Stress/Strain Induced Void?

Abstract

Fracture micro mechanisms of ductile porous solids are substantially researched worldwide since last 60 years through different experiments, theories, thermodynamics and computer models. It is still attracting immense interests to the scientists/engineers as evidenced by a slew of many interesting and innovative techniques, different perceptions and philosophies to elucidate ductile fracture micro mechanisms of materials. The damage accumulation (i.e., void volume fraction, fv) inside a ductile material under tensile deformation is strongly dependent on many engineering/metallurgical variables with their complex and unknown interactions. The role of micro void nucleation and growth during ductile fracture of materials under different environments and loading conditions is well established and documented, but the details of some micro mechanisms governing this fracture process are not still clearly understood. Such as, the coalescence of micro voids has not been clarified clearly, since it is an unstable and rapidly occurred phenomenon in materials. A comprehensive and exhaustive literature review has been performed to realize these facts completely. This article also critically reviews the standard computational methods often widely used for fracture mechanics analysis, which have been proposed/developed by eminent scientists to simulate the ductile fracture of materials. Many studies monitoring the damage accumulation during tensile deformation of different ductile alloys which are, in principle, affected by the imposed stress triaxiality, applied stress and the resulting plastic strains, are already available in the open published literatures. But it is still not clear in these circumstances, whether this damage accumulation is stress assisted or strain induced. In the current investigation, it has been demonstrated through experiments, modeling and reviewing from existing literature that damage accumulation inside a material can be effectively explained by imposed stress triaxiality. This article would be truly being a gift to the structural materials and solid mechanics communities as a whole.

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Abbreviations

AHSS :

Advanced high strength steels

ANN :

Artificial neural network

AISI :

American iron and steel institute

bcc :

Body centered cubic

BNN :

Bayesian neural network

C :

Micro void coalescence

CDM :

Continuum damage mechanics

CP :

Crystal plasticity

CP-FEM :

Crystal plasticity-finite element modeling

DIM :

Deformation induced martensite

DP :

Dual phase

DRX :

Dynamic recrystallization

EBSD :

Electron back scatter diffraction

EAM :

Embedded-atom method

EL :

Elongation

F :

Fracture

FEM :

Finite element modeling

FEA :

Finite element analysis

fcc :

Face centered cubic

GT :

Gurson–Tvergaard model

G :

Micro void growth

GND :

Geometrically necessary dislocations

GB :

Grain boundary

GBTP :

Grain boundary triple points

GS :

Grain size

GTN :

Gurson–Tvergaard–Needleman model

GLD :

Golaganu–Leblond–Devaux model

HT :

High temperature

HSLA :

High strength low alloy steels

hcp :

Hexagonal closed packed

IP :

Image processing

J :

J–integral

K :

Strain hardening co-efficient

LT :

Low temperature

LPE :

Log predictive error

MD :

Molecular dynamics

MMC :

Metal matrix composites

N :

Micro void nucleation

NL :

Notch length

L :

Displacement

M :

Strain rate sensitivity

NND :

Nearest neighboring distance

OLM :

Optical light microscope

OFHC :

Oxygen-free high thermal conductivity

PMMA :

Poly (methyl methacrylate)

RVE :

Representative Volume Element

RT :

Room temperature

RA :

Reduction in area

SR :

Strain rate

SEM :

Scanning electron microscope

SFE :

Stacking fault energy

SD :

Standard deviation

SZW :

Sretch zone width

T :

Temperature

TB :

Twin boundary

TRIP :

Transformation induced plasticity

TEM :

Transmission electron microscope

UTS :

Ultimate tensile strength

YS :

Yield strength

XRD :

X-ray diffraction

XRAY-CT:

X-ray computer tomography

ΔG c :

Critical free energy change

E :

Young’s modulus

ε :

Strain

ε c :

Critical strain

ε f :

Fracture strain

ε eff :

Effective strain

ε eq :

Equivalent strain

ε p :

Plastic strain

f 0 :

Initial void volume fraction

f c :

Critical void volume fraction

f v :

Void volume fraction

γ :

Shear stress

l 0 :

Intervoid spacing

l c :

Critical intervoid ligament distance

n :

Strain hardening exponent

P :

Load

r 0 :

Initial void size

ρ d :

Dislocation density

σ :

Applied stress

σ N :

Normal stress

σ h :

Hydrostatic tensile stress

σ r :

Residual stress

σ c :

Critical stress

σ f :

Fracture stress

σ m :

Mean stress

σ eq :

Equivalent stress

σ eff :

Effective stress

σ υ :

Sigma noise

T e :

Test error

t r :

Rupture time

τ :

Stress triaxiality ratio

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Acknowledgements

All the experiments and simulations (FEM through ABAQUS 6.9) were carried out at CSIR-National Metallurgical Laboratory, Jamshedpur when the author was previously employed as a Scientist during 2004–2014. I am extremely grateful to Professor Sir H.K.D.H. Bhadeshia, Phase Transformation and Complex Properties Research Group, Department of Materials Science and Metallurgy, University of Cambridge, UK for the provision of Neuromat Neural Network software for the current analysis. I would also like to thank Professor Eugenio Onate (The Editor in Chief - Archives of Computational Methods in Engineering) for the provision of facilities for the revision of the manuscript. The insightful suggestions, comments and strong recommendations about the manuscript by the anonymous reviewers are also gratefully appreciated.

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Das, A. Stress/Strain Induced Void?. Arch Computat Methods Eng (2020). https://doi.org/10.1007/s11831-020-09444-y

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