; Cold forming; Anisotropy; Deep drawing},
	abstract = {Despite the generally good cold workability of some α-titanium alloys, their relevant mechanical properties are quite different to those of traditional cold forming materials. The hexagonal close packed (HCP) crystal structure of α-titanium alloys results in a highly textured, highly anisotropic material that exhibits some specifics in its plastic response. A numerical simulation method using the Barlat [1989] material model has been developed to aid in forming tool development and process parameter determination. In order to account for the anisotropic hardening of the material, plastic strain ratios are input into the model as functions of plastic strain and an inversely determined, experimental strain hardening curve is used. The procedure for determining the input data from the tensile test is outlined and demonstrated on the α-titanium alloy 1.2ASN from Kobe Steel. The flow potential exponent m is evaluated via a parametric analysis of the Erichsen test and an appropriate value is determined. The forming limit diagram is adopted as a means for failure prediction and determined using the Nakajima method. Finally, the method is evaluated on an example of a deep drawn part with good correlation to the physical process.},
	issn = {0039-2480},	pages = {148-155},	doi = {10.5545/sv-jme.2012.415},
	url = {https://www.sv-jme.eu/article/numerical-simulation-of-cold-forming-of-%ce%b1-titanium-alloy-sheets/}
}
Jurendić, S.,Gaiani, S.
2013 June 59. Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 59:3
%A Jurendić, Sebastijan 
%A Gaiani, Sivlia 
%D 2013
%T Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets
%B 2013
%9 α-titanium; HCP metals; Numerical simulation; Cold forming; Anisotropy; Deep drawing
%! Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets
%K α-titanium; HCP metals; Numerical simulation; Cold forming; Anisotropy; Deep drawing
%X Despite the generally good cold workability of some α-titanium alloys, their relevant mechanical properties are quite different to those of traditional cold forming materials. The hexagonal close packed (HCP) crystal structure of α-titanium alloys results in a highly textured, highly anisotropic material that exhibits some specifics in its plastic response. A numerical simulation method using the Barlat [1989] material model has been developed to aid in forming tool development and process parameter determination. In order to account for the anisotropic hardening of the material, plastic strain ratios are input into the model as functions of plastic strain and an inversely determined, experimental strain hardening curve is used. The procedure for determining the input data from the tensile test is outlined and demonstrated on the α-titanium alloy 1.2ASN from Kobe Steel. The flow potential exponent m is evaluated via a parametric analysis of the Erichsen test and an appropriate value is determined. The forming limit diagram is adopted as a means for failure prediction and determined using the Nakajima method. Finally, the method is evaluated on an example of a deep drawn part with good correlation to the physical process.
%U https://www.sv-jme.eu/article/numerical-simulation-of-cold-forming-of-%ce%b1-titanium-alloy-sheets/
%0 Journal Article
%R 10.5545/sv-jme.2012.415
%& 148
%P 8
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 59
%N 3
%@ 0039-2480
%8 2018-06-28
%7 2018-06-28
Jurendić, Sebastijan, & Sivlia  Gaiani.
"Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets." Strojniški vestnik - Journal of Mechanical Engineering [Online], 59.3 (2013): 148-155. Web.  05 Dec. 2021
TY  - JOUR
AU  - Jurendić, Sebastijan 
AU  - Gaiani, Sivlia 
PY  - 2013
TI  - Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2012.415
KW  - α-titanium; HCP metals; Numerical simulation; Cold forming; Anisotropy; Deep drawing
N2  - Despite the generally good cold workability of some α-titanium alloys, their relevant mechanical properties are quite different to those of traditional cold forming materials. The hexagonal close packed (HCP) crystal structure of α-titanium alloys results in a highly textured, highly anisotropic material that exhibits some specifics in its plastic response. A numerical simulation method using the Barlat [1989] material model has been developed to aid in forming tool development and process parameter determination. In order to account for the anisotropic hardening of the material, plastic strain ratios are input into the model as functions of plastic strain and an inversely determined, experimental strain hardening curve is used. The procedure for determining the input data from the tensile test is outlined and demonstrated on the α-titanium alloy 1.2ASN from Kobe Steel. The flow potential exponent m is evaluated via a parametric analysis of the Erichsen test and an appropriate value is determined. The forming limit diagram is adopted as a means for failure prediction and determined using the Nakajima method. Finally, the method is evaluated on an example of a deep drawn part with good correlation to the physical process.
UR  - https://www.sv-jme.eu/article/numerical-simulation-of-cold-forming-of-%ce%b1-titanium-alloy-sheets/
@article{{sv-jme}{sv-jme.2012.415},
	author = {Jurendić, S., Gaiani, S.},
	title = {Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {59},
	number = {3},
	year = {2013},
	doi = {10.5545/sv-jme.2012.415},
	url = {https://www.sv-jme.eu/article/numerical-simulation-of-cold-forming-of-%ce%b1-titanium-alloy-sheets/}
}
TY  - JOUR
AU  - Jurendić, Sebastijan 
AU  - Gaiani, Sivlia 
PY  - 2018/06/28
TI  - Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 59, No 3 (2013): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2012.415
KW  - α-titanium, HCP metals, Numerical simulation, Cold forming, Anisotropy, Deep drawing
N2  - Despite the generally good cold workability of some α-titanium alloys, their relevant mechanical properties are quite different to those of traditional cold forming materials. The hexagonal close packed (HCP) crystal structure of α-titanium alloys results in a highly textured, highly anisotropic material that exhibits some specifics in its plastic response. A numerical simulation method using the Barlat [1989] material model has been developed to aid in forming tool development and process parameter determination. In order to account for the anisotropic hardening of the material, plastic strain ratios are input into the model as functions of plastic strain and an inversely determined, experimental strain hardening curve is used. The procedure for determining the input data from the tensile test is outlined and demonstrated on the α-titanium alloy 1.2ASN from Kobe Steel. The flow potential exponent m is evaluated via a parametric analysis of the Erichsen test and an appropriate value is determined. The forming limit diagram is adopted as a means for failure prediction and determined using the Nakajima method. Finally, the method is evaluated on an example of a deep drawn part with good correlation to the physical process.
UR  - https://www.sv-jme.eu/article/numerical-simulation-of-cold-forming-of-%ce%b1-titanium-alloy-sheets/
Jurendić, Sebastijan, AND Gaiani, Sivlia.
"Numerical Simulation of Cold Forming of α-Titanium Alloy Sheets" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 59 Number 3 (28 June 2018)

Authors

Affiliations

  • Novelis Deutschland GmbH, DE-37075 Goettingen, Germany 1
  • Novelis Deutschland GmbH, Germany / University of Modena and Reggio Emilia, Department of Materials Engineering, Italy 2

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 59(2013)3, 148-155

https://doi.org/10.5545/sv-jme.2012.415

Despite the generally good cold workability of some α-titanium alloys, their relevant mechanical properties are quite different to those of traditional cold forming materials. The hexagonal close packed (HCP) crystal structure of α-titanium alloys results in a highly textured, highly anisotropic material that exhibits some specifics in its plastic response. A numerical simulation method using the Barlat [1989] material model has been developed to aid in forming tool development and process parameter determination. In order to account for the anisotropic hardening of the material, plastic strain ratios are input into the model as functions of plastic strain and an inversely determined, experimental strain hardening curve is used. The procedure for determining the input data from the tensile test is outlined and demonstrated on the α-titanium alloy 1.2ASN from Kobe Steel. The flow potential exponent m is evaluated via a parametric analysis of the Erichsen test and an appropriate value is determined. The forming limit diagram is adopted as a means for failure prediction and determined using the Nakajima method. Finally, the method is evaluated on an example of a deep drawn part with good correlation to the physical process.

α-titanium; HCP metals; Numerical simulation; Cold forming; Anisotropy; Deep drawing