This work documents the development of a tool to perform automated parameter fitting of constitutive material models. Specific to this work is the fitting of a Swift hardening rule and isotropic linear plasticity model to aluminum 2024-T351, C36000 brass, and C10100 copper. Material characterization was conducted through the use of compressive, cold upsetting tests. A noncontact, optical displacement measurement system was applied to measure the axial and radial deformation of the test specimens. Nonlinear optimization techniques were then applied to tune a finite element model to match experimental results through the optimization of material model parameters as well as frictional coefficient. The result is a system, which can determine constitutive model parameters rapidly and without user interaction. While this tool provided material parameters for each material and model tested, the quality of the fit varied depending on how appropriate the constitutive model was to the material's actual plastic behavior. Aluminum's behavior proved to be an excellent match to the Swift hardening rule while the behavior of brass and copper was described better by the linear plasticity model.

References

1.
Johnson
,
G.
, and
Cook
,
W.
,
1983
, “
A Constitutive Model and Data for Metals Subjected to Large Strains, High Strain Rates and High Temperatures
,”
Seventh International Symposium on Ballistics
, The Hague, The Netherlands, Apr. 19–21, pp.
541
547
.
2.
Chait
,
R.
, and
Curll
,
C. H.
,
1976
, “
Evaluating Engineering Alloys in Compression
,”
Recent Developments in Mechanical Testing
,
A.
Schmleder
, ed.,
ASTM International
, West Conshohocken, PA, pp.
3
19
.
3.
Wierzbicki
,
T.
,
Bao
,
Y.
,
Lee
,
Y. W.
, and
Bai
,
Y.
,
2005
, “
Calibration and Evaluation of Seven Fracture Models
,”
Int. J. Mech. Sci.
,
47
(
4–5
), pp.
719
743
.
4.
Xue
,
L.
, and
Wierzbicki
,
T.
,
2009
, “
Numerical Simulation of Fracture Mode Transition in Ductile Plates
,”
Int. J. Solids Struct
,
46
(
6
), pp.
1423
1435
.
5.
Bao
,
Y.
, and
Wierzbicki
,
T.
,
2004
, “
A Comparative Study on Various Ductile Crack Formation Criteria
,”
ASME J. Eng. Mater. Technol.
,
126
(
3
), p.
314
.
6.
Chen
,
F. K.
, and
Chen
,
C. J.
,
2000
, “
On the Nonuniform Deformation of the Cylinder Compression Test
,”
ASME J. Eng. Mater. Technol.
,
122
(
2
), pp.
192
197
.
7.
Banerjee
,
J. K.
,
1985
, “
Barreling of Solid Cylinders Under Axial Compression
,”
ASME J. Eng. Mater. Technol.
,
107
(
2
), pp.
138
144
.
8.
ASTM International
,
2012
, “
Standard Test Methods of Compression Testing of Metallic Materials at Room Temperature
,”
ASTM International
,
West Conshohocken, PA
, Standard No.
E9-09
.https://www.astm.org/DATABASE.CART/HISTORICAL/E9-09.htm
9.
Narayan
,
S.
, and
Rajeshkannan
,
A.
,
2012
, “
Some Aspects of Barreling in Sintered Plain Carbon Steel Powder Metallurgy Preforms During Cold Upsetting
,”
Mater. Res
,
15
(
2
), pp.
291
299
.
10.
Christiansen
,
P.
,
Martins
,
P. A. F.
, and
Bay
,
N.
,
2016
, “
Friction Compensation in the Upsetting of Cylindrical Test Specimens
,”
Exp. Mech.
,
56
(
7
), pp.
1271
1279
.
11.
Springmann
,
M.
, and
Kuna
,
M.
,
2005
, “
Identification of Material Parameters of the Gurson-Tvergaard-Needleman Model by Combined Experimental and Numerical Techniques
,”
Comput. Mater. Sci.
,
33
(
4
), pp.
501
509
.
12.
Vaz
,
M.
,
Cardoso
,
E. L.
,
Munoz-Rojas
,
P. A.
,
Carniel
,
T. A.
,
Luersen
,
M. A.
,
Tomiyama
,
M.
,
da Silva
,
J. O.
,
Stahlschmidt
,
J.
, and
Trentin
,
R. G.
,
2015
, “
Identification of Constitutive Parameters - Optimization Strategies and Applications
,”
Materialwiss. Werkstofftech.
,
46
(
4–5
), pp.
477
491
.
13.
Abbasi
,
M.
,
Ketabchi
,
M.
,
Izadkhah
,
H.
,
Fatmehsaria
,
D.
, and
Aghbash
,
A.
,
2011
, “
Identification of GTN Model Parameters by Application of Response Surface Methodology
,”
Procedia Eng.
,
10
, pp.
415
420
.
14.
Muñoz-Rojas
,
P. A.
,
Cardoso
,
E. L.
, and
Vaz
,
M.
,
2010
, “
Parameter Identification of Damage Models Using Genetic Algorithms
,”
Exp. Mech.
,
50
(
5
), pp.
627
634
.
15.
Cooreman
,
S.
,
Lecompte
,
D.
,
Sol
,
H.
,
Vantomme
,
J.
, and
Debruyne
,
D.
,
2008
, “
Identification of Mechanical Material Behavior Through Inverse Modeling and DIC
,”
Exp. Mech.
,
48
(
4
), pp.
421
433
.
16.
Roux
,
E.
, and
Bouchard
,
P.-O.
,
2015
, “
On the Interest of Using Full Field Measurements in Ductile Damage Model Calibration
,”
Int. J. Solids Struct.
,
72
, pp.
50
62
.
17.
Primavera
,
V.
,
Perillo
,
M.
,
Carofalo
,
A.
,
Giorgi
,
M. D.
, and
Nobile
,
R.
,
2015
, “
Calibration of Material Models for the Numerical Simulation of Aluminium Foams—MAT 154 for M-PORE Foams @ 3 Loads
,”
13th International LS-Dyna Users Conference
, Dearborn, MI, June 8–10, pp.
1
24
.https://www.dynalook.com/13th-international-ls-dyna-conference/constitutive-modeling/calibration-of-material-models-for-the-numerical-simulation-of-aluminium-foams-2013-mat-154-for-m-pore-foams-3-loads/view
18.
Bondy
,
M.
,
Altenhof
,
W.
, and
Jensen
,
M. R.
,
2016
, “
Finite Element Modelling of a Novel Cutting Deformation Mode of AA6061-T6 Tubes Employing Higher Order Element Formulations and GPU Computing Technology
,”
ICILSM 2016
, Turin, Italy, May 22–26, pp.
1
6
.
19.
Umbrello
,
D.
,
M'Saoubi
,
R.
, and
Outeiro
,
J. C.
,
2007
, “
The Influence of Johnson-Cook Material Constants on Finite Element Simulation of Machining of AISI 316 L Steel
,”
Int. J. Mach. Tools Manuf.
,
47
(
3–4
), pp.
462
470
.
20.
Wikman
,
B.
,
Bergman
,
G.
,
Oldenburg
,
M.
, and
Häggblad
,
H. Å.
,
2006
, “
Estimation of Constitutive Parameters for Powder Pressing by Inverse Modelling
,”
Struct. Multidiscip. Optim.
,
31
(
5
), pp.
400
409
.
21.
Morrow
,
D. A.
,
Donahue
,
T. H.
,
Odegard
,
G. M.
, and
Kaufman
,
K. R.
,
2010
, “
A Method for Assessing the Fit of a Constitutive Material Model to Experimental Stress-Strain Data
,”
Comput. Methods Biomech. Biomed. Eng.
,
13
(
2
), pp.
247
256
.
22.
Chawla
,
A.
,
Mukherjee
,
S.
, and
Karthikeyan
,
B.
,
2009
, “
Characterization of Human Passive Muscles for Impact Loads Using Genetic Algorithm and Inverse Finite Element Methods
,”
Biomech. Model. Mechanobiol.
,
8
(
1
), pp.
67
76
.
23.
Guan
,
F.
,
Han
,
X.
,
Mao
,
H.
,
Wagner
,
C.
,
Yeni
,
Y. N.
, and
Yang
,
K. H.
,
2011
, “
Application of Optimization Methodology and Specimen-Specific Finite Element Models for Investigating Material Properties of Rat Skull
,”
Ann. Biomed. Eng.
,
39
(
1
), pp.
85
95
.
24.
Bao
,
Y.
,
2003
, “
Prediction of Ductile Track Formation in Uncracked Bodies
,” Ph.D. thesis, MIT, Cambridge, MA.
25.
Felling
,
A.
, and
Doman
,
D. A.
,
2018
, “
A New Video Extensometer System for Testing Materials Undergoing Severe Plastic Deformation
,”
ASME J. Eng. Mater. Technol.
,
140
(
3
), p.
031005
.
26.
LSTC
,
2016
, “
LS-DYNA Keyword User's Manual Volume II—Material Models
,” 9.0.1 ed.,
Livermore Software Technology Corporation
,
Livermore, CA
.
27.
Khan
,
A. S.
, and
Liu
,
H.
,
2012
, “
A New Approach for Ductile Fracture Prediction on Al 2024-T351 Alloy
,”
Int. J. Plast.
,
35
, pp.
1
12
.
28.
Malcher
,
L.
,
Andrade Pires
,
F.
, and
César de Sá
,
J.
,
2012
, “
An Assessment of Isotropic Constitutive Models for Ductile Fracture Under High and Low Stress Triaxiality
,”
Int. J. Plast.
,
30–31
, pp.
81
115
.
29.
MathWorks Inc.
,
2017
, “
Constrained Nonlinear Optimization Algorithms: Documentation (r2017a)
,” Natick, MA.
30.
Roux
,
E.
, and
Bouchard
,
P.-O.
,
2010
, “
Ductile Damage Material Parameter Identification: Numerical Investigation
,”
Tenth International Conference on Computational Structures Technology
, Barcelona, Spain, Sept. 4–6, pp.
1
10
.
You do not currently have access to this content.