Research of the friction stir welding process of aluminium alloys.
Cesnavicius, R. ; Kilikevicius, S. ; Krasauskas, P. 等
1. Introduction
It is well known that welding of aluminium alloys using
conventional welding methods is a highly costly process, therefore, in
order to replace this welding technology, various other joining methods
are used. One of them is friction stir welding considered as a
non-traditional welding method. This method now is accepted as a
standard welding method for aluminium alloys and is used in various
fields of industry: aviation, train and marine building, chemical
industry etc. to weld aluminium materials which are difficult to weld by
other processes [1]. It has the benefits of operation and investment
cost savings, weight reduction, high repeatability and consistence, low
maintenance, better work environment and recyclability versus other
aluminium spot joining methods such as resistance spot welding (RSW) and
riveting [2, 3]. This welding method is relative simply, do not requires
consumables or filler metal and gas shielding, is low energy consuming
process, however needs special welding tool and powerful fixtures to
clamp the workpiece. Main parameters which have to be controlled during
the process are welding speed and feed which depends on the welding
material and the thickness of the welding parts, so to ensure
microstructural stability, these processing parameters must be
investigated thoroughly [4].
Due to wide applicability, this process is being studied
thoroughly. The basic principles of FSW, the weld microstructure and
hardness, mechanical properties, including consideration of residual
stress, fracture, fatigue and corrosion is described in [5] and is
demonstrated that FSW of aluminium has commercial applications.
Friction stir weldability of the 2017-T351 aluminium alloy was
investigated in [6], weldability and modelling of the 6061-T6 aluminium
alloy in [7], mechanical properties of AA 6082 aluminium alloy butt
joints welded by cylindrical taper pin profile in [8], effect of welding
speed and tool pin profile on welding zone formation in AA6061 aluminium
alloy was investigated in [9].
The overview showed that for different aluminium materials there is
no common welding parameters, i.e. for each one's strength,
hardness and microstructure should be defined experimentally.
The numerical modelling of the FSW process is a complicated task
highly dependent on various factors such as material properties, welding
process conditions, geometrical parameters of the tool, etc. During this
process, high stress and strain rate takes place and this leads to
non-linear material behaviour, excessive mesh distortion and the need
for high computational resources; therefore, a modelling of the FSW
process for each new case is complicated and specific.
Most of the researches dealing with the topic is focused on the
microstructural changes, heat transfer and thermal analysis in FSW.
Several approaches are used for modelling the FSW process. Coupled
thermo-mechanical modelling is analysed in papers [10-13].
Development of numerical simulation model for FSW employing
particle method is presented in [14]. A smoothed particle hydrodynamics
(SPH) model for FSW is proposed in paper [15].
Another approach for FSW modelling is the computational fluid
dynamics method [16, 17]. However, it is difficult to estimate metal
properties of the plastic deformation behaviour applying fluid models
for FSW.
This paper presents an experimental investigation and a numerical
modelling of the FSW process in order to analyse the influence of
different welding parameters on the horizontal welding force.
2. Experimental set-up and results
The FSW experiment was carried out on aluminium alloy AW 10-50 and
TL091T4 (AlMg5Mn) 100x50 mm plates with 1.5 mm in thickness using an FSW
tool with a special square pin. The shape and dimensions of the FSW tool
are shown in Fig. 1. The tool consists of three parts: a shoulder 1
which is made of hot-work tool steel X37CrMoV5-1 EN ISO 4957:2002 and
hardened to 50 HRC with a body diameter of 11 mm and a concavity of
5[degrees], a 1.3 mm length square cross-section 3x3 mm tungsten carbide
pin 2, and a M6 screw 3 for fixing pin in the shoulder.
[FIGURE 1 OMITTED]
The experimental setup is shown in Fig. 2. The experiments were
carried out on a CNC machining centre "LEADWELL V-20" 1 with a
"Fanuc 18i-MB" controller and "Manual Guide i"
software. The horizontal welding force was measured using a universal
laboratory charge amplifier Kistler type 5018A 2 and a press force
sensor Kistler type 9345B 3 mounted on the CNC table. Measuring ranges
for force of the sensor -10 ... 10 kN, sensitivity: [approximately equal
to] -3.7 pC/N. The amplifier converts the charge signal from the
piezoelectric pressure sensor into a proportional output voltage. The
variation of the horizontal welding force was recorded to a personal
computer 4 using a "PICOSCOPE 4424" oscilloscope 5 and
"PicoScope 6" software.
[FIGURE 2 OMITTED]
The tool was plunged into the joining zone of the workpieces by 1.3
mm (in vertical direction) and then welding was performed in horizontal
direction. Spindle speeds of 2000, 3000 and 4000 rpm were used and for
each of them three tool feed rates of 100, 200 and 300 mm/min were
assigned in order to investigate the influence of these parameters on
the horizontal welding force magnitude. The results of the investigation
of friction stir welding under different spindle speed and feed rates
are presented in Table 1.
An example of AW 10-50 aluminium alloy welded plates at spindle
speed of 2000 rpm and feed rate of 100 mm/min is shown in Fig. 3.
[FIGURE 3 OMITTED]
The experiments showed that the horizontal welding force increases
as feed rate increases, also the horizontal welding force decreases when
the spindle speed increases.
3. Mathematical background of FSW modelling
The governing equation describing the heat transfer during FSW can
be expressed as follows [18]:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], (1)
where [rho] is the material density; c is the specific heat, T is
the temperature, t is the time, k is the heat conductivity, G is the
heat generation. Generally, the main heat generation source in FSW is
considered to be the friction between the rotating tool and the
workpieces and the plastic straining in vicinity of the tool.
For the modelling based on the finite element method (FEM), the
Johnson-Cook model was used [19]:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)
where parameter A is the initial yield strength of the material at
room temperature, B is the hardening modulus; C is the parameter
representing strain rate sensitivity; [[bar.[epsilon]].sub.pl] is the
effective plastic strain; [[bar.[??]].sub.pl] is the effective plastic
strain rate [[??].sub.0] is the reference strain rate; n is the strain
hardening exponent; m is the parameter which evaluates thermal softening
effect, [T.sub.mell] and [T.sub.room] are the material melting and room
temperatures.
4. Computational model for the FSW process
ABAQUS/EXPLICIT software was used for a FEM modelling of the FSW
process. The workpieces were created as 10x25x1.5 mm plates. Only these
elements of the tool were modelled which can be in contact with the
workpieces, besides, the tool model was simplified making the pin round,
in order to achieve convergence (Fig. 4).
[FIGURE 4 OMITTED]
The adaptive meshing technique was applied by carrying it out for
every ten increments and performing five mesh sweeps per adaptive mesh
increment. The tool was meshed using element type C3D10MT due to its
complex shape and the plates were meshed using element type C3D8RT. An
element size of 0.3 mm was used for the tool and an element size of 0.15
mm was used for the plates. 8 layers of elements through the thickness
were generated in each of the plates. The mesh of each plate contained
63756 elements while the mesh of the tool contained 55040 elements.
In order to save computational time, the mass scaling technique was
used that modifies the densities of the materials in the model and
improves the computational efficiency [20], obtaining a stable time
increment of at least 0.0001 s step time.
It was assumed that 100% of dissipated energy caused by friction
between the parts was converted to heat. The temperature dependent
friction coefficient 2 of aluminium and steel used in this study is
presented in Table 2 [21]. The friction coefficient was set to 0 at the
melting temperature of aluminium alloy AW1050.
Material properties and the Johnson-Cook parameters for aluminium
alloy AW 1050 used for the FSW modelling are presented in Table 3 [22].
The boundary conditions (Fig. 5) were set as follow: the bottom
surface and all outer sides of the plates were restrained in all degree
of freedom; the top surfaces were under free convection with the
convection coefficient of 30 W/[m.sup.2]K; the ambient air temperature
and the initial temperature of the workpieces were set to 293 K.
[FIGURE 5 OMITTED]
5. Numerical modelling and comparison to the experimental results
Fig. 6 shows how the temperature changes during the FSW process
under spindle speed S = 3000 rpm and feed rate [F.sub.2] = 300 mm/min.
The maximum value was 627 K and it was observed during the tool plunging
phase. During the welding, the maximum temperature value was varying
between 578 K and 597 K.
Fig. 7 shows the von Mises stress at various instances of time, due
to the thermomechanical action. During the plunging phase, when the
temperature was 627 K, the maximum value of von Mises stress was about
211 MPa. Under the temperature value of 597 K, the maximum von Mises
stress is about 184 MPa.
Fig. 8 shows how the equivalent plastic strain changes during the
FSW process. Throughout the whole process, the maximum value of
equivalent plastic strain was 0.799.
[FIGURE 6 OMITTED]
[FIGURE 7 OMITTED]
[FIGURE 8 OMITTED]
The variation of the experimental and the simulated horizontal
welding force over time is presented in Fig. 9. The results showed a
good agreement in the time intervals between 0 and 1 s and between 2 s
and 3 s. In the time interval between 1 s and 2 s the difference was
more significant.
However, the trends of the experimental and the simulated welding
force variation over time are quite similar and this shows that the
presumptions taken in the modelling are quite reasonable.
[FIGURE 9 OMITTED]
6. Conclusions
An experimental analysis and a numerical modelling of the FSW
process were carried out welding two plates of aluminium alloy AW 1050
and TL091T4.
The experiments showed that the horizontal welding force increases
as feed rate increases, also the horizontal welding force decreases when
the spindle speed increases.
The modelling showed that under spindle speed S = 3000 rpm and feed
rate F2 = 300 mm/min, the maximum temperature value was 627 K and it was
observed during the tool plunging phase. During the welding, the maximum
temperature value was varying between 578 K and 597 K. During the
plunging phase, when the temperature was 627 K, the maximum value of von
Mises stress was about 211 MPa. Under the temperature value of 597 K,
the maximum von Mises stress is about 184 MPa. Throughout the whole
process, the maximum value of equivalent plastic strain was 0. 799. A
comparison between the experimental and the modelled horizontal welding
force showed a good agreement.
The results of the study showed that the presumptions taken in the
modelling are reasonable, therefore, the FEM modelling could be used for
prediction of rational FSW parameters in order to define lower weld
force, which leads to a decrease of tool wear.
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Received April 20, 2016
Accepted July 04, 2016
R. Cesnavicius, Kaunas University of Technology, Studenty 56, 51424
Kaunas, Lithuania, E-mail: ramunas.cesnavicius@ktu.lt
S. Kilikevicius, Kaunas University of Technology, Studenty 56,
51424 Kaunas, Lithuania, E-mail: sigitas.kilikevicius@ktu.lt
P. Krasauskas, Kaunas University of Technology, Studenty 56, 51424
Kaunas, Lithuania, E-mail: povilas.krasauskas@ktu.lt
R. Dundulis, Kaunas University of Technology, Studenty 56, 51424
Kaunas, Lithuania, E-mail: romualdas.dundulis@ktu.lt
H. Olisauskas, Kaunas University of Technology, Studenty 56, 51424
Kaunas, Lithuania, E-mail: harius.olisauskas@ktu.edu
http://dx.doi.org/10.5755/j01.mech.22.4.16167
Table 1
Matrix of the friction stir welding experiments and results
Material Plates Spindle Horizontal Maximal
thickness, speed, feed rate, welding
mm rpm mm/min force, N
AW 10-50 1.5 2000 100 2349
2000 200 2555
2000 300 2690
3000 100 2158
3000 200 2385
3000 300 2611
4000 100 2063
4000 200 2334
4000 300 2547
TL091T4 1.5 2000 100 1950
2000 200 1963
2000 300 1991
3000 100 1914
3000 200 1948
3000 300 1985
4000 100 1857
4000 200 1873
Table 2
Temperature dependent friction coefficient of aluminium
and steel
Temperature (K) Friction coefficient
273.0 0.610
307.7 0.545
366.3 0.359
420.5 0.255
483.6 0.244
533.0 0.147
588.6 0.135
644.1 0.02
699.7 0.007
Table 3
Mechanical properties and the Johnson-Cook
parameters for aluminium alloy AW 1050
Parameter Units Value
Young modulus, E GPa 69
Poisson's ratio, v -- 0.33
Density, [rho] kg/[m.sup.3] 2710
Melting temperature, [[theta].sub.melt] K 918
Specific heat capacity J/(kgK) 899
Thermal conductivity W/(mK) 160
Initial yield strength A MPa 110
Hardening modulus B MPa 150
Strain hardening exponent n -- 0.36
Thermal softening exponent m -- 1
Strain rate constant C -- 0.014
