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Parametric approach model for determining welding conditions: New type of welding limit diagrams (WLD)
Journal of Materials Processing Technology 170 (2005) 477–486
Parametric approach model for determining welding conditions: New type of welding limit diagrams (WLD) Emin Bayraktar a,∗ , Dominique Kaplan b a
Supmeca/LISMMA-Paris, School of Mechanical and Manufacturing Engineering, Saint Ouen, France b ARCELOR GROUP, Paris, France Received 5 April 2004; received in revised form 5 April 2005; accepted 13 June 2005
Abstract A simple and easily understandable model was developed for predicting the relative importance of different factors (composition of the steels and welding processing conditions) in order to obtain an efficient welding joint. An application on the interstitial free (IF) steel sheets welded by LASER, TIG and also by resistance spot welding (RSW) for automotive industry as well as an application of multipass welds of structural steels for offshore and pressure vessel are given in this study. This model is based on thermal, metallurgical and mechanical and also in situ test conditions. It operates easily on the PC type computer. This approach is an efficient way to separate the responsibilities of the steel maker and welding designer for increasing the reliability of the welded structures. The construction of welding limit diagrams (WLD) that allows us to predict the values of the parameters in order to obtain an efficient welding joint is presented. © 2005 Elsevier B.V. All rights reserved. Keywords: Modelling; Welding conditions; Materials parameters; Welding limit diagrams (WLD)
1. Introduction The assessment of the safety of welded structures is carried out by commonly known fracture mechanic tests, particularly in heat affected zones (HAZ), such as crack tip opening displacement (CTOD), which is very sensitive to local brittle zones and wide plate testing [1–6,9–11]. In spite of long time required to conduct these tests, for finding practical data showing the welding (plate) conditions or a practical information giving a relation between chemical composition and welding conditions (multipass) in order to evaluate the welded structures in practical point of view is a real problem in many industrial applications, such as pipeline, offshore, marine engineering, pressure vessel, energy or other metallic constructions. Additionally, the toughness of HAZ is strongly function of the length of the local brittle zone, which deteriorates toughness in coarse grain HAZ (CGHAZ) and in intercritically HAZ (ICCGHAZ) and the critical value of the ∗
Corresponding author. E-mail address: [email protected] (E. Bayraktar).
0924-0136/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jmatprotec.2005.06.034
local brittle zone depends on the test conditions (failure mode, specimen geometry and temperature) as well as mechanical properties of the different microstructures intercepted. In other words, fracture initiation in welded structures has a probabilistic nature, rather than a deterministic one [12]. It seems that, the improvement the toughness of HAZ in multipass welds necessitates to reduce of the percentage of the local brittle zones. On the other hand, resistance spot welding (RSW) is the most widespread process applied on modern thin sheet steels or the interstitial free steels (IFS) used in the automotive industry. Recently, the development of tailored blanks by means of LASER welding and the general application of the LASER welding in this area have also occurred. Generally, IF steels have extremely low values of C and N contents, making them particularly suitable for deep drawing. However, for these steels, the appearance of the unusual grain growth at the HAZ has been reported. The presence this zone could decrease the fatigue resistance of spot welds by about 20%. Additionally, the impact tensile tests involving a notch localised in the grain growth zone display intergranular frac-
E. Bayraktar, D. Kaplan / Journal of Materials Processing Technology 170 (2005) 477–486
478
Nomenclature a Ac3 Ar3 c d e E G
Q t 700 t300 v x
thermal diffusivity (mm2 s−1 ) ␣ → ␥ transformation temperature (at heating) (◦ C) ␥ → ␣ transformation starting temperature (at cooling) (◦ C) specific heat sheet thickness (mm) basic logarithm linear welding heat input (kJ/cm) (welding ηQ power/welding speed) ηUI v = v dθ/dx (◦ C/mm) thermal gradient (At any given moment, this variable describes the “thermal environment” of a given point. A high “G” value indicates naturally high possibilities of heat evacuation by means of the surrounding zones.) power of the heat source (W) (VI for TIG and ηUIt for resistance spot weld) time for a given point (s) cooling conditions (s) (time elapsed from 700 to 300 ◦ C) welding speed (cm/min) distance to the fusion line for a given point (mm)
Greek letters dαL ferrite grain size in longitudinal direction (m) dαT ferrite grain size in transversal direction (m) η thermal efficiency depending on welding process and geometry (%) θ given temperature at a point during the thermal cycle (◦ C) θ0 initial temperature (◦ C) ρ specific mass ρc J mm−3 ◦ C−1
ture surface, by which the facet size corresponds to the grain size. Although there are a lot of studies on the assessment of the safety of welded structures related to HAZ but there is little information on the estimation of microstructure in the real welds and on the correlation of these values with welding conditions. Many researches concentrate on the thermal simulations for understanding metallurgical mechanism in a given welding conditions supported by FEM analysis but they are not sufficient to explain the complex situation met in many welding processes (e.g. multipass) or new steel compositions in a practical and easily understandable way. The objective of this paper is centred on a parametric approach model based on thermal, metallurgical and mechanical background and also in situ test conditions. This analytical approach is an efficient way to separate the responsibilities
of the steel maker and welding designer for increasing the reliability of the welded structures [7,8]. All of the works presented here are performed easily on an ordinary PC type computer.
2. Experimental study 2.1. Materials and welding process Different industrial grades of interstitial free (IF) steels whose thickness varies between 0.65 and 0.9 mm have been studied. The carbon values vary from 1.4 × 10−3 to 5 × 10−3 wt% and Mn values vary from 100 × 10−3 to 200 × 10−3 wt%. The grain growth in HAZ has been studied by means of the following techniques: - Gas tungsten arc welding (GTAW) has been performed with a voltage of 10 V, an intensity of 65 A, a welding rate of 40 cm/min and shielding argon gas (12 l/min). Considering the coefficient of thermal efficiency of the process (η ≈ 50%), the corresponding linear energy varies from 0.75 to 0.95 kJ/cm. - Resistance spot welding experiments were performed with a voltage of 1 V, an intensity of 6000 A and a welding time of 30 cycles (50 Hz). Spot diameter was approximately 4 mm. - The LASER welding experiments were performed with a CO2 LASER with powers ranging from 1.5 to 4 kW and with welding rates from 0.6 to 9 m/min. Considering the coefficient of thermal efficiency of the process (η ≈ 15%), the corresponding linear energy varies from 0.1 to 4 kJ/cm. Additionally, different grades of C–Mn steels have been studied. The carbon values vary from 70 × 10−3 to 130 × 10−3 wt% and Mn values vary from 500 × 10−3 to 1600 × 10−3 wt%. In the case of multipass welding, the values of thermal efficiency of the process was taken as η ≈ 15% and the corresponding welding linear energy varies from 5 to 65 kJ/cm. 2.2. Position of the problem First of all, estimation of a welded structure based on thermal, metallurgical and mechanical background and also in situ test conditions necessitates to know their suitability and limits with respect to each other at the same time. So, a model that includes all these parameters should be a simple and practical guide to the steel makers or to the weld designers. Secondly, the type of microstructure of a weld joint is function of many input parameters, which belong to the steel maker or weld designer (customer). The final result after a welding process (output) depends on the type, the toughness and the geometrical distribution of the microstructures.
E. Bayraktar, D. Kaplan / Journal of Materials Processing Technology 170 (2005) 477–486
Finally, an analytical approach is given to establish a relation between them and to put together all of the input parameters on a single diagram for presenting simply the final result. In the following section, all of these input parameters will be expressed in the form the influence diagrams, which are called new type of welding limit diagrams (WLD).
perature on the grain size and what about the percentage of intercritical zone? These questions may be multiplied with many input variables (I and II parameters) quoted just above. The final result (output) can be given as a function of types I and II input variables as follows: F = f (E, t, Ac1 , Ac3 , Ar3 , θ0 , θ1 , θ3 , v, etc.)
3. Results and discussion The problem can be presented with a system of three parts with many input variables coming from the steel maker’s responsibility (I) and weld designer or customer’s responsibility (II) and the final results, the output (III) (Fig. 1): (I) Endogenous variables (materials): This part includes variables, which belong to the steel maker’s responsibility. These are mainly steel composition and thermomechanical treatment for achieving optimal properties. These general characteristics are allotropic transformation temperature A1 &Ac3 , initial precipitation and its dissolution temperature, the other thermal properties, etc. (II) Exogenous variables (processing): This part includes welding parameters, particularly, welding energy, type of process, welding speed, initial temperature, interpass temperature, geometry of deposit, etc. (III) The output (final result): This part gives mechanical and metallurgical characteristics of welded structures. In the view of the schematic presentation given in Fig. 1, following questions will be answered: Is it possible to predict the qualitative effect of each input variable on the final result? All other parameters being constant, what is the effect of the increase or decrease in welding energy or in initial tem-
479
(1)
where E is the welding energy (type of process), Ac1 is the ␣ → ␥ transformation starting temperature at heating (◦ C), Ac3 is the ␣ → ␥ transformation finishing temperature at heating (◦ C), Ar3 is the ␥ → ␣ transformation starting temperature at cooling (◦ C), t the sheet thickness, v the welding speed, θ 0 the initial temperature, etc. By differentiation, this relation can be written as: ∂F ∂F ∂F dAc3 dE + dt + dF = ∂E ∂t ∂Ac3 ∂F ∂F dAr3 + + dΘ0 + · · · (2) ∂Ar3 ∂Θ0 So, the general indications on the values of (∂F/∂X) can be presented in order to give practical and simple recommendations to the steel maker and the welding designer. Here, (∂F/∂X) (where X = input variable) indicates the partial deriving with respect to the considered variable. 3.1. Application of WLD to IF steels 3.1.1. WLD: effect of the variation of the welding parameters on the ferrite grain size in the HAZ As known, the ferrite grain size in HAZ of IF steels obtained after a welding process is function of input variables, such as transformation temperatures Ar3 at cooling, thickness t, welding energy E and initial temperature θ 0 , etc. [1,7].
Fig. 1. Effect of materials and processing variables on the final result (output) of a welded structure.
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E. Bayraktar, D. Kaplan / Journal of Materials Processing Technology 170 (2005) 477–486
In order to evaluate the effect of these input variables on the ferrite grain size during the TIG, LASER and resistance spot welding, a central working point corresponding to real welding conditions are taken and then the input parameters are varied around this point and thus the corresponding ferrite grain size variations may be estimated easily according to the variation of welding constitutive parameters. All calculations were made for a wide range of the most important input parameters and the central points were taken for TIG welding as the following: E = 0.95–4.75 kJ/cm and central point: 2.85 kJ/cm (welding linear energy); t = 0.5–1.5 mm and central point: 1 mm (thickness of the welded sheet); Ar3 = 500–900 ◦ C and central point: 700 ◦ C (transformation temperatures at cooling); θ 0 = 0–200 ◦ C and central point: 100 ◦ C (initial temperature), etc. For the resistance spot welding, input parameters and also the central points are: E = 1.68–8.5 kJ/cm and central point: 5 kJ/cm (welding linear energy); t = 0.5–1.5 mm and central point: 1 mm (thickness of the welded sheet); Ar3 = 500–900 ◦ C and central point: 700 ◦ C (transformation temperatures at cooling); θ 0 = 0–200 ◦ C and central point: 100 ◦ C (initial temperature), etc. For the LASER welding, input parameters and also the central points are: E = 0.95–4.75 kJ/cm and central point: 2.85 kJ/cm (welding linear energy); t = 0.5–1.5 mm and central point: 1 mm (thickness of the welded sheet); Ar3 = 500–900 ◦ C and central point: 700 ◦ C (transformation temperatures at cooling); θ 0 = 0–200 ◦ C and central point: 100 ◦ C (initial temperature), etc. Fig. 2a–c shows the variation of the ferrite grain size as a function of different input variables in TIG, LASER and resistance spot welding conditions, respectively. For the sake of simplicity, all of these input parameters were put together on a single diagram. But, care must be taken of the different scales for the input variables. It may be seen from these figures that welding energy has a strong influence: an increase in welding energy decreases the ferrite grain size for all welding processes used in this study. And also, an increase in transformation temperatures, Ar3 , increases the ferrite grain size. But this effect is more pronounced in LASER and resistance spot welding conditions compared to the TIG welding conditions due to the different cooling rates depending on the welding processes, the highest
Table 1 Schematic influence of various input parameters on the ferrite grain size in HAZ (IFS) Input variable
Welding process
Influence (in the case of an increase of the input variable)
E (kJ/cm) ∂dα/∂E
TIG RSW LASER
Favourable Favourable Favourable
θAr3 (◦ C) ∂dα/∂θAr3
TIG RSW LASER
Detrimental Detrimental (pronounced) Detrimental (more pronounced)
Θ0 (◦ C) ∂dα/∂θ 0
TIG RSW LASER
Favourable Favourable Favourable
t (mm) ∂dα/∂t
TIG RSW LASER
Slightly detrimental Detrimental Detrimental (pronounced)
in LASER welding process. However, the influences of the sheet thickness and initial temperature are of the same level in TIG and RSW welding conditions. These effects are more pronounced in LASER welding process [1,7]. The final results (outputs) concerning the influences of the different input variables may be presented in the form of a table for simplicity. As an example, such evaluation carried on the seven industrial grades of IF steel is given in Table 1 for the three welding processes. 3.1.2. WLD: effect of the variation of the welding parameters on the thermal gradient (G) in the HAZ The G values were evaluated by means of an analytic model at different welding conditions (TIG, LASER and RSW). A simplified solution was used for the welding of thin sheets, IFS [6,7]: ηQ 1 2 θ(x,t) − θ0 = (3) e−x /4at 1/2 vdρc (4πat) where x is a distance to the fusion line, t the time for a given point, θ the given temperature at a point during the thermal cycle, θ 0 the initial temperature, a the thermal diffusivity, ρ the specific mass, c the specific heat, v the welding speed, Q the power of the heat source (VI), η the thermal efficiency depending on welding process and geometry and d is the sheet thickness. The temperature evolution was calculated as a function of time and distance from the fusion zone by means of the Eq. (1) at the experimental conditions of the each welding processes.1 Calculated and measured values obtained on the IFS samples were compared. The cooling parameter deter700 = 10 s) is very close to mined by this calculation (t300 700 the experimental values (t300 = 8–10 s). These parameters depend only slightly on the maximum temperature and define 1 The values used for the calculation are: θ = 940 ◦ C, θ = 20 ◦ C, m 0 t = 0.9 mm, ρc = 0.005 J mm−3 ◦ C−1 , a = 8 mm2 s−1 and v = 40 cm/min. And different thermal efficiency (η) is used depending on welding process.
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Fig. 2. Welding limit diagram, IFS: influence of different input variables on the ferrite grain size in TIG (a), LASER (b) and resistance spot welding (RSW) (c).
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Fig. 3. Welding limit diagram, IFS: influence of different input variables on the thermal gradient (G) in TIG (a), LASER (b) and resistance spot welding (RSW) (c).
E. Bayraktar, D. Kaplan / Journal of Materials Processing Technology 170 (2005) 477–486
thermal conditions in the HAZ. The cooling rate is even more 700 = 4–10 s) in LASER and spot welds. These rapid (t300 values are often only obtained by means of models or extrapolations from the data obtained on the microstructure, because it is difficult to determine these values experimentally. This model was then used for deriving the parameters, which define the thermal conditions, prevailed in HAZ during the grain growth. The thermal gradient, G, values for TIG and LASER welding processes were then calculated next to a point, xm , where the maximum temperature, θ m , is attained, when t = tm G=
dθ dx
√ − 2πe(θm − θ0 )2 dρc (xm , tm ) = E
(4)
where E is the linear welding heat input (welding ηUI ηQ power/welding speed) v = v .
483
In the same way, the thermal gradient is defined for resistance spot welding by πedρc(θm − θ0 )2 dθ =− (5) G= dx ηQ where Q is power of heat source (ηUIt) and d is the thickness of the sheet. All calculations for G values were made for the TIG, LASER and RSW welding conditions by using the same input parameters with that mentioned in Section 3.1.2. All of these input parameters were presented on a single welding limit diagram. So the variation of the thermal gradient values (G) as a function of different input variables in TIG, LASER and resistance spot welding conditions are shown in Fig. 3a–c, respectively. It seems from these figures that the influence of all the input parameters is more pronounced in LASER welding process.
Fig. 4. Influence of the chemical composition on the ferrite grain size (a) and the (␥ → ␣) transformation temperature (θAr3 ) (b), IFS.
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3.1.3. Effect of the steel composition on the ferrite grain size in the HAZ and on the (γ → α) transformation temperature (θAr3 ) A parallel approach was made to evaluate the influence of the chemical composition on the ferrite grain size and the (␥ → ␣) transformation temperature (θAr3 ) for the IF steels for comparing the tendencies shown in the preceding sections (Fig. 4a and b). The measurements of the ferrite grain size were carried out on the RSW structures of IFS and the (␥ → ␣) transformation temperature (θAr3 ) were measured by means of thermal cycles performed on a high-speed dilatometer (DT1000), which is based on direct radiation heating on the IFS samples [1,7,8]. These simple diagrams are very similar to the ones given in the previous figures and illustrate the variations of the grain size (dα) and the (␥ → ␣) transformation temperature (θAr3 )
depending on the different parameters, which play an important role on the welded structure. From then, it seems these diagrams are very useful and efficiency in manufacturing engineering in order to propose a practical chart to the welding designer for understanding tendencies in a multivariable system. 3.2. Application of the WLD to C–Mn steels 3.2.1. WLD: effect of the variation of the welding parameters on the microstructure; prediction of ICHAZ and CGHAZ Analysing of the local microstructures and predicting of the toughness levels in the HAZ should be made for a wide range of the input variables, such as initial temperature (θ 0 ), critical temperature for M-A dissolution (θ 1 ), critical tem-
Fig. 5. Welding limit diagram, C–Mn steel: influence of different input variables on the fraction of the ICHAZ (a) and the CGHAZ (b).
E. Bayraktar, D. Kaplan / Journal of Materials Processing Technology 170 (2005) 477–486
perature for austenite grain coarsening (θ 3 ), welding linear energy (E), weld metal radius (R), because these parameters have more physical significances on the critical HAZ. So, the calculation of the percentage of the special phases (ICHAZ and CGHAZ) should be made at a certain distance from fusion line on the HAZ. This distance is usually considered to be 0.5 mm, because it is a common specification in industry (pipeline and off shore) for COD testing and also in accordance with IIW recommendation for impact testing (Charpy-V) in HAZ [13]. For the sake of simplicity and mechanical and metallurgical coherency, an efficient model is described as the following: In order to evaluate the influence of the most important input variables on the ICHAZ and CGHAZ of the C–Mn steels in multipass welding, a central working point corresponding to real welding conditions are taken and then, the variation of the fraction of ICHAZ and CGHAZ may be calculated. So, the variations of the fraction of these intercritical zones at a distance of 0.5 mm from the fusion line are presented in Fig. 5a and b depending on the different input parameters by practical and understandable diagrams. As shown in these figures, the range of input parameters and the central point were taken as the following: E = 5–65 kJ/cm and central point: 35 kJ/cm; θ 1 = 500–700 ◦ C and central point: 600 ◦ C; θ 0 = 20–160 ◦ C and central point: 90 ◦ C; R = 3–7 mm and central point: 5 mm; θ 3 = 1000–1400 ◦ C and central point: 1200 ◦ C. As can be seen from Fig. 5, welding energy level (E) should be increased in order to reduce the fraction of intercritical zone or interpass temperature (θ 0 ) should be decreased to obtain optimal fraction values for ICHAZ. However, variations of θ 1 and θ 3 have no effect on the fraction of ICHAZ
485
in the considered range of this study [2,8]. However, it seems that the situation is contrary for the CGHAZ fraction. The parameter of the welding energy (E) has a very detrimental effect and interpass temperature (θ 0 ) has a slight beneficial one. But, critical temperature for austenite grain coarsening (θ 3 ) must be decreased to reduce the fraction of CGHAZ. Additionally, systematic combinations of extreme values of these input variables can be taken for a good evaluation of general tendencies or mean slope of each input variable. And then all the other variables being constant, the mean slope of a variable can be calculated as follows: (output) , X where X is one of the input variables quoted just above. By this way, evaluation of the variables may be more clear, for example, in order to understand if an increase of the considered variable is beneficial or detrimental for toughness properties of a welded structure by means of the final result (output). In this application, every 1 kJ/cm of increase in heat input (E) should decrease the percentage of ICHAZ by roughly 0.03–0.2%. 3.3. A typical application of WLD to IFS As can be seen from Fig. 2, the ferrite grain size becomes very important in certain conditions, which decreases toughness value of the welded structure. Some critic values and their limits may be explained in terms of welding conditions (for example, the couple of welding linear energy versus thickness of the steel sheet) to avoid the grain growth phenomenon for a given composition. Fig. 6 shows a typical example of another type of the welding limit diagram allowing to provide the grain growth
Fig. 6. Welding limit diagram: conditions of the appearance of large grain during the TIG welding of different grades of IF steels.
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conditions during the TIG welding of some grades of IF steel [7]. The appearance of the large grains in the grades of IF-B occurs only in very special conditions, which never arise in practical applications (small energy and large thickness). So, grey zones correspond to the appearance of the large grain size of the ferrite [1,7]. In fact, general view of the presented examples indicates that the approach allows providing sufficiently the limits for a given composition and a chosen welding process.
4. Conclusion - A new type of welding limit diagrams was developed by means of the model proposed based on thermal, metallurgical and mechanical background. This model can work easily on an ordinary PC type computer. - It is a useful tool for evaluating of microstructure particularly in HAZ for a given set of the welding conditions and also material characteristics. - This model is a simple and an efficient way to separate the responsibilities of the steel maker for the selection of steel to be used and welding designer for the selection of the welding conditions to work in a safety zone in order to increase the reliability of the welded structures. - There is a good agreement when comparing the predictions of the model and the results of the experiments carried out in this study as well as of these from the literature. These welding limit diagrams are very satisfying taking into account the simplicity of the proposed model.
Acknowledgements The authors thank Mr. J.P. Fouquet and Mr. J. Claire from IRSID for the technical support for the realisation of this work. References [1] E. Bayraktar, Research Report IRSID, no. 120151 (1998). [2] L. Devillers, D. Kaplan, P. Testard, Research Report IRSID, no. 91316 (1991). [3] I. Hrivnak, in: H. Cerjak (Ed.), Modelling of LBZ (local brittle zone) in Heavy Steel Plate, The Institute of Materials, 1997, ISBN 186125010X, pp. 218–225. [4] H. Badhesia, Models for the elementary mechanical properties of steel welds, Mathematical modelling of weld phenomena 3, reference 3, 1997, pp. 229–284. [5] D. Kaplan, D. Cloud-Castillo, Research Report, IRSID, no. 97.07 (1997). [6] Ø. Grong, Metallurgical Modelling of Welding, The Institute of Materials, 1994, ISBN 0901716375. [7] E. Bayraktar, Grain growth mechanism in IF steels during the welding, Research Report IRSID/CNAM, Arts et M´etiers, MPM 00-2714 (2000). [8] B. Antolovich, D. Kaplan, Research Report, IRSID, no. 96.04 (1996). [9] K. Ichikawa, H. Badhesia, Modelling of allotriomorphic ferrite in steel welds, reference 3, 1997, pp. 181–194. [10] J.C. Ion, Modelling of laser welding of C–Mn steels, reference 3, 1997, pp. 917–931. [11] E. Bayraktar, D. Kaplan, M. Grumbach, Application of impact tensile testing to the welded thin sheets, J. Mater. Process. Technol. 145 (2004) 27–39. [12] M. Toyoda, F. Minami, Y. Yamaguchi, K. Amano, Tempering effect on HAZ toughness of multi-layered welds, The Publication of IIW, Documentation number: X-1193-89 (1997). [13] Documentation of IIS/IIW, no. IX-475-75 (1997).
Parametric approach model for determining welding conditions: New type of welding limit diagrams (WLD) Emin Bayraktar a,∗ , Dominique Kaplan b a
Supmeca/LISMMA-Paris, School of Mechanical and Manufacturing Engineering, Saint Ouen, France b ARCELOR GROUP, Paris, France Received 5 April 2004; received in revised form 5 April 2005; accepted 13 June 2005
Abstract A simple and easily understandable model was developed for predicting the relative importance of different factors (composition of the steels and welding processing conditions) in order to obtain an efficient welding joint. An application on the interstitial free (IF) steel sheets welded by LASER, TIG and also by resistance spot welding (RSW) for automotive industry as well as an application of multipass welds of structural steels for offshore and pressure vessel are given in this study. This model is based on thermal, metallurgical and mechanical and also in situ test conditions. It operates easily on the PC type computer. This approach is an efficient way to separate the responsibilities of the steel maker and welding designer for increasing the reliability of the welded structures. The construction of welding limit diagrams (WLD) that allows us to predict the values of the parameters in order to obtain an efficient welding joint is presented. © 2005 Elsevier B.V. All rights reserved. Keywords: Modelling; Welding conditions; Materials parameters; Welding limit diagrams (WLD)
1. Introduction The assessment of the safety of welded structures is carried out by commonly known fracture mechanic tests, particularly in heat affected zones (HAZ), such as crack tip opening displacement (CTOD), which is very sensitive to local brittle zones and wide plate testing [1–6,9–11]. In spite of long time required to conduct these tests, for finding practical data showing the welding (plate) conditions or a practical information giving a relation between chemical composition and welding conditions (multipass) in order to evaluate the welded structures in practical point of view is a real problem in many industrial applications, such as pipeline, offshore, marine engineering, pressure vessel, energy or other metallic constructions. Additionally, the toughness of HAZ is strongly function of the length of the local brittle zone, which deteriorates toughness in coarse grain HAZ (CGHAZ) and in intercritically HAZ (ICCGHAZ) and the critical value of the ∗
Corresponding author. E-mail address: [email protected] (E. Bayraktar).
0924-0136/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jmatprotec.2005.06.034
local brittle zone depends on the test conditions (failure mode, specimen geometry and temperature) as well as mechanical properties of the different microstructures intercepted. In other words, fracture initiation in welded structures has a probabilistic nature, rather than a deterministic one [12]. It seems that, the improvement the toughness of HAZ in multipass welds necessitates to reduce of the percentage of the local brittle zones. On the other hand, resistance spot welding (RSW) is the most widespread process applied on modern thin sheet steels or the interstitial free steels (IFS) used in the automotive industry. Recently, the development of tailored blanks by means of LASER welding and the general application of the LASER welding in this area have also occurred. Generally, IF steels have extremely low values of C and N contents, making them particularly suitable for deep drawing. However, for these steels, the appearance of the unusual grain growth at the HAZ has been reported. The presence this zone could decrease the fatigue resistance of spot welds by about 20%. Additionally, the impact tensile tests involving a notch localised in the grain growth zone display intergranular frac-
E. Bayraktar, D. Kaplan / Journal of Materials Processing Technology 170 (2005) 477–486
478
Nomenclature a Ac3 Ar3 c d e E G
Q t 700 t300 v x
thermal diffusivity (mm2 s−1 ) ␣ → ␥ transformation temperature (at heating) (◦ C) ␥ → ␣ transformation starting temperature (at cooling) (◦ C) specific heat sheet thickness (mm) basic logarithm linear welding heat input (kJ/cm) (welding ηQ power/welding speed) ηUI v = v dθ/dx (◦ C/mm) thermal gradient (At any given moment, this variable describes the “thermal environment” of a given point. A high “G” value indicates naturally high possibilities of heat evacuation by means of the surrounding zones.) power of the heat source (W) (VI for TIG and ηUIt for resistance spot weld) time for a given point (s) cooling conditions (s) (time elapsed from 700 to 300 ◦ C) welding speed (cm/min) distance to the fusion line for a given point (mm)
Greek letters dαL ferrite grain size in longitudinal direction (m) dαT ferrite grain size in transversal direction (m) η thermal efficiency depending on welding process and geometry (%) θ given temperature at a point during the thermal cycle (◦ C) θ0 initial temperature (◦ C) ρ specific mass ρc J mm−3 ◦ C−1
ture surface, by which the facet size corresponds to the grain size. Although there are a lot of studies on the assessment of the safety of welded structures related to HAZ but there is little information on the estimation of microstructure in the real welds and on the correlation of these values with welding conditions. Many researches concentrate on the thermal simulations for understanding metallurgical mechanism in a given welding conditions supported by FEM analysis but they are not sufficient to explain the complex situation met in many welding processes (e.g. multipass) or new steel compositions in a practical and easily understandable way. The objective of this paper is centred on a parametric approach model based on thermal, metallurgical and mechanical background and also in situ test conditions. This analytical approach is an efficient way to separate the responsibilities
of the steel maker and welding designer for increasing the reliability of the welded structures [7,8]. All of the works presented here are performed easily on an ordinary PC type computer.
2. Experimental study 2.1. Materials and welding process Different industrial grades of interstitial free (IF) steels whose thickness varies between 0.65 and 0.9 mm have been studied. The carbon values vary from 1.4 × 10−3 to 5 × 10−3 wt% and Mn values vary from 100 × 10−3 to 200 × 10−3 wt%. The grain growth in HAZ has been studied by means of the following techniques: - Gas tungsten arc welding (GTAW) has been performed with a voltage of 10 V, an intensity of 65 A, a welding rate of 40 cm/min and shielding argon gas (12 l/min). Considering the coefficient of thermal efficiency of the process (η ≈ 50%), the corresponding linear energy varies from 0.75 to 0.95 kJ/cm. - Resistance spot welding experiments were performed with a voltage of 1 V, an intensity of 6000 A and a welding time of 30 cycles (50 Hz). Spot diameter was approximately 4 mm. - The LASER welding experiments were performed with a CO2 LASER with powers ranging from 1.5 to 4 kW and with welding rates from 0.6 to 9 m/min. Considering the coefficient of thermal efficiency of the process (η ≈ 15%), the corresponding linear energy varies from 0.1 to 4 kJ/cm. Additionally, different grades of C–Mn steels have been studied. The carbon values vary from 70 × 10−3 to 130 × 10−3 wt% and Mn values vary from 500 × 10−3 to 1600 × 10−3 wt%. In the case of multipass welding, the values of thermal efficiency of the process was taken as η ≈ 15% and the corresponding welding linear energy varies from 5 to 65 kJ/cm. 2.2. Position of the problem First of all, estimation of a welded structure based on thermal, metallurgical and mechanical background and also in situ test conditions necessitates to know their suitability and limits with respect to each other at the same time. So, a model that includes all these parameters should be a simple and practical guide to the steel makers or to the weld designers. Secondly, the type of microstructure of a weld joint is function of many input parameters, which belong to the steel maker or weld designer (customer). The final result after a welding process (output) depends on the type, the toughness and the geometrical distribution of the microstructures.
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Finally, an analytical approach is given to establish a relation between them and to put together all of the input parameters on a single diagram for presenting simply the final result. In the following section, all of these input parameters will be expressed in the form the influence diagrams, which are called new type of welding limit diagrams (WLD).
perature on the grain size and what about the percentage of intercritical zone? These questions may be multiplied with many input variables (I and II parameters) quoted just above. The final result (output) can be given as a function of types I and II input variables as follows: F = f (E, t, Ac1 , Ac3 , Ar3 , θ0 , θ1 , θ3 , v, etc.)
3. Results and discussion The problem can be presented with a system of three parts with many input variables coming from the steel maker’s responsibility (I) and weld designer or customer’s responsibility (II) and the final results, the output (III) (Fig. 1): (I) Endogenous variables (materials): This part includes variables, which belong to the steel maker’s responsibility. These are mainly steel composition and thermomechanical treatment for achieving optimal properties. These general characteristics are allotropic transformation temperature A1 &Ac3 , initial precipitation and its dissolution temperature, the other thermal properties, etc. (II) Exogenous variables (processing): This part includes welding parameters, particularly, welding energy, type of process, welding speed, initial temperature, interpass temperature, geometry of deposit, etc. (III) The output (final result): This part gives mechanical and metallurgical characteristics of welded structures. In the view of the schematic presentation given in Fig. 1, following questions will be answered: Is it possible to predict the qualitative effect of each input variable on the final result? All other parameters being constant, what is the effect of the increase or decrease in welding energy or in initial tem-
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(1)
where E is the welding energy (type of process), Ac1 is the ␣ → ␥ transformation starting temperature at heating (◦ C), Ac3 is the ␣ → ␥ transformation finishing temperature at heating (◦ C), Ar3 is the ␥ → ␣ transformation starting temperature at cooling (◦ C), t the sheet thickness, v the welding speed, θ 0 the initial temperature, etc. By differentiation, this relation can be written as: ∂F ∂F ∂F dAc3 dE + dt + dF = ∂E ∂t ∂Ac3 ∂F ∂F dAr3 + + dΘ0 + · · · (2) ∂Ar3 ∂Θ0 So, the general indications on the values of (∂F/∂X) can be presented in order to give practical and simple recommendations to the steel maker and the welding designer. Here, (∂F/∂X) (where X = input variable) indicates the partial deriving with respect to the considered variable. 3.1. Application of WLD to IF steels 3.1.1. WLD: effect of the variation of the welding parameters on the ferrite grain size in the HAZ As known, the ferrite grain size in HAZ of IF steels obtained after a welding process is function of input variables, such as transformation temperatures Ar3 at cooling, thickness t, welding energy E and initial temperature θ 0 , etc. [1,7].
Fig. 1. Effect of materials and processing variables on the final result (output) of a welded structure.
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In order to evaluate the effect of these input variables on the ferrite grain size during the TIG, LASER and resistance spot welding, a central working point corresponding to real welding conditions are taken and then the input parameters are varied around this point and thus the corresponding ferrite grain size variations may be estimated easily according to the variation of welding constitutive parameters. All calculations were made for a wide range of the most important input parameters and the central points were taken for TIG welding as the following: E = 0.95–4.75 kJ/cm and central point: 2.85 kJ/cm (welding linear energy); t = 0.5–1.5 mm and central point: 1 mm (thickness of the welded sheet); Ar3 = 500–900 ◦ C and central point: 700 ◦ C (transformation temperatures at cooling); θ 0 = 0–200 ◦ C and central point: 100 ◦ C (initial temperature), etc. For the resistance spot welding, input parameters and also the central points are: E = 1.68–8.5 kJ/cm and central point: 5 kJ/cm (welding linear energy); t = 0.5–1.5 mm and central point: 1 mm (thickness of the welded sheet); Ar3 = 500–900 ◦ C and central point: 700 ◦ C (transformation temperatures at cooling); θ 0 = 0–200 ◦ C and central point: 100 ◦ C (initial temperature), etc. For the LASER welding, input parameters and also the central points are: E = 0.95–4.75 kJ/cm and central point: 2.85 kJ/cm (welding linear energy); t = 0.5–1.5 mm and central point: 1 mm (thickness of the welded sheet); Ar3 = 500–900 ◦ C and central point: 700 ◦ C (transformation temperatures at cooling); θ 0 = 0–200 ◦ C and central point: 100 ◦ C (initial temperature), etc. Fig. 2a–c shows the variation of the ferrite grain size as a function of different input variables in TIG, LASER and resistance spot welding conditions, respectively. For the sake of simplicity, all of these input parameters were put together on a single diagram. But, care must be taken of the different scales for the input variables. It may be seen from these figures that welding energy has a strong influence: an increase in welding energy decreases the ferrite grain size for all welding processes used in this study. And also, an increase in transformation temperatures, Ar3 , increases the ferrite grain size. But this effect is more pronounced in LASER and resistance spot welding conditions compared to the TIG welding conditions due to the different cooling rates depending on the welding processes, the highest
Table 1 Schematic influence of various input parameters on the ferrite grain size in HAZ (IFS) Input variable
Welding process
Influence (in the case of an increase of the input variable)
E (kJ/cm) ∂dα/∂E
TIG RSW LASER
Favourable Favourable Favourable
θAr3 (◦ C) ∂dα/∂θAr3
TIG RSW LASER
Detrimental Detrimental (pronounced) Detrimental (more pronounced)
Θ0 (◦ C) ∂dα/∂θ 0
TIG RSW LASER
Favourable Favourable Favourable
t (mm) ∂dα/∂t
TIG RSW LASER
Slightly detrimental Detrimental Detrimental (pronounced)
in LASER welding process. However, the influences of the sheet thickness and initial temperature are of the same level in TIG and RSW welding conditions. These effects are more pronounced in LASER welding process [1,7]. The final results (outputs) concerning the influences of the different input variables may be presented in the form of a table for simplicity. As an example, such evaluation carried on the seven industrial grades of IF steel is given in Table 1 for the three welding processes. 3.1.2. WLD: effect of the variation of the welding parameters on the thermal gradient (G) in the HAZ The G values were evaluated by means of an analytic model at different welding conditions (TIG, LASER and RSW). A simplified solution was used for the welding of thin sheets, IFS [6,7]: ηQ 1 2 θ(x,t) − θ0 = (3) e−x /4at 1/2 vdρc (4πat) where x is a distance to the fusion line, t the time for a given point, θ the given temperature at a point during the thermal cycle, θ 0 the initial temperature, a the thermal diffusivity, ρ the specific mass, c the specific heat, v the welding speed, Q the power of the heat source (VI), η the thermal efficiency depending on welding process and geometry and d is the sheet thickness. The temperature evolution was calculated as a function of time and distance from the fusion zone by means of the Eq. (1) at the experimental conditions of the each welding processes.1 Calculated and measured values obtained on the IFS samples were compared. The cooling parameter deter700 = 10 s) is very close to mined by this calculation (t300 700 the experimental values (t300 = 8–10 s). These parameters depend only slightly on the maximum temperature and define 1 The values used for the calculation are: θ = 940 ◦ C, θ = 20 ◦ C, m 0 t = 0.9 mm, ρc = 0.005 J mm−3 ◦ C−1 , a = 8 mm2 s−1 and v = 40 cm/min. And different thermal efficiency (η) is used depending on welding process.
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Fig. 2. Welding limit diagram, IFS: influence of different input variables on the ferrite grain size in TIG (a), LASER (b) and resistance spot welding (RSW) (c).
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Fig. 3. Welding limit diagram, IFS: influence of different input variables on the thermal gradient (G) in TIG (a), LASER (b) and resistance spot welding (RSW) (c).
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thermal conditions in the HAZ. The cooling rate is even more 700 = 4–10 s) in LASER and spot welds. These rapid (t300 values are often only obtained by means of models or extrapolations from the data obtained on the microstructure, because it is difficult to determine these values experimentally. This model was then used for deriving the parameters, which define the thermal conditions, prevailed in HAZ during the grain growth. The thermal gradient, G, values for TIG and LASER welding processes were then calculated next to a point, xm , where the maximum temperature, θ m , is attained, when t = tm G=
dθ dx
√ − 2πe(θm − θ0 )2 dρc (xm , tm ) = E
(4)
where E is the linear welding heat input (welding ηUI ηQ power/welding speed) v = v .
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In the same way, the thermal gradient is defined for resistance spot welding by πedρc(θm − θ0 )2 dθ =− (5) G= dx ηQ where Q is power of heat source (ηUIt) and d is the thickness of the sheet. All calculations for G values were made for the TIG, LASER and RSW welding conditions by using the same input parameters with that mentioned in Section 3.1.2. All of these input parameters were presented on a single welding limit diagram. So the variation of the thermal gradient values (G) as a function of different input variables in TIG, LASER and resistance spot welding conditions are shown in Fig. 3a–c, respectively. It seems from these figures that the influence of all the input parameters is more pronounced in LASER welding process.
Fig. 4. Influence of the chemical composition on the ferrite grain size (a) and the (␥ → ␣) transformation temperature (θAr3 ) (b), IFS.
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3.1.3. Effect of the steel composition on the ferrite grain size in the HAZ and on the (γ → α) transformation temperature (θAr3 ) A parallel approach was made to evaluate the influence of the chemical composition on the ferrite grain size and the (␥ → ␣) transformation temperature (θAr3 ) for the IF steels for comparing the tendencies shown in the preceding sections (Fig. 4a and b). The measurements of the ferrite grain size were carried out on the RSW structures of IFS and the (␥ → ␣) transformation temperature (θAr3 ) were measured by means of thermal cycles performed on a high-speed dilatometer (DT1000), which is based on direct radiation heating on the IFS samples [1,7,8]. These simple diagrams are very similar to the ones given in the previous figures and illustrate the variations of the grain size (dα) and the (␥ → ␣) transformation temperature (θAr3 )
depending on the different parameters, which play an important role on the welded structure. From then, it seems these diagrams are very useful and efficiency in manufacturing engineering in order to propose a practical chart to the welding designer for understanding tendencies in a multivariable system. 3.2. Application of the WLD to C–Mn steels 3.2.1. WLD: effect of the variation of the welding parameters on the microstructure; prediction of ICHAZ and CGHAZ Analysing of the local microstructures and predicting of the toughness levels in the HAZ should be made for a wide range of the input variables, such as initial temperature (θ 0 ), critical temperature for M-A dissolution (θ 1 ), critical tem-
Fig. 5. Welding limit diagram, C–Mn steel: influence of different input variables on the fraction of the ICHAZ (a) and the CGHAZ (b).
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perature for austenite grain coarsening (θ 3 ), welding linear energy (E), weld metal radius (R), because these parameters have more physical significances on the critical HAZ. So, the calculation of the percentage of the special phases (ICHAZ and CGHAZ) should be made at a certain distance from fusion line on the HAZ. This distance is usually considered to be 0.5 mm, because it is a common specification in industry (pipeline and off shore) for COD testing and also in accordance with IIW recommendation for impact testing (Charpy-V) in HAZ [13]. For the sake of simplicity and mechanical and metallurgical coherency, an efficient model is described as the following: In order to evaluate the influence of the most important input variables on the ICHAZ and CGHAZ of the C–Mn steels in multipass welding, a central working point corresponding to real welding conditions are taken and then, the variation of the fraction of ICHAZ and CGHAZ may be calculated. So, the variations of the fraction of these intercritical zones at a distance of 0.5 mm from the fusion line are presented in Fig. 5a and b depending on the different input parameters by practical and understandable diagrams. As shown in these figures, the range of input parameters and the central point were taken as the following: E = 5–65 kJ/cm and central point: 35 kJ/cm; θ 1 = 500–700 ◦ C and central point: 600 ◦ C; θ 0 = 20–160 ◦ C and central point: 90 ◦ C; R = 3–7 mm and central point: 5 mm; θ 3 = 1000–1400 ◦ C and central point: 1200 ◦ C. As can be seen from Fig. 5, welding energy level (E) should be increased in order to reduce the fraction of intercritical zone or interpass temperature (θ 0 ) should be decreased to obtain optimal fraction values for ICHAZ. However, variations of θ 1 and θ 3 have no effect on the fraction of ICHAZ
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in the considered range of this study [2,8]. However, it seems that the situation is contrary for the CGHAZ fraction. The parameter of the welding energy (E) has a very detrimental effect and interpass temperature (θ 0 ) has a slight beneficial one. But, critical temperature for austenite grain coarsening (θ 3 ) must be decreased to reduce the fraction of CGHAZ. Additionally, systematic combinations of extreme values of these input variables can be taken for a good evaluation of general tendencies or mean slope of each input variable. And then all the other variables being constant, the mean slope of a variable can be calculated as follows: (output) , X where X is one of the input variables quoted just above. By this way, evaluation of the variables may be more clear, for example, in order to understand if an increase of the considered variable is beneficial or detrimental for toughness properties of a welded structure by means of the final result (output). In this application, every 1 kJ/cm of increase in heat input (E) should decrease the percentage of ICHAZ by roughly 0.03–0.2%. 3.3. A typical application of WLD to IFS As can be seen from Fig. 2, the ferrite grain size becomes very important in certain conditions, which decreases toughness value of the welded structure. Some critic values and their limits may be explained in terms of welding conditions (for example, the couple of welding linear energy versus thickness of the steel sheet) to avoid the grain growth phenomenon for a given composition. Fig. 6 shows a typical example of another type of the welding limit diagram allowing to provide the grain growth
Fig. 6. Welding limit diagram: conditions of the appearance of large grain during the TIG welding of different grades of IF steels.
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conditions during the TIG welding of some grades of IF steel [7]. The appearance of the large grains in the grades of IF-B occurs only in very special conditions, which never arise in practical applications (small energy and large thickness). So, grey zones correspond to the appearance of the large grain size of the ferrite [1,7]. In fact, general view of the presented examples indicates that the approach allows providing sufficiently the limits for a given composition and a chosen welding process.
4. Conclusion - A new type of welding limit diagrams was developed by means of the model proposed based on thermal, metallurgical and mechanical background. This model can work easily on an ordinary PC type computer. - It is a useful tool for evaluating of microstructure particularly in HAZ for a given set of the welding conditions and also material characteristics. - This model is a simple and an efficient way to separate the responsibilities of the steel maker for the selection of steel to be used and welding designer for the selection of the welding conditions to work in a safety zone in order to increase the reliability of the welded structures. - There is a good agreement when comparing the predictions of the model and the results of the experiments carried out in this study as well as of these from the literature. These welding limit diagrams are very satisfying taking into account the simplicity of the proposed model.
Acknowledgements The authors thank Mr. J.P. Fouquet and Mr. J. Claire from IRSID for the technical support for the realisation of this work. References [1] E. Bayraktar, Research Report IRSID, no. 120151 (1998). [2] L. Devillers, D. Kaplan, P. Testard, Research Report IRSID, no. 91316 (1991). [3] I. Hrivnak, in: H. Cerjak (Ed.), Modelling of LBZ (local brittle zone) in Heavy Steel Plate, The Institute of Materials, 1997, ISBN 186125010X, pp. 218–225. [4] H. Badhesia, Models for the elementary mechanical properties of steel welds, Mathematical modelling of weld phenomena 3, reference 3, 1997, pp. 229–284. [5] D. Kaplan, D. Cloud-Castillo, Research Report, IRSID, no. 97.07 (1997). [6] Ø. Grong, Metallurgical Modelling of Welding, The Institute of Materials, 1994, ISBN 0901716375. [7] E. Bayraktar, Grain growth mechanism in IF steels during the welding, Research Report IRSID/CNAM, Arts et M´etiers, MPM 00-2714 (2000). [8] B. Antolovich, D. Kaplan, Research Report, IRSID, no. 96.04 (1996). [9] K. Ichikawa, H. Badhesia, Modelling of allotriomorphic ferrite in steel welds, reference 3, 1997, pp. 181–194. [10] J.C. Ion, Modelling of laser welding of C–Mn steels, reference 3, 1997, pp. 917–931. [11] E. Bayraktar, D. Kaplan, M. Grumbach, Application of impact tensile testing to the welded thin sheets, J. Mater. Process. Technol. 145 (2004) 27–39. [12] M. Toyoda, F. Minami, Y. Yamaguchi, K. Amano, Tempering effect on HAZ toughness of multi-layered welds, The Publication of IIW, Documentation number: X-1193-89 (1997). [13] Documentation of IIS/IIW, no. IX-475-75 (1997).