Research Papers

A Microstructure-Sensitive Model for Simulating the Impact Response of a High-Manganese Austenitic Steel

[+] Author and Article Information
M. Mirzajanzadeh

Department of Mechanical Engineering,
Advanced Materials Group (AMG),
Koç University,
İstanbul 34450, Turkey

D. Canadinc

Department of Mechanical Engineering,
Advanced Materials Group (AMG),
Koç University;
Koç University Surface Science
and Technology Center (KUYTAM),
İstanbul 34450, Turkey
e-mail: dcanadinc@ku.edu.tr

1Corresponding author.

Contributed by the Materials Division of ASME for publication in the JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY. Manuscript received November 12, 2015; final manuscript received April 7, 2016; published online June 13, 2016. Assoc. Editor: Antonios Kontsos.

J. Eng. Mater. Technol 138(4), 041004 (Jun 13, 2016) (14 pages) Paper No: MATS-15-1287; doi: 10.1115/1.4033559 History: Received November 12, 2015; Revised April 07, 2016

Microstructurally informed macroscopic impact response of a high-manganese austenitic steel was modeled through incorporation of the viscoplastic self-consistent (VPSC) crystal plasticity model into the ansys ls-dyna nonlinear explicit finite-element (FE) frame. Voce hardening flow rule, capable of modeling plastic anisotropy in microstructures, was utilized in the VPSC crystal plasticity model to predict the micromechanical response of the material, which was calibrated based on experimentally measured quasi-static uniaxial tensile deformation response and initially measured textures. Specifically, hiring calibrated Voce parameters in VPSC, a modified material response was predicted employing local velocity gradient tensors obtained from the initial FE analyses as a new boundary condition for loading state. The updated micromechanical response of the material was then integrated into the macroscale material model by calibrating the Johnson–Cook (JC) constitutive relationship and the corresponding damage parameters. Consequently, we demonstrate the role of geometrically necessary multi-axial stress state for proper modeling of the impact response of polycrystalline metals and validate the presented approach by experimentally and numerically analyzing the deformation response of the Hadfield steel (HS) under impact loading.

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Fig. 1

Schematic illustration of the dependency of equivalent strain to fracture on the stress triaxiality in polycrystalline metals and the JC damage model (I and II represent different strain rates) modified with respect to the cutoff value of negative triaxiality for fracture

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Fig. 2

Dimensions of impact specimens (utilized in the experiments) besides geometry of the fixed supports (beds) and hammer employed in the FE simulation

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Fig. 3

Experimental impact test results: (a) force versus time in temperature of 323 K using three similar specimens of HS and (b) force versus time using four differently heated HS specimens

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Fig. 4

SEM observations of the fractured specimen with concentration on crack edge in the specimen, the dislocation concentration along the crack, and fractured face with void formation at T = 473 K. The arrows in (b) indicate the dense dislocation regions.

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Fig. 5

Quasi-static true-stress inelastic strain curve of HS and fitted JC material model used in the FE analysis

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Fig. 6

(a) The room temperature strain rate dependence of the monotonic tensile deformation response of Hadfield steels used for calculation of C constant parameter: Each curve is representative of 3–5 experiments [36]. (b) High temperature dependence of the monotonic tensile deformation response of the HS [2] accompanied by the JC fitted curve for the room temperature and strain rate of 0.4 s−1.

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Fig. 7

Final FE mesh and impact specimen geometry discretization for calculation of the microstructural behavior for the next step of the numerical work: ten different zones were identified for crystal plasticity modeling

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Fig. 8

Average stress triaxiality on the face-side of the smallest cross section on the Y-direction with horizontal representative of the cutoff value (explained in Ref. [33]) of stress triaxiality

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Fig. 9

Stress triaxiality parameter (η) distribution around the damage evolution region during ductile fracture

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Fig. 10

Strain (mm/mm) distribution along the X-direction emphasizing the position of the NA over four different steps of the deformation sequences during impact. Contour levels for strain are restricted between −0.5 and 2 in order to represent the location of NA more clearly.

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Fig. 11

Initial simulation of the impact force versus time response of HS with the application of JC material and damage model—JC material and fracture constants are cited in Table 1

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Fig. 12

(a) Quasi-static true-stress inelastic strain curve of HS used in the VPSC crystal plasticity simulation and initial VPSC modeling results: One should note that these experiments were aborted at about 18% of strain. (b) Inverse pole figure demonstrating the texture and anisotropy of HS along the loading direction of the sample (the data were obtained from XRD measurements).

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Fig. 13

Schematic illustration of the employed approach in numerical simulation of the impact response of high-manganese steel

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Fig. 14

Multiscale FE prediction of the impact force versus time response of HS with the application of JC material and damage model: comparison between FE and proposed multiscale FE model

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Fig. 15

von Mises stress (MPa) distribution and deformation sequences during ductile fracture of the whole sample

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Fig. 16

Strain (mm/mm) distribution along the X-direction at the end of the deformation illustrating protruded regions behind the striker (under high compressive loads) and mirrored picture of the cracked surfaces after fracture (under the notch) on the top. Photos show the actual samples following the experiments.



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