Developing predictive tools for friction stir weld quality assessment

Developing predictive tools for friction stir weld quality assessment K. V. Singh1, C. Hamilton*1 and S. Dymek2 This research programme explores predictive tools that assess friction stir weld quality in aluminium alloys through dynamic characterisation. The study focuses on the correlations between dynamic interrogations measures of friction stir welded panels with the weld energy, as welded mechanical properties and the microstructure. 7136-T76 aluminium extrusions were joined at unique weld energies, and to characterise and identify the friction stir welds through nondestructive techniques, theoretical modelling and lab scale dynamic testing were conducted to establish the correlation between the weld energy and the associated spectral characteristics of the beam (natural frequencies/mode shapes). In this non-destructive evaluation study, the modal parameters were measured and were correlated with the friction stir weld microstructure and the physical parameters of the welded components, such as axial and flexural rigidities. The viability of weld parameter identification and weld quality assessment of friction stir welding beams using dynamic interrogation techniques is demonstrated. Keywords: Dynamic characterisation, Weld quality, Aluminium, Friction stir welding

Introduction As the aerospace industry produces new and more efficient airframes, the need to provide high strength, lightweight alloys that meet the more aggressive design objectives for mechanical performance, manufacturability and service life arises. To that end, the aluminium industry has sought to develop alloys and heat treatments that combine superior mechanical properties with excellent resistance to exfoliation corrosion and stress corrosion cracking. One such alloy and temper combination is 7136-T76, an alloy produced by Universal Alloy Corporation based in Anaheim, CA. Aluminium 7136 contains higher levels of zinc than typical 7XXX alloys (8?4–9?4 wt-%) and contains zirconium (0?10–0?20 wt-%) as a microstructural stabiliser, similar to the 7X5X family of alloys. Produced in a -T76 temper, 7136 offers superior mechanical properties to 7075-T6 with an excellent and guaranteed exfoliation corrosion rating of EB per ASTM G 34. Table 1 displays the minimum tensile properties for 7136-T76 extrusions as a function of product thickness.1 The impact of friction stir welding (FSW) on the properties and structure of 7136-T76 is of primary importance. Invented in 1991 by the Welding Institute, FSW is a novel solid state joining process that is gaining popularity in the manufacturing sector.2,3 Friction stir welding utilises a rotating tool design to induce plastic 1 Miami University, Mechanical and Manufacturing Engineering, Oxford, OH 45056, USA 2 AGH University of Science and Technology, al. Mickiewicza 30, Krako´w 30059, Poland

*Corresponding author, email [email protected]

ß 2010 Institute of Materials, Minerals and Mining Published by Maney on behalf of the Institute Received 8 September 2009; accepted 15 November 2009 DOI 10.1179/136217109X12590746472571

flow in the base metals and essentially ‘stirs’ the pieces together. During the welding process, a pin, attached to the primary tool, is inserted into the joint with the shoulder of the rotating tool abutting the base metals. As the tool traverses the joint, the rotation of the shoulder under the influence of an applied load heats the metal surrounding the joint and with the rotating action of the pin induces metal from each workpiece to flow and form the weld. The microstructure resulting from the influence of plastic deformation and elevated temperature is characterised by a central weld nugget surrounded by a thermomechanically affected zone (TMAZ) and heat affected zone (HAZ). The welded joint is fundamentally defect free and displays excellent mechanical properties when compared to conventional fusion welds.4–7 The current status of FSW research has been well summarised by Mishra and Ma8 and Nandan et al.9 The microstructure resulting from FSW directly influences the overall mechanical behaviour of the welded structure. Hence, it is essential to assess and evaluate the quality of friction stir welds corresponding to different weld energies. Destructive and non-destructive techniques are of the paramount interest to industries and research communities to assess weld quality and to monitor the health of the welded structures. To date, however, limited research has been done in the area of non-destructive structural health monitoring techniques towards the characterisation of the friction stir welded sections.10 Vibration modal testing is one of the most common non-destructive testing methods. In such testing methods, the modal parameters, i.e. natural frequencies (eigenvalues) and mode shapes (eigenvectors), are

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measured without affecting the structural integrity. The basic concept of vibration based testing is that the modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical parameters of the structure (mass, damping, and stiffness). Therefore, changes in the physical parameters will be reflected as changes in the modal properties. Previous research has focused on detecting damage parameters (reflecting small changes in the overall physical parameters of the structure) using different non-destructive vibration based detection techniques.11,12 Through a similar approach, the fundamental problem addressed in this investigation is characterising the physical parameters associated with the friction stir weld zone by dynamic/vibration testing. It is assumed that the FSW microstructure impacts the physical properties of the overall structure due to changes in the local properties at the FSW zone. Even a small change in these physical parameters due to FSW may be detected from the perturbation in their original (baseline structure) spectral behaviour, i.e. shift in natural frequencies or change in the mode shapes, during dynamic analysis/measurement. Once the relationship between the change in physical parameters and its effect on the spectral behaviour are identified, then such relationships can be correlated to the weld parameters. Such non-destructive techniques, therefore, may become the basis for weld quality assessment and weld monitoring. For this study, five aluminium 7136-T76 beams of equal lengths, one baseline and four welded in the centre by FSW, were examined. It is assumed that the transverse rigidity (bending stiffness) of the welded zone is altered during the FSW process and can be directly related to the weld energy. For simplicity, it is also assumed that changes in cross sectional area and density of the beam are negligible. Static mechanical and dynamic tests were conducted to evaluate the physical parameters of the baseline and welded beams. A mathematical model, approximating each welded beam by finite element method, is developed, and parametric studies are conducted that correlate the weld energies with the changes in the natural frequencies of the beams. These natural frequency changes are further correlated to the change in the bending rigidity and hence the modulus of elasticity of the beams. Obtaining the first four natural frequencies of the welded and baseline beams (same length and boundary configurations), the transverse rigidity and the modulus of elasticity from the dynamic testing are estimated.

Developing predictive tools for friction stir weld quality assessment

a mechanical testing; b dynamic testing 1 Friction stir weld configurations

welded by the Edison Welding Institute (Columbus, OH). For mechanical testing, the extrusions were welded along the L direction in configuration shown in Fig. 1a, but for dynamic testing, the extrusions were welded in the LT direction as shown in Fig. 1b. With a weld velocity of 2?1 mm s21 and an applied force of 26?7 kN, unique welds were produced at the following tool rotation speeds: 175, 225, 250, 300, 350 and 400 rev min21. The diameter of the FSW tool shoulder was 17?8 mm, the pin diameter tapered linearly from 10?3 mm at the tool shoulder to 7?7 mm at the tip and the pin depth was 6?1 mm. More specific details of the tool design are proprietary to Edison Welding Institute, but Mishra and Ma have reviewed many of the common FSW tool designs that are indicative of that utilised in this investigation.8,13,14

Mechanical testing From the welded panels, full thickness tensile samples were excised perpendicular to the friction stir weld. In this orientation, the load is applied transverse to the weld direction and across all microstructural regions associated with the welding process, i.e. weld nugget, HAZ and TMAZ. In addition to the welded tensile specimens, tensile bars of the same geometry and dimensions were also excised from an area away from the weld region for baseline property comparison. All tensile tests were performed in accordance with ASTM E 8 utilising an Instron 5867 screw driven test frame with a 30 kN load cell and a 0?001–500 mm min21 speed range. Specimen extension was measured by means of a 25 mm extensometer attached to the reduced section. The yield strength sy was obtained by the 0?2% offset method Rp0?2, and the elastic modulus E was determined by fitting a linear regression to the elastic region of the

Experimental procedure Beam fabrication Aluminium 7136-T76 extrusions with a thickness of 6?35 mm and a width of 101?6 mm were obtained and

Table 1 Baseline mechanical properties of 7136-T76511 extrusions Thickness, mm 6?35–12?69

(6?34

12?70–19?04

19?05–38?09

Property

L

LT

L

LT

L

LT

L

LT

Tensile ultimate, MPa Tensile yield, MPa Compression yield, MPa

620 600 615

600 580 590

640 615 615

615 585 600

650 615 630

630 600 620

650 615 630

630 600 620


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2

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6 qi h 6 6 22h m ~ 6 420 6 54 4 {13h

22h

54

4h2

13h

13h

156

{3h2

{22h

(e)

{13h

3

7 {3h2 7 7 7 {22h 7 5 4h2

and

(2) 2

2 a schematic and nomenclature of welded beam for vibration testing and b equivalent finite element model of welded beam

stress–strain curve. The elongation e was determined by scribing marks with known separation within the reduced section before testing and measuring their separation after testing.

Dynamic testing Five beams, one baseline and four welded beams with various weld energies, were considered for vibration testing. Each beam had the same dimensions, as shown in Table 2. The beams were clamped at one end, assuring that all beams had the same clamped length and boundary condition. Ten locations along the length of the clamped beam were impinged by a modal hammer and the collocated frequency response function for each beam was extracted. Each location was struck three times and an averaging of impulse responses was carried out. For each beam, 10 collocated (impact and sensing at the same location) frequency response functions were then extracted by computing the transfer function of the input impulse and response using a triaxial accelerometer.

Mathematical modelling In order to analyse the effect of weld parameters on the natural frequencies of the beam, a traditional finite element model is utilised. The finite element approximation for a transversely vibrating beam, as shown in Fig. 2, can be obtained by expressing the transverse displacement of the beam element by the cubic interpolating functions (shape functions) as v(x)~L(x)T w

(1)

where L(x) is the Hermite cubic interpolating function, and w is the corresponding vector of nodal displacements. Using this shape function, the elemental mass and stiffness matrices for beam element can be obtained as Table 2 Material and physical parameters of beams for experiment and simulation Modulus of elasticity (baseline) E, GPa Density of the beam (baseline and welded), kg m23 Width of beam, m Thickness of beam, m Clamped length of beam, m Location of weld from the clamped end, m Length of weld zone, m Location of the weld from free end, m

70?4 2880 0?1016 0?01905 0?746125 0?418308 0?01905 0?310358

12 _ 6 ri 6 6 6h k(e) ~ 3 6 h 6 {12 4 6h

6h

{12

4h2

{6h

{6h

12

2h

2

{6h

6h

3

7 2h2 7 7 7 {6h 7 5 2 4h

After evaluating the elemental matrices, the global mass and stiffness matrices can be assembled for various boundary configurations leading to the system of equations corresponding to n element finite element models :: M wzKw~0 (3) where M and K are the final mass and stiffness matrices, respectively, of dimension (2n62n) for a fixed free configuration. The nodal degree of freedom is denoted by w5(w2 h2 w3 … wnz1 hnz1) of dimension (2n61), and n is the number of discrete elements of the finite element model of the beam. The natural frequencies of the beam (baseline or welded) can then be evaluated by solving the eigenvalue problem K{v2 M v~0 (4) where vi for i51, 2, … 2n are the natural frequencies of the beam (in rad s21), and vi are the corresponding mode shapes. For the welded beam, it is assumed that the elemental stiffness matrices are changed by a factor of a in the weld nugget/TMAZ and b in each of the HAZ, representing the change in rigidity of the structure depending upon the weld parameters. In order to accommodate the effects of FSW, the governing eigenvalue problem is modified as ~ ~ (5) K{v2 M v~0 with the elemental mass and stiffness matrices associated with the weld and HAZs modified as m{1 m m mz1 km{1 welded ~bkbaseline , kwelded ~akbaseline , kwelded

~bkmz1 baseline

(6)

where the mth element represents the weld nugget/ TMAZ and (m21)th and (mz1)th elements corresponds to the HAZ. For simulation and estimation of natural frequencies, the parameters listed in Table 2 are used. The lower four natural frequencies of the baseline and welded beams with varying a and b are computed and the percentage change in the natural frequencies are calculated as ðf Þ {ðfi Þweld , for i~1,2,3,4 fî ~100| i baseline ðf i Þ

(7)

baseline

The characteristics of the change in the natural frequencies with respect to various combinations of a and b values are shown in Fig. 3. It is clear that for a fixed free boundary configuration, the first and third


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3 Prediction of change in natural frequencies with respect to change in transverse rigidities at weld nugget/TMAZ and HAZ using finite element model

natural frequencies are less sensitive to the weld zones compared to second and fourth natural frequencies. Such an observation is helpful in deciding which lower natural frequencies from experiment can be used for prediction of weld characteristics. This model will be used to make a prediction of the change in transverse rigidity from the change in natural frequencies in a proceeding section. It must be noted, however, that this approach does not differentiate between all the factors that could contribute to changes in natural frequency, such as residual stress or microstructural differences after FSW.

workpiece, the bottom of the tool pin against thickness material and the pin surface against thickness material. Utilising this model, the energy per unit length of weld becomes El ~Ttotal

v vw

(8)

Although the applied force during FSW was set at 26?7 kN, real time data from the welding trials revealed that the load oscillated as the machine continuously corrected the load toward the set point. Consequently, the average load during welding deviated from the desired set point; therefore, the average load was determined from the recorded data for each weld condition and was utilised in the analysis of that condition. The recorded data did verify that the weld velocity remained constant at 2?1 mm s21 for all welding trials. Using a coefficient of sliding friction between aluminium and mild steel of 0?47,17 Table 3 summarises the average mechanical properties and the energy per unit length of weld determined for each tool rotation speed. The baseline material, in both the L and LT orientations, displayed tensile strengths in excess of 635 MPa. Most notable is that the maximum joint efficiency, 74?6%, is obtained at the highest energy level of 1768 J mm21. Under this condition, not only is the

Results and discussion Mechanical testing During FSW, the weld parameters, weld velocity vw, tool rotation speed v and applied force F, influence the microstructural properties within the welded region and determine the overall energy imparted to the workpieces. The energy per unit length of weld El, therefore, more appropriately indicates the welding conditions than any individual welding parameter. The weld energy can be derived from Khandkar’s15,16 torque based model for which the total torque Ttotal is expressed as the sum of torque contributions from the tool shoulder against the Table 3 Mechanical properties of 7136-T76 welded extrusions Tool rotation speed, rev min21

Load, kN

El, J mm21

Rm, MPa

Re0?2, MPa

e, %

E, GPa

Efficiency, %

L LT 175 225 250 300 350 400

… … 24?3 29?0 20?9 29?4 26?5 21?1

… … 810 1245 997 1684 1768 1606

641 635 443 449 448 465 478 454

614 607 354 354 340 355 362 352

10?5 10?9 5?5 5?3 4?1 5?2 6?6 5?4

70?4 70?4 66?4 68?6 70?1 66?7 69?2 67?6

… … 69?1 70?0 69?9 72?5 74?6 70?8


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sensitive to the energy level with the tensile strength rising 24 MPa as the energy increases from 1684 J mm21 to 1768 MPa. For energy levels corresponding to 175, 225 and 250 rev min21, the yield strength appears insensitive to the energy, showing no net increase as the energy level rises from 810 to 1245 J mm21. For energy levels corresponding to 300, 350 and 400 rev min21, however, the yield strength, much like the tensile strength, rises sharply (10 MPa) over a 84 J mm21 increase in energy.

Dynamic testing 4 As welded mechanical properties as function of weld energy

highest tensile strength obtained, but the yield strength and elongation are also greater than those of the other weld conditions. In contrast, the conditions corresponding to the lowest energy level of 810 J mm21 produced the lowest joint efficiency, 69?1%. For the tensile strength, a correlation with the weld energy is revealed for which the tensile strength increases with increasing weld energy as displayed in Fig. 4. For energy levels corresponding to 175, 225 and 250 rev min21, the tensile strength appears somewhat insensitive to the weld energy as the tensile strength rises only 6 MPa as the energy increases from 810 to 1245 J mm21. For energy levels corresponding to 300, 350 and 400 rev min21, the tensile strength is more

The representative frequency response functions are shown in Fig. 5 for the beams as a function of weld energy. The lower three peaks, representing the first three natural frequencies, are extracted for each strike and for all five beams. The average values of the natural frequencies with the estimated values from the FEM are listed in Table 4. The change in natural frequencies follows a similar trend to the change in mechanical properties. Initially with increasing weld energy, the mechanical properties change only slightly; however, beyond a critical energy level (,1300 J mm21), they rapidly increase with weld energy. With increasing weld energy, the natural frequencies initially decrease until reaching a critical energy level (,1225 J mm21), after which they rapidly increase with energy. The behaviour in both the natural frequencies and mechanical properties may be associated with the change in the aluminium 7136 microstructure at

5 Comparison of trends in changes in dynamic and microscopic characteristics of welded beams with respect to weld energy Table 4 Experimental natural frequencies of beam samples for various weld energies

Tool rotation speed, rev min21 Weld energy, J mm21 f1, Hz f2, Hz f3, Hz

Beam no. 0

Beam no. 1

Beam no. 2

Beam no. 3

Beam no. 4

Baseline Baseline 9?2 (9?11) 57?03 (57?09) 160?75 (159?85)

175 791 9?18 56?44 159?7545

300 1173 9?28 57?24 161?62

350 1235 9?29 57?48 162?1455

400 1289 9?09 56?17 158?76


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6 a prediction of change in transverse rigidity of weld and HAZ (a5b) based upon change in second natural frequency, and b predicted change in modulus of elasticity based on change in second natural frequency with respect to weld energies

different weld energy levels.18 Figure 5 also displays a TEM image of the baseline alloy and TEM micrographs of the weld nugget taken from a low weld energy (,1000 J mm21) sample and a high weld energy (.1000 J mm21) sample. Evident in the baseline image is the high density of fine precipitates that naturally corresponds to an aluminium alloy with the strength and hardness levels of 7136-T76. In comparison, the low energy image is primarily characterised by the uniform distribution of coarse precipitates, identified by X-ray phase analysis as MgZn2, and by the lack of the minute strengthening phases observed in the baseline material. In the high energy image, however, a bimodal distribution of particle sizes is observed. The coarse precipitates observed in the low energy sample are certainly present, but a distribution of fine, rod-like strengthening phases within the grains also appears. These microstructural differences give insight into the correlation of natural frequencies with welding energy. The higher energy weld is strengthened by the fine precipitates that are not observed in the lower energy weld. Although the welding temperature (and plastic deformation) was sufficient to promote dissolution of the secondary phases in both weld conditions, only the residual temperature profile of the higher energy weld and its duration were able to ‘pseudo-age’ the supersaturated areas of the weld such that a distribution of fine strengthening phases formed.18 Thus, within the range of the welding energies studied in this project for aluminium 7136-T76, increasing the welding energy promotes the precipitation of strengthening phases within the weld zone and increases the mechanical properties of the weld. Based on the natural frequencies, 1225 J mm21 represents the critical weld energy for which the temperature profile is sufficient for the pseudo-aging process to occur.

Property estimation Using the finite element model presented earlier and the sensitivity of the change in the second natural frequency from the experiment, the change in rigidity of the welded beams may be estimated as shown in Fig. 6. Here, a and b are set equal to one another, indicating that the HAZ and weld nugget/TMAZ contribute equally to the changing rigidity. In actuality, the weld nugget/TMAZ may be expected to contribute more due to the degree of plastic deformation experienced within this region; however, as seen in Fig. 3, various combinations of a

and b can lead to the same change in natural frequency. Therefore, arbitrarily selecting values for a or b may not be judicious, and allowing the two parameters to be equal ensures that at least the trend in rigidity corresponding to the change natural frequency can be estimated. Although the estimated change in rigidity, and hence the modulus of elasticity, is larger than experimentally measured by mechanical testing (Table 3), the trend in the percentage change in modulus with respect to weld energy shown in Fig. 6b is similar to those observed between tensile strength/natural frequency and weld energy. These trends are attributable to the microstructural changes during FSW as described earlier.

Conclusions High strength 7136-T76 aluminium extrusions were friction stir welded at various weld energies and evaluated for their mechanical properties and dynamic behaviour. Mechanical testing revealed that higher joint efficiencies occurred at higher weld energies and that the correlation between the mechanical properties and the weld energy is related to the reprecipitation and aging of strengthening phases. Finite element models, approximating the welded beam with variable physical properties were developed to estimate the spectral characteristics (natural frequencies) of welded beams during dynamic testing and its correlation to varying weld parameters. Modal analysis vibration tests were conducted on five cantilevered beams of same length (one baseline and four welded with different weld energies). The percentage changes in the natural frequencies were correlated with the change in modulus corresponding to different weld energies. It is observed from both static and dynamic tests that the transverse rigidity of the welded beams is changed. The trends observed in these changes are similar to those observed in the mechanical properties, which correspond very well to the microstructural changes due to the FSW process. Future dynamic and static experiments corresponding to different boundary configurations and weld parameters are planned to understand the relationship between the microstructural characteristics of FSW and the dynamic characteristics. Such a correlation can help predict the quality of friction stir welds through non-destructive means.


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Acknowledgement The authors acknowledge the Polish Ministry of Science and Higher Education (grant no. N507 446337) for their support on this research.

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