torsion strength of tig welded similar and dissimilar
TRANSCRIPT
Torsion strength of TIG welded similar and dissimilar metal jointsof ASME SA213 Gr.T11 and BS3059:1987 PT1 ERW320
SEWA SINGH1,* , VIKAS CHAWLA1 and GURBHINDER SINGH BRAR2
1Department of Mechanical Engineering, IKG-Punjab Technical University, Kapurthala, Punjab, India2Department of Mechanical Engineering, Anand College of Engineering and Management, Kapurthala, Punjab,
India
e-mail: [email protected]; [email protected]; [email protected]
MS received 14 March 2021; revised 9 September 2021; accepted 22 September 2021
Abstract. Tungsten Inert Gas (TIG) welding has been learnt to be the most widely used technique among the
fusion welding techniques. Welding of different components of boilers is preferably accomplished by TIG
welding, due to the process capabilities of the technique to produce sound joints, even in case of Dissimilar
Metal Joints (DMJ). DMJs owing to the techno-economic advantages, find vast area of application especially in
boiler fabrication industry. It has been learnt that the quality of welded joints is signified by mechanical
properties of the joint. The present paper is focused on the behavioural aspects of similar and dissimilar metal
joints of ASME SA 213 GR. T11 and BS 3059:1987 PT 1 ERW 320, the boiler steam tube materials, prepared
by TIG welding under torsional loading. It has been observed that the dissimilar metal joint has performed better
than the individual similar metal joints under torsional loading by achieving 85% of the torsion strength of one
of the parent metal, whereas in the case of individual similar metal joints of ASME SA213 Gr. T11 and
BS3059:1987 PT1 ERW320, 78% and 68% of the torsion strength of respective parent metals has been
observed. ANOVA statistics have validated the existence of significant impact of input process variables on the
output quality measure of the welded joint at 95% level of confidence. The predictive models for optimum
torsional strength have been proposed by regression analysis.
Keywords. Dissimilar metal joints; Torsion strength; TIG welding; ANOVA; Multiple regression.
1. Introduction
Fusion Welding (FW) has been considered as the suit-
able and oldest method of joining two metallic components
and the versatility of the technique, deems it fit for several
industrial applications wherein nearly all kind of metallic
joints are being fabricated under the one umbrella of FW.
Different techniques of FW have been in practice, and the
thoughtful selection of most suitable technique for a par-
ticular material combination renders sound joint [1], certain
metallurgical issues however are associated with the FW,
especially in case of dissimilar metal joints [2], reduction in
the mechanical strength has also been found, when com-
pared with the base metals [3].
Arc welding in manual mode, Gas Metal Arc Welding
(GMAW), Gas Tungsten Arc Welding (GTAW) or TIG are
frequently preferred welding methods [4]. It is quite obvi-
ous that being a fusion welding process, the performance of
the TIG welded joint be marginally inferior in comparison
to the parent metal as well as the joint prepared by solid
state welding, the reported results in the literature advocate
the statement wherein it has been mentioned that the
accumulated plastic strain is higher in the TIG welded joint
than that in friction stir welded joint of aluminium alloy
AW 1050 [5]. However, literature has suggested that being
capable of joining large number of metals, TIG welding is
considered as most versatile and popular method of
metallic joint fabrication [6, 7], it has also been learnt that
using TIG welding, effective and efficient production of
sound joints is feasible irrespective of the welding position
[8]. Fox et al have stated that deeper penetration in single
pass has been found feasible using TIG welding [9].
Numerous researchers have discussed TIG welded joints
from different perspectives in the literature published so
far. Here, few of them have been quoted, discussing the
weldment quality of TIG welded joints and the extent of
influence of the process variables on it. TIG welding has
been observed better than MIG welding in several aspects
[10], the effect of TIG welding parameters on the
mechanical properties and the corrosion resistance of
aluminium alloy AA 6061 T6 has been reported in the
literature [11], it has been found that the TIG welded
specimen experienced ductile fracture in tensile as well as
torsion loading. However, the fracture location has been*For correspondence
Sådhanå (2021) 46:231 � Indian Academy of Sciences
https://doi.org/10.1007/s12046-021-01750-w Sadhana(0123456789().,-volV)FT3](0123456789().,-volV)
noticed in heat affected region [12]. The torsion test of TIG
welded SS 304 and Ni-Ti joint revealed that on an average
the joint resisted a torque of 52 Nm before fracture, it has
been reported that the heat affected zone in the said TIG
welded joint extended to a distance of 125 lm [13].
The welding current has been reported to be an important
factor influencing the output weldment quality of the TIG
welded joint [14], size of filler wire, flow rate of gas and
welding speed have also been presented as influencing
factors affecting the weldment quality [15], speed of
welding and mechanical properties of the weldment have
been reported to be negatively associated [16]. The welding
current affects the heat input at the weld interface, which in
turn affects the microstructure at and around the joint
interface [17]. It has also been reported that TIG welded
joints of alloy 6061 T6 of aluminium exhibited the fatigue
strength in the range comparable to that produced by fric-
tion stir welding, thereby proving the capability of the
technique, in spite of being part of fusion welding family
[18].
Mechanical testing and characterization of TIG welded
dissimilar metal joints of Inconel 718 and high strength
steel has revealed that the heat input at the weld interface
has affected the microstructural growth in the heat affected
region, the weldment quality has been signified by the
mechanical properties of the joint [19]. The composition of
the filler wire has been reported to be an influential
parameter in dissimilar metal joints, playing decisive role in
the output quality of the weldment in terms of mechanical
properties [20]. It has been learnt that the use of some
interlayer improves the mechanical properties of the welded
joint, literature has supported the statement reporting the
use of Incoloy 600 during the activated TIG welding of
AISI 316 L steel with P91 steel, it has revealed the
improvement in microstructure and impact toughness of the
joint without compromise of joint strength [21], the role of
flux type in influencing the mechanical properties of A-TIG
welded dissimilar metal joint prepared from P92 and 304H
stainless steel has been explored and the results revealed
that the appropriate selection of the flux positively impact
the joint properties [22].
The contribution of the input process parameters towards
the variation in macrostructure, microstructure and
mechanical properties of the TIG welded joints has been
explored, while using the controlled intermittent wire feed
method, it has been reported that above 40% reduction in
joint strength observed attributed to lower heat input at
weld interface [23]. The effect of welding current and
welding time on mechanical and microstructural properties
during dissimilar arc stud welding of different steel com-
binations viz. AISI 316L, AISI 1020 and AISI 304 has been
reported in literature, it was observed that joint produced at
a welding current of 600 A for 0.25 seconds exhibited the
maximum torque strength of 77 Nm [24]. The significant
influence of the inert gas shielding on the microstructure
and weld quality has been advocated in literature [25].
The use of statistical techniques for the validation of
inferences of the experimental observations, and opti-
mization of the process parameters to obtain the best in
class results of the experiments has been in practice since
long ago. The published literature supports the statement
that the careful selection of the process parameters plays
prominently decisive role as far as the quality characteris-
tics of the welded joints are concerned, the attempts of
optimization of the process variables using statistical
techniques have been reported in the literature [26, 27, and
28].
It is apparent from the brief discussion of the above
literature that various researchers have attempted to
explore different aspects of the TIG welding technique in
preparing different similar and dissimilar metal joints of
numerous materials, very few have discussed the perfor-
mance of TIG welded joint of ASME SA213 Gr. T11 and
BS3059:1987 PT1 ERW320 as discussed by Singh et al[1], it has been observed that the said paper has focused
on only tensile strength of the TIG welded similar and
dissimilar metal joints of the materials under considera-
tion, further the performance of the same material com-
bination under torsional loading has not been reported so
far, therefore an attempt has been made in the present
work to explore and report the behaviour of the similar
and dissimilar metal joints of the same materials under
torsional loading, in order to narrow down the gap in
knowledge about the mechanical behaviour of the said
materials.
2. Materials and methods
The current study has been focused on investigation of
weldments of ASME SA213 Gr. T11 (referred as T11,
hereafter) and BS3059:1987 PT1 ERW320 (referred as
3059, hereafter), the materials of boiler steam tubes being
used in boiler fabrication industry, the outer diameter and
wall thickness of the tubes were 38 mm and 3.7 mm
respectively. As per current industrial practice, the weld-
ments of boiler steam tubes are prepared after pre-heating
the work pieces to 150� to 200�C. Hence it has been
decided to prepare the weldments under three pre-
conditions i.e. welding without preheating (represented as
welding at room temperature, RT), welding after
pre-heating at 150�C (referred as PH150), and welding after
preheating at 200�C (referred as PH200).
TIG welding equipment used for current work supported
manual welding therefore the process variables considered
for the current investigation were, welding current and flow
rate of inert gas. After the pilot investigations, the current
variation has been decided to lie between 90-120 A with
incremental value of 10 A. Similarly, the gas flow rate was
decided to vary from 8 l/min to 12 l/min, incrementing by
2 l/min. Hence the total number of weldments corresponding
231 Page 2 of 12 Sådhanå (2021) 46:231
to each pre-condition piled up to 12. The welding equip-
ment used was of GAIDU make, operating on single phase
power AC power supply of 220 V. Table 1 depicts the
specifications of the welding equipment and figure 1 depicts
the photographs of the one of the dissimilar metal joints
prepared at a welding current of 110 A and under the gas
flow rate of 10 l/min.
Table 2 presents the compositional details other than Fe
in both the parent metals, as revealed from the optical
spectroscopy conducted in the laboratory of Central Insti-
tute of Hand Tools, Jalandhar, Punjab (India) and table 3
presents the different combinations of the process variables
in different experimental conditions. The terms F1, F2 and
F3 represent the flow rate of 8 l/min, 10 l/min and 12 l/min
respectively; whereas C1-C4 represent the welding current
settings varying from 90 A to 120 A, incrementing by 10 A
and L1–L3 represent the pre-condition of the work piece
before welding, herein L1 corresponds to the weldments
prepared at room temperature i.e. weldments prepared
without preheating, L2 represent the weldments prepared
after preheating to 150�C, and L3 corresponds to the
weldments prepared after preheating to 200�C.
3. Experimental results and discussion
Torsion testing of the weldments was conducted on FIE
make torsion testing machine installed in the laboratory of
Anand College of Engineering and Management, Kapur-
thala (Punjab, India). Table 4 contains the specifications of
the machine. ASTM E2207-15 standard has been followed
for specimen preparation and testing of the weldments as
suggested in published literature [29] (figure 2), the welded
portion was kept in the centre of the specimen. Table 5
contains the torsion test results of the parent metals (un-
welded). The torque before fracture has been considered as
the indicative measure of the torsion strength of the spec-
imen, and twist angle indicates the extent of ductile nature
of the specimen. Apparently the specimens of BS3059:1987
PT1 ERW320 have reflected the existence of the more
torsional resistance and ductility than that exhibited by
ASME SA213 Gr. T11, it may be the effect of Cr present in
the later material.
Table 6 depicts the maximum torque and maximum twist
angle observed during the torsion testing of the samples of
similar metal joints prepared from ASME SA213 Gr. T11.
Apparently it can be stated that the torque and angle of
twist are in direct association with the welding current, in
other words the samples prepared at higher welding current
are observed to exhibit higher torque before failure, and the
same is true for angle of twist. It may be attributed to the
reason as stated in literature that higher welding current
leads to higher and quicker heat input at the weld interface
resulting in refined microstructure leading to improved
mechanical properties [18] and [30]. However, the flow rate
of gas has directly influenced the torque and twist angle up
to the value of 10 l/min, and thereafter either the output
parameters tended to stabilise or showed slight decline in
the torque and twist angle. The maximum torque of 21 Nm
and maximum angle of twist of 18� has been observed in
the samples welded without preheating, when the welding
current and flow rate of gas were 110 A and 10 l/min
respectively.
Similarly, the response of similar metal joints prepared
from BS3059:1987 PT1 ERW320, to the torsional loading,
has been presented in table 7, general observation reveals
that the torque and twist angle increased, as the samples
prepared at higher and higher current were encountered.
The variation of the torque and twist angle with the vari-
ation in flow rate of gas has been observed to follow nearly
the similar trends as stated above, the slight decrease in the
torque in the samples welded at increased flow rate of gas
may be attributed to the increased cooling rate at the weld
interface due to the enhanced convective heat transfer rate
owing to the increased flow volume of the inert gas.
The maximum torque of 21 Nm has been observed in the
samples welded at 120 A of current and 12 l/min of gas
flow rate, when welded without preheating. The same value
has also been noticed in the samples welded at 110 A of
current and 10 l/min of gas flow, after preheating to 150�C.The parametric combination resulted in maximum twist
angle of 18�.Table 8 illustrates the data pertaining to the torsional
testing of dissimilar metal joints of ASME SA213 Gr. T11
and BS3059:1987 PT1 ERW320. Herein, the trends
obtained are on similar track as discussed above, the
maximum torque of 23 Nm has been observed in the
samples welded at 110 A of current and 10 l/min of gas
flow rate, when the samples were preheated to 200�C, thecorresponding angle of twist was noticed to be 18�. It hasbeen noticed that the maximum angle of twist of 20�exhibited by the samples welded at 120 A of current and
12 l/min of gas flow rate, when the samples were preheated
to 200�C, but the sample failed at lesser torque i.e. 21 Nm,
it may be attributed to the microstructural refinement and
embrittlement caused by the high heat input at elevated
level of current. The trends of variation of torsion strength
as depicted in tables 6, 7, 8 are in good agreement with the
published literature showing increase in torsion strength
Table 1. Specifications of TIG welding equipment.
Sl.No. Description Specification
1. Make GAIDU
2. Manufactured 2014
3. Power supply 220 V, AC
4. Current range Single phase, 0-200 A
5. Torch cooling Air cooled
Sådhanå (2021) 46:231 Page 3 of 12 231
with increase in heat input at weld interface up to certain
limit and thereafter tends to either stabilise or showing
declining values, however the source of heat input therein
was frictional effect between the mating surface unlike the
welding current in present work [31].
In all the three cases discussed above, it has also been
noticed that the pre heat temperature influences the tor-
sional strength and angle of twist to considerable extent, the
interaction of heat input at the weld interface and the
temperature gradient between weld region and parent metal
may be supposed to be the reason behind the behavioural
trends observed; stating otherwise increase in pre-heat
temperature leads to lowering temperature difference
between the weld interface and the parent metal, thereby
slowing down the cooling to some extent and hence lim-
iting the embrittlement caused by quicker cooling, and
hence improvement in the mechanical properties has been
witnessed, the literature also suggests the microstructural
refinement due to the heat interaction at the weld interface
Figure 1. Photograph demonstrating welded joint between T11 and 3059.
Table 2. Chemical composition of parent metals (in %), other than Fe.
Material C Si Mn P S Cr Mo Ni V
3059 0.371 0.469 1.01 0.0367 0.043 – – – –
T11 0.12 0.646 0.511 0.007 0.0031 1.11 0.469 0.0527 0.0021
Table 3. Experimental design depicting process variable.
Sl.No. Pre-Condition
Flow rate of inert gas (l/min)
F1 F2 F3
1. L1 (RT) C1 C1 C1
2. C2 C2 C2
3. C3 C3 C3
4. C4 C4 C4
5. L2 (PH150) C1 C1 C1
6. C2 C2 C2
7. C3 C3 C3
8. C4 C4 C4
9. L3 (PH200) C1 C1 C1
12. C2 C2 C4
11. C3 C3 C3
12. C4 C4 C4
Table 4. Specifications of torsion testing machine.
Make Model Maximum torque capacity (Nm) Torsion speed (rpm) Clearance between grips (mm)
FIE TT-10 100 1.5 0–420
231 Page 4 of 12 Sådhanå (2021) 46:231
to be the reason behind the mechanical behaviour of the
weldment [32, 33, and 34]
Figures 3, 4 and 5 represent the graphical presentation of
the torsion strength of similar metal joints of ASME SA213
Gr. T11 and BS3059:1987 PT1 ERW320; and dissimilar
metal joints of both the metals respectively. The trends
observed in current investigation are similar to those
specified in literature in terms of the effect of heat input on
the mechanical properties of the welded joint. It has been
reported therein that increase in axial pressure and rota-
tional speed during friction welding resulted in higher heat
input at weld interface leading to the improvement trends in
mechanical properties of the joint bearing direct association
with the heat input [35], likewise the heat input at weld
interface in current study being directly influenced by the
welding current has resulted in the trends presented herein.
4. Statistical validation
The inferences made from unprocessed raw data obtained
from the experimental observation is not considered as
healthy practice, but statistically processed data can reliably
be leading to some authenticated conclusions. The state-
ment is supported by the published literature signifying the
use of numerous mathematical and statistical technique for
the optimization of the process parameters [36].
The results discussed in previous sections indicate
towards the existence of some kind of association between
input process variables and the output joint strength in
terms of torque exhibited before fracture; however the
associations indicated herein by the variance in the results
may be theoretically obvious but the possibility of inclusion
of the variance due to experimental circumstances cannot
be completely ruled out; so the situation of ambiguity can
Figure 2. Torsion test specimen.
Table 5. Torsion test results of parent metals.
Sl.No Strength indicator ASME SA213 Gr. T11 BS3059:1987 PT1 ERW320
1. Torque (Nm) 27 31
2. Angle of twist (Degree) 20 23
Table 6. Torsion test results of similar metal joints of T11.
Flow rate Current
L1 L2 L3
Torque (Nm) Angle of twist (Deg) Torque (Nm) Angle of twist (Deg) Torque (Nm) Angle of twist (Deg)
F1 C1 8 5 9 5 11 7
C2 12 7 12 8 12 9
C3 15 8 16 10 17 10
C4 17 12 17 12 17 12
F2 C1 11 7 11 8 12 9
C2 16 12 14 10 14 11
C3 21 18 16 11 18 12
C4 21 17 17 12 20 12
F3 C1 10 7 11 8 12 10
C2 15 12 15 12 15 14
C3 19 15 18 13 17 15
C4 20 18 18 12 18 15
Sådhanå (2021) 46:231 Page 5 of 12 231
be avoided by testing the variance statistically. As sug-
gested by literature [1, 26] and [27], Analysis of Variance
(ANOVA) has been used to test the variance followed by
regression analysis, in order to develop predictive model of
the input and output relationship. Following are the null
hypothesis tested using two-way ANOVA:
1. H01= No significant influence of welding current exists,
on the torsion strength of the joints
2. H02= No significant influence of the gas flow rate exists,
on the torsion strength of the joints.
3. H03= No significant influence of the temperature of work
piece before welding exists, on the torsion strength of the
joints.
4. H04= No significant interaction exists between the input
parameters.
4.1 Similar metal joints of ASME SA213 Gr. T11
The summary of important statistics of ANOVA test carried
on the test data corresponding to the similar metal joints of
ASME SA213 Gr. T11 has been depicted in Appendix A1.
It is apparent from the tabulation that Fcurrent= 59.005, when
p=0.0005\a=0.05, it implies that H01 cannot be accepted
i.e. there exists a significant association between the
welding current and mechanical property of the joint under
consideration. Fflow=5.933, when p\a compels the rejec-
tion of H02, in other words significant association between
flow rate and the torsion strength has been validated.
Ftemp=0.617, when p[a indicates that the temperature has
no significant impact on the torsion strength of the weld-
ment, hence H03 has been accepted. As far as the interaction
between the input parameters is concerned it is evident
Table 7. Torsion test results of similar metal joints of 3059.
Flow rate Current
L1 L2 L3
Torque (Nm) Angle of twist (Deg) Torque (Nm) Angle of twist (Deg) Torque (Nm) Angle of twist (Deg)
F1 C1 10 8 12 8 12 10
C2 14 10 15 12 17 14
C3 16 13 16 14 19 16
C4 19 13 21 15 20 16
F2 C1 13 9 13 10 12 10
C2 17 13 18 13 17 13
C3 18 14 21 18 19 15
C4 19 17 20 18 19 14
F3 C1 12 10 13 9 13 12
C2 17 12 18 12 17 13
C3 18 15 20 12 18 15
C4 21 18 20 13 19 15
Table 8. Torsion test results of dissimilar metal joints of T11 and 3059.
Flow rate Current
L1 L2 L3
Torque (Nm) Angle of twist (Deg) Torque (Nm) Angle of twist (Deg) Torque (Nm) Angle of twist (Deg)
F1 C1 12 14 15 13 16 14
C2 16 16 18 15 20 17
C3 19 17 19 16 21 18
C4 20 17 21 18 21 19
F2 C1 14 13 16 14 17 15
C2 18 15 20 16 19 14
C3 20 17 21 19 23 18
C4 21 19 22 19 22 16
F3 C1 14 12 17 13 17 15
C2 19 14 18 14 19 18
C3 21 17 21 17 22 18
C4 21 18 21 18 21 20
231 Page 6 of 12 Sådhanå (2021) 46:231
from the tabulated data in Appendix-A1 that there exists no
significant interaction between current and flow rate,
whereas significant association between current-tempera-
ture and flow rate-temperature has been indicated, so H04
can be rejected for the later combination of parameters.
The model summary of regression analysis has been
presented in Appendix B1, it is evident that ‘R’ theMultiple
Correlation Coefficient has been noticed to bear value
0.914. It implies excellent level of prediction of the torsion
strength by the regression analysis. ‘R2’ the Coefficient ofDetermination signifies the model effectiveness in
explaining the contribution of the input variables in the
variance of output quantity, herein R2=0.835 simply means
that the welding current, flow rate, and temperature
0
5
10
15
20
25
90 A 100A
110A
120A
90 A 100A
110A
120A
90 A 100A
110A
120A
RT PH150 PH2008 l/min 8 12 15 17 9 12 16 17 11 12 17 17
10 l/min 11 16 21 21 11 14 16 17 12 14 18 20
12 l/min 10 15 19 20 11 15 18 18 12 15 17 18
Max
imum
torq
ue(N
m)
SIMILAR METAL JOINTS OF ASME SA213 Gr. T11
Figure 3. Variation of maximum torque (Similar Metal Joints of T11).
0
5
10
15
20
25
90 A 100A
110A
120A
90 A 100A
110A
120A
90 A 100A
110A
120A
RT PH150 PH2008 l/min 10 14 16 19 12 15 16 21 12 17 19 20
10 l/min 13 17 18 19 13 18 21 20 12 17 19 19
12 l/min 12 17 18 21 13 18 20 20 13 17 18 19
Max
imum
torq
ue
(Nm
)
SIMILAR METAL JOINTS OF BS3059:1987 PT1 ERW320
Figure 4. Variation of maximum torque (similar metal joints of BS3059).
Sådhanå (2021) 46:231 Page 7 of 12 231
accounts for 83.5% of variation of torsion strength. The
standard error of estimation has been observed to be 1.47. It
reflects that the average distance of observed data from the
regression line is 1.47 Nm, it further supports the closeness
of the predictive model to the observed experimental
trends. The same is further strengthened by the ANOVA
statistics of the regression model (Appendix C1) , depicting
the fitness of the model to the experimental data, evidently
the f-statistics obtained here i.e. F(3, 32)= 54.023, when
p=0.0005\\ a=0.05, indicates that the regression model
under consideration holds good fit of the experimental
results.
The generalised predictive model proposed by the
regression analysis can be presented as below:
TST11 ¼ �18:114þ 0:269C þ 0:521F � 0:002T
4.2 Similar metal joints of BS3059:1987 PT1ERW320
The summary of important statistics of ANOVA test carried
on the test data corresponding to the similar metal joints of
BS3059:1987 PT1 ERW320 has been presented in
Appendix-A2. It is apparent from the tabulation that Fcur-
rent= 221.851, when p=0.0005\a=0.05, it implies that H01
is rejected i.e. there exists a significant association between
the welding current and mechanical property of the joint
under consideration. Fflow=2.679, when p\a compels the
rejection of H02, in other words significant association
between flow rate and the torsion strength has been
validated. Ftemp=1.767, when p[a indicates that the tem-
perature has no significant impact on the torsion strength of
the weldment, hence H03 has been accepted. As far as the
interaction between the input parameters is concerned, it is
evident from the Appendix-A2 that there exists no signifi-
cant interaction between current and flow rate, whereas
significant association between current-temperature and
flow rate-temperature has been indicated, so H04 can be
rejected for the later combination of parameters.
The model summary of regression analysis depicts the
fitness of regression model (Appendix-B2), the MultipleCorrelation Coefficient, R = 0.910, means excellent level of
prediction of the torsion strength by the regression model.
The Coefficient of Determination R2=0.827 signifies that
the regression model is effective in explaining the contri-
bution of the input variables in the variance of output
quantity to the tune of 82.7%. The standard error of esti-
mate of 1.35 leads to inference that on an average the
observed values are 1.35 Nm far from the predictive model
represented by the regression equation, which strongly
supports the inference driven by the value of R2=0.827 and
further the closeness of fitment of the observed experi-
mental results and the predictive regression model has been
confirmed by the ANOVA statistics of the regression
model, (Appendix C2) depicting the fitness of the model to
the experimental data, evidently the f-statistics obtained
here i.e. F(3, 32)= 51.060, when p=0.0005\\a=0.05, indi-cates that the regression model under consideration holds
good fit of the experimental results.
The generalised predictive model proposed by the
regression analysis can be presented as below:
0
5
10
15
20
25
90 A 100A
110A
120A
90 A 100A
110A
120A
90 A 100A
110A
120A
RT PH150 PH2008 l/min 12 16 19 20 15 18 19 21 16 20 21 21
10 l/min 14 18 20 21 16 20 21 22 17 19 23 22
12 l/min 14 19 21 21 17 18 21 21 17 19 22 21
Max
imum
torq
ue(N
m)
ASME SA213 Gr. T11 & BS3059:1987 PT1 ERW320 DISSIMILAR METAL JOINT
Figure 5. Variation of maximum torque (dissimilar metal joints of T11 and 3059).
231 Page 8 of 12 Sådhanå (2021) 46:231
TS3059 ¼ �12:518þ 0:243C þ 0:313F þ 0:005T
4.3 Dissimilar metal joints of ASME SA213 Gr.T11 and BS3059:1987 PT1 ERW320
Observing the summary of important statistics of ANOVA
test carried on the test data corresponding to the dissimilar
metal joints of ASME SA213 Gr. T11 and BS3059:1987
PT1 ERW320 (Appendix A3), it is evident that Fcurrent=
46.201, when p=0.0005\a=0.05, it is an indication of the
fact that there exists a significant association between the
welding current and mechanical property of the joint under
consideration, hence H01 has be rejected. Fflow=6.419, when
p\ a compels the rejection of H02, in other words signif-
icant association between flow rate and the torsion strength
has been validated. Ftemp=6.200, when p\a indicates that
the temperature has significant impact on the torsion
strength of the weldment, hence H03 needs not to be
accepted i.e. temperature of the work pieces before welding
has significant impact on the torsion strength for dissimilar
metal combination. As far as the interaction between the
input parameters is concerned, it is evident from Appendix
A3 that there exists no significant interaction between
current-flow rate and temperature-flow rate, whereas sig-
nificant association between current-temperature has been
indicated. So H04 can be rejected for the later combination
of parameters.
The model summary of regression analysis (Appendix
B3) reflects the authenticity of the predictive regression
model, the Multiple Correlation Coefficient, R = 0.908,
signifies the existence of excellent level of prediction of the
torsion strength by the regression model. The Coefficient ofDetermination R2=0.825 implies that the 82.5% of the
variance of torsion test results due to variance of input
process variables has been explained by the regression
model. The standard error of estimate appears to be 1.15, it
simply implies that the explanation of the variance pre-
sented by coefficient of determination of 0.825 has been
strongly supported by the calculated standard error of
estimate, in other words the average distance between the
predictive model presented by the regression line and the
observed experimental results is 1.15 Nm only, and hence
the high degree of fitness of the predictive model can safely
be claimed, which is again supported by the ANOVA
statistics of the regression model (Appendix C3), depicting
the quality of fit of the regression model to the experimental
data, apparently F(3, 32)=50.289, when p\\a, indicates theexcellent fit of the model to the test results.
The generalised predictive model for the dissimilar metal
joints of the metals under investigation has been presented
as follows:
TSDis ¼ �5:627þ 0:196C þ 0:271F þ 0:011T
5. Conclusions
The present investigation has successfully explored the
performance to TIG welded similar and dissimilar metal
joints of T11 and 3059 materials of boiler steam tubes
under the action of torsional loading. The torque experi-
enced by the welded sample before fracture has been taken
as an indicative measure of the torsion strength. The
observations have revealed that there exists significant
individual impact of input process variables on the output
mechanical property of the welded joints at 95% level of
confidence. The trends depicted here are in good agreement
to those depicted in literature [37, 38, and 39]. The joint
efficiency in case of dissimilar metal joints has been
observed to be 85% and 74% as compared to the parent
metals T11 and 3059, respectively, whereas in case of
similar metal joints the joint efficiency has been found to be
78% in case of T11 and 68% in case of 3059 materials,
respectively. However, the results depicted here are far
better than those reported in the literature [23].
The volume of a particular research work can never be so
vast that the researcher could claim the perfectness, there
are certain unavoidable constraints of time and finances that
limit the extent of work envelop, certainly such limitations
serve as the scope for future work by fellow researchers,
following are such scope for future work.
1. The investigation can be focused on detailed exploration
of more mechanical properties. Especially, the impact of
process variables on fracture behaviour can be explored.
2. Effect of filler metal composition can be explored.
Appendix
Appendix A1
See Table 9.
Table 9. ANOVA Statistics for similar metal joints of ASME SA
213 GR. T11
Source of variation SS df MS F P
Current 342.556 3 114.185 59.005 0.0005
Flow rate 39.389 2 19.694 5.933 0.046
Temperature 5.722 2 2.861 0.617 0.569
Current*flow rate 1.944 6 0.324 0.526 0.778
Current*temperature 11.611 6 1.935 3.143 0.043
Flow rate*temperature 13.278 4 3.319 5.391 0.010
Sådhanå (2021) 46:231 Page 9 of 12 231
Appendix A2
See Table 10.
Appendix A3
See Table 11.
Appendix B1
See Table 12.
Appendix B2
See Table 13.
Appendix B3
See Table 14.
Appendix C1
See Table 15.
Table 10. ANOVA Statistics for similar metal joints of
BS3059:1987 PT1 ERW320
Source of variation SS df MS F P
Current 289.639 3 96.546 221.851 0.0005
Flow rate 12.500 2 6.250 2.679 0.0183
Temperature 7.167 2 3.583 1.767 0.317
Current*flow rate 8.611 6 1.435 1.938 0.155
Current*temperature 2.611 6 0.435 0.588 0.0073
Flow rate*temperature 9.333 4 2.333 3.150 0.049
Table 11. ANOVA Statistics for dissimilar metal joints of
ASME SA213 Gr. T11 and BS3059:1987 PT1 ERW320
Source of variation SS df MS F P
Current 191.222 3 63.741 46.201 0.0005
Flow rate 11.056 2 5.528 6.419 0.046
Temperature 22.389 2 11.194 6.200 0.033
Current*flow rate 2.278 6 0.380 0.872 0.542
Current*temperature 8.278 6 1.380 3.170 0.042
Flow rate*temperature 3.444 4 0.861 1.979 0.162
Table 12. Model summary of regression analysis for similar
metal joints of ASME SA 213 Gr. T11
Model R R2Adjusted R
square
Std. error of the
estimate
1 0.914a 0.835 0.820 1.47442
a Predictors: (Constant), Current (C), Flow Rate (F), Temperature (T)
Table 13. Model summary of regression analysis for similar
metal joints of BS3059:1987 PT1 ERW320
Model R R2Adjusted R
square
Std. error of the
estimate
1 0.910a 0.827 0.811 1.35251
a Predictors: (Constant), Current (C), Flow rate (F), Temperature (T)
Table 14. Model summary of regression analysis for dissimilar
metal joints of ASME SA 213 Gr. T11 and BS3059:1987 PT1
ERW320
Model R R2Adjusted R
square
Std. Error of the
estimate
1 0.908a 0.825 0.809 1.15486
a Predictors: (Constant), Current (C), Flow rate (F), Temperature (T)
Table 15. ANOVA Statistics of regression model for similar
metal joints of ASME SA 213 Gr. T11
Model Sum of squares df Mean square F P
1Regression 352.324 3 117.441 54.023 .0005b
Residual 69.565 32 2.174
Total 421.889 35
a Dependent Variable: Torsion Strength (TS)b Predictors: (Constant), Current (C), Flow rate (F), Temperature (T)
231 Page 10 of 12 Sådhanå (2021) 46:231
Appendix C2
See Table 16.
Appendix C3
See Table 17.
Acknowledgements
The author is grateful to I. K. Gujral Punjab Technical
University, Kapurthala, Punjab (India) for providing oppor-
tunity to work on the project and providing the able
professional support through my supervisors Dr. Vikas
Chawla and Dr. G S Brar.
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