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Scripta Materialia 67 (2012) 783–786

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Quantitative characterization of porosity in laser welds ofstainless steel

Jonathan D. Madisona,⇑ and Larry K. Aagesenb

aComputational Materials Science and Engineering, Sandia National Laboratories, Albuquerque, NM 87185, USAbMaterials Science and Engineering, University of Michigan, Ann Arbor, MI 48109, USA

Received 6 April 2012; revised 9 June 2012; accepted 11 June 2012Available online 16 June 2012

Standing-edge joints made by a continuous-wave Nd:YAG laser are examined in 304L stainless steel to advance understanding ofthe linkage between processing and microstructure in high-rate solidification events. Microcomputed tomography combined withtraditional metallography has provided qualitative and quantitative characterization of welds in this material system of broaduse and applicability. Pore presence and variability have been examined three-dimensionally for average values, spatial distributionsand morphology, and related to processing parameters such as weld speed, delivered power and focal lens.� 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Keywords: Microcomputed tomography; Stainless steel; Welding; Microstructure

It is fundamentally understood that processingdetermines material microstructure, and microstructure,in turn, dictates mechanical response. It is rather difficult,however, to quantitatively predict microstructure basedsolely upon processing inputs. Laser welds are no excep-tion to this trend. While the field has benefited from inves-tigations to further understand and model heat–materialinteraction among laser welds [1–10], a portion of theseinvestigations have focused specifically on the formationof porosity and its driving forces. Prevailing hypothesesassert that porosity seen in high-power laser welds largelyresult from intermittent molten pool collapse broughtabout by a fluctuating imbalance between ablation recoilpressure, molten liquid surface tension and impactingpressure [11–14]. This phenomenon is chiefly referred toas “key-hole collapse”. While models have advancedgreatly in the incorporation of multiphysics approachesto better understand this weld process, the ability of thesemodels to qualify and specifically predict large-scalemicrostructure over a broad range of process-parameterspace requires further development. As such, commonengineering practice for the qualification of welds are per-formed industrially in-process by means of optical,acoustic and/or charged particle sensors [15]. Post-pro-cess inspections are generally performed by post-mortemfailure investigations [16], radiography [17] or ultrasonic

1359-6462/$ - see front matter � 2012 Acta Materialia Inc. Published by Elhttp://dx.doi.org/10.1016/j.scriptamat.2012.06.015

⇑Corresponding author. E-mail: jdmadis@sandia.gov

scans [18] which often yield two-dimensional projectionsof a three-dimensional space. This work, seeks to provide:(i) a detailed three-dimensional, quantitative interroga-tion of weld microstructure over a window of porosityproducing weld schedules in a widely utilized materialsystem; and (ii) relate resultant microstructure, with chiefemphasis on porosity, to the processing parameters ofthat weld schedule window.

A matrix of six standing-edge laser welds yieldingvaried microstructure and differing porosity levels werewelded with a ROFIN-Sinar, Inc., continuous wave,015HQ, Nd:YAG laser. For each weld, two 2.54 cm �10.16 cm � 0.1 cm plates of 304L stainless steel havinga nominal composition of Fe–0.04C–18.12Cr–1.21Mn–8.09Ni–0.028N–0.022P–0.001S–0.34Si (wt.%) wereoriented parallel to one another, fixed at their base byclamp and welded on their upper seam producing weldjoints having an approximate depth (y), length (z) andwidth (x) of 0.5 cm � 7.0 cm � 0.2 cm, respectively.See Figure 1. Delivered power was measured via aMackenP2000Y Laser Power-Probe and confirmed tobe 1200 W for each weld with an 80 or 120 mm focusinglens at constant speeds of 1016 mm min�1 (16.9 mms�1), 1524 mm min�1 (25.4 mm s�1) and 2032 mm min�1

(33.8 mm s�1) respectively. See Table 1. These parame-ters were not selected to mirror a commercial processbut to produce three distinct regimes of porosity previ-ously identified in millimeter-scale laser welds of 304L[19,20].

sevier Ltd. All rights reserved.

Figure 1. Representative weld cross-sections at each welding speed for120 mm focal lens series illustrating keyhole weld microstructures andembedded porosity. Figure 2. (a) Surface width to depth width ratio (SW/DW) and (b)

crown height as functions of weld speed.

784 J. D. Madison, L. K. Aagesen / Scripta Materialia 67 (2012) 783–786

Microcomputedtomography (lCT) was employedusing a Kevex PSX10-65WX-ray tube operating at130 kV and 250 lA. The sample was rotated counter-clockwise at a speed of 0.12�s�1. Transmitted signalswere received on a cesium iodide fluorescent platethrough a magnification lens. The final voxel (or three-dimensional pixel) resolution of the 80 and 120 mm focallens sets were 15.5 � 15.5 � 31 and 13.5 � 13.5 � 27lm voxel�1, respectively. Next one weld at each settingwas sectioned at three intervals along the length of theweld, metallographically prepared and imaged for com-parison by optical microscopy.

Metallographic cross-sections, Figure 1, reveal typicaltrends in the ratio of penetration depth to weld width[19,21–26] with increasing weld speed and focal distance(Table 1). Tomography for one sample using the120 mm lens at 2032 mm min�1 utilized a differentX-ray source that resulted in a loss of resolution. Largevoids remained distinguishable in size and shape, whilesmaller pores experienced a loss in fidelity. For this reasonthe voids/unit length is not reported for this sample. Theseminal work of Cline and Anderson illustrated manyrelations between weld geometry and the physics of theheat–material interaction [1,2]. Two measures that canhelp describe weld geometry are the ratio of surface widthto subsurface breadth or “depth width” and the crownheight. Here, surface width (SW) is identified as the weldwidth at its surface, while depth width (DW) is defined asthe maximum weld width at distances at or below half thetotal penetration depth. Crown height is defined as theelevation of the weldment at its centerline relative to thebase metal. While implications will be discussed later,the variation of these measures with respect to weld speedis shown in Figure 2.

Table 1. Weld matrix with associated measures.

Focal lens(mm)

Weld speed(mm min�1)

D/Wratio

Nominal voidvolume (mm3)

Nominal voids/length (mm�1)

80 1016 1.44 0.075 2.4680 1016 0.068 2.58120 1016 1.28 0.190 1.05120 1016 0.180 1.2480 1524 1.43 0.0050 6.0480 1524 0.0049 6.04120 1524 1.18 0.0094 5.11120 1524 0.0075 4.5480 2032 1.45 0.0018 8.5080 2032 0.0015 7.22120 2032 1.26 0.0032 7.01120 2032 0.0041 –

lCT revealed trends in porosity size, distributions,location in the weld and overall void morphology. Toprovide measures of average individual void volumes,minima of 90% or more of the total voided space in eachweld were considered with their associated averages pre-fixed by the term “nominal” as displayed in Table 1. Atboth focusing distances, decreases in nominal void vol-ume were apparent, as were increases in nominal voidsper unit length with increases in weld speed. Reconstruc-tions of porosity are shown in Figure 3. These findingsare consistent with trends and observations providedby Norris et al. [19,20,25]; here, however, physical vol-umes of the observed porosity are returned, rather thana singular observed diameter. Beyond average measures,porosity histograms, binned by void size (i.e. voxels perpore), illustrate that major contributors to the totalvoided space in each weld are not the most frequentlyoccurring populations (Fig. 3). In fact, voxel bins pos-sessing 10 or fewer voxels per pore contribute less than7% to the total porosity observed in each case despitebeing among the most frequently occurring population.Each histogram pair corresponds to the reconstructedpores pictured above them.

With regards to the morphology of the porosity,Voorhees et al. [27–29] have developed methods fordescribing curvature populations for any geometry ofinterface between two discrete phases with previousapplications to solidification [30], coarsening in metals[27,29,31,32] and topologically complex domains[28,33,34]. One major output of these methods are inter-facial shape distributions (ISDs), which indicate theprobabilities associated with encountering an interfacialpatch having a specific pairing of principal curvatures.

unit Porosity volumefraction

Normalized nominalshape anisotropy

Major (a) Minor1 (b) Minor 2

0.079 ± 0.03 1.84 ± 0.24 1.16 ± 0.18 11.82 ± 0.22 1.17 ± 0.16 1

0.081 ± 0.02 1.75 ± 0.26 1.23 ± 0.19 11.69 ± 0.27 1.19 ± 0.13 1

0.017 ± 0.004 1.63 ± 0.21 1.25 ± 0.14 11.65 ± 0.25 1.25 ± 0.16 1

0.023 ± 0.004 1.54 ± 0.23 1.23 ± 0.11 11.57 ± 0.24 1.21 ± 0.12 1

0.009 ± 0.001 1.67 ± 0.20 1.23 ± 0.14 11.66 ± 0.19 1.21 ± 0.14 1

0.014 ± 0.002 1.61 ± 0.22 1.25 ± 0.13 11.63 ± 0.22 1.22 ± 0.13 1

Figure 3. Microcomputed tomography reconstructions of 120 mmfocal lens weld series. Upper and lower histograms report voided spacepercentage contributions and total quantities of voids, respectively, asfunctions of voxel size.

Figure 4. Interfacial shape distribution plots for 120 mm focal lensporosity reconstructions illustrated in Figure 3.

J. D. Madison, L. K. Aagesen / Scripta Materialia 67 (2012) 783–786 785

For further details on this method and the ISD legend,the reader is referred to the aforementioned references.With respect to the ISD legend contained in these refer-ences, in the analysis herein, the “S” phase correspondsto the weld metal and the “L” phase, as shown in theISD legend, here, correspond to porosity. ISDs for the120 mm lens series are shown in Figure 4. As weldspeeds increase, the ISD population peak shifts fromj2 equal to 0 with slightly negative values of j1, to j1

and j2 both becoming increasingly negative. This funda-mentally means two things as welding speeds increase,(i) curvature population maxima lose almost all j2 val-ues greater than 0, indicating a near complete loss ofsaddle-like patches; (ii) the morphology of porositytransitions from being elliptical with a relatively tightdistribution of curvatures to a collection of morpholo-gies more spherical in shape, having a wider distributiondue to increased populations. To make the transition inmorphology more clear, ellipses were fit to individualvoids throughout each reconstruction while returningthe major (a), minor1 (b) and minor 2 dimensions ofeach ellipse for extrapolation of diameter anisotropy.In this measure, ranges of 90–99% of the voided spacewithin each weld were evaluated. To compare acrossvoids of varying size, each pore’s a and b axes were nor-malized by its minor 2 axis. It was found that at slowspeeds, pores exhibit a major diameter nearly twice thatof the secondary and tertiary axes. With increases inweld speed or focal length, shape anisotropy decreasesbut never reaches a 1:1:1 aspect ratio (Table 1).

Lastly, by combining metallography with lCT obser-vations, the void volume fractions in each weld were cal-culated (Table 1). Using the metallographic sectionsacquired, cross-sectional area throughout the length ofthe weld can be approximated and compared to directlymeasured porosity volumes. The standard deviations re-ported in Table 1 were calculated from differences in vol-ume fraction for a given weld, using the three separatemetallographic cross-sections. Porosity volume fractionwas observed to yield a maximum of 8 ± 3.0% and aminimum of 1 ± 0.1% in the welds examined.

In the experiments performed here, the 80 and120 mm focal lenses provide focal depths of 2.5 and3 mm, respectively. These ranges bound the maximumdeviation of delivered power to no less than 88–90% ofpower delivered at optimum focus. It follows that theD/W ratio would be greater than unity for the powerand standing-edge geometry used as well as serve as afairly effective indicator of the “keyhole” strength pres-ent during processing. Further changes in the weld enve-lope and fusion zone, however, can offer additionalinsight into the welding process. The increasing surfacewidth to depth width ratio (SW/DW) (Fig. 2a) indicatesthat while the overall depth to width (D/W) ratio re-mains largely unchanged over the weld speeds examined(Table 1), the relative breadth of the subsurface weldinterior becomes smaller by a factor of 1.5–2� in com-parison to the weld at its surface as welding speeds in-crease. This indicates a diminishing of “keyhole”behavior with higher travel speeds. While this is a gener-ally understood behavior due to the transition from key-hole to near-conduction mode welding at very highspeeds or very low powers, here we document powersand speeds over which such a transition begins to occurand the relative extent to which the weld interior nar-rows in comparison to the weld surface. Additionally,increases in weld speed are accompanied by decreasesin crown height. Over the parameters investigated, thecrown height actually becomes negative at 1.5 and2 m min�1, indicating a depression at the centerline ofthe weld below the surface of the base metal. Significantefforts have been undertaken by other investigators tomodel weld pool dynamics and even relate molten fluidflow to the final microstructure. Among these efforts,some have centered around interactions due to surfacetension [8], resolving velocity and temperature fields[35,36] and/or combining energy balance with three-dimensional fluid flow models [9]. The observance ofthe transition to a recessed weld surface here is notewor-thy as it clearly documents a specific set of processingparameters around which such an event occurs.

The progression of void volumes and the increase invoids per unit length are consistent with the observa-tions of Norris et al. for the keyhole microstructuresexamined here, and suggest that while keyhole collapse[11–14] is a likely explanation for the porosity seen atlow speeds, a very different mechanism may be at playat higher speeds. The smaller pores found at highertravel rates exhibit a stark contrast from slow speedpores in frequency, lateral distribution and longitudinal

786 J. D. Madison, L. K. Aagesen / Scripta Materialia 67 (2012) 783–786

position on top and below one another throughout theweld centerline. The widely accepted keyhole collapsemodels do not predict or suggest void populations ofthis arrangement, quantity or placement. At these higherwelding speeds, impurities and/or shielding gas effectsmay play a greater role in the formation of porosityobserved.

Shape anisotropy reported here indicate that theapproximation of porosity in high-power, millimeter-scale laser welds as spheres is somewhat inaccurateand proposes that ellipses are a more precise morphol-ogy. This is of particular importance for mechanical re-sponse models seeking to incorporate physical oridealized pore geometries. Additionally, based on load-ing direction, the effects of substituting a spherical porein place of an ellipse can generate very different and fun-damentally disparate behavior. Furthermore, the poreshapes documented here indicate that returning singularpore diameters may result in increased levels of inaccu-racy for measures such as shape, size and volume frac-tion. While approximation of the entire weld envelopeshould be improved to further reduce uncertainty in vol-ume fraction calculations, such an improvement willlikely require destructive methods, such as serial section-ing, or using smaller heat inputs to reduce variationthroughout the length of the weld.

In summary, the characterization detailed here pro-vides an advance in the qualitative and quantitativeunderstanding of millimeter-scale laser weld microstruc-tures. It was found that both macro- and microstruc-tural features such as void volumes, frequency, shapeand volume fraction all vary distinctly with changes indocumented processing parameters. It was also shownthat porosity shapes discovered in these microstructuresare more accurately described as ellipses rather thanspheres.

The authors thank D. MacCallum and A. Kil-go of Sandia National Laboratories for laser machiningand metallographic preparation, P. Voorhees of North-western University for use of the ISD analysis tool andD. Rowenhorst of the Naval Research Laboratory foruse of the three-dimensional ellipse fit algorithm. SandiaNational Laboratories is a multi-program laboratorymanaged and operated by Sandia Corporation, a whollyowned subsidiary of Lockheed Martin Corporation, forthe US Department of Energy’s National Nuclear Secu-rity Administration under contract DE-AC04-94AL85000.

[1] T.R. Anthony, H.E. Cline, J. Appl. Phys. 48 (1977) 3888–3894.

[2] H.E. Cline, T.R. Anthony, J. Appl. Phys. 48 (1977) 3895–3900.

[3] C. Chan, J. Mazumder, M.M. Chen, Metall. Mater.Trans. A 15A (1984) 2175–2184.

[4] S. Kou, Y.H. Wang, Met. Trans. A 17A (1986) 2265–2270.

[5] R.K. Ganesh, A. Faghri, Y. Hahn, Int. J. Heat MassTransfer 40 (1997) 3351–3360.

[6] P. Solano, G. Negro, J. Phys. D: Appl. Phys. 30 (1997)3216–3222.

[7] R. Fabbro, K. Chouf, J. Appl. Phys. 87 (2000) 4075–4083.[8] V.V. Semak, G.A. Knorovsky, D.O. MacCallum, R.A.

Roach, J. Phys. D: Appl. Phys. 39 (2006) 590–595.

[9] R. Rai, J.W. Elmer, T.A. Palmer, T. DebRoy, J. Phys. D:Appl. Phys. 40 (2007) 5753–5766.

[10] K. Salonitis, A. Stournaras, G. Tsoukantas, P. Stavropo-ulos, G. Chryssolouris, J. Mater. Proc. Technol. 183(2007) 96–103.

[11] A.F.H. Kaplan, M. Mizutani, S. Katayama, A. Matsu-nawa, J. Phys. D: Appl. Phys. 35 (2002) 1218–1228.

[12] J.Y. Lee, S.H. Ko, D.F. Farson, C.D. Yoo, J. Phys. D:Appl. Phys. 35 (2002) 1570–1576.

[13] A. Matsunawa, J.-D. Kim, N. Seto, M. Mizutani, S.Katayama, J. Laser Apps. 10 (1998) 247–254.

[14] S. Pang, L. Chen, J. Zhou, Y. Yin, T. Chen, J. Phys. D:Appl. Phys. 44 (2011) 1–15.

[15] R. Paura, Laser weld quality monitoring, in: ASMHandbook, vol. 6A, ASM International, Materials Park,OH, 2011, pp. 595–605.

[16] B.L. Boyce, P.L. Reu, C.V. Robino, Metall. Mater.Trans. A 37A (2006) 2481–2492.

[17] A. Haboudou, P. Peyre, A.B. Vannes, G. Peix, Mater.Sci. Eng. A A363 (2003) 40–52.

[18] W.D. Feist, G.-R. Tillack, in: European–American Work-shop Determination of Reliability and Validation Meth-ods of NDE, NDT.net, Berlin, Germany, 1997.

[19] J.T. Norris, M.J. Perricone, R.A. Roach, K.M. Faraone,C.M. Ellison, in: SAND2007-1051, Sandia NationalLaboratories, 2007.

[20] J.T. Norris, C.V. Robino, D.A. Hirschfeld, M.J. Perri-cone, Welding J. 90 (2011) 198–203.

[21] S. Kuo, Welding Metallurgy, John Wiley, Hoboken, NJ,2003.

[22] T.Y. Kuo, S.L. Jeng, J. Phys. D: Appl. Phys. 38 (2005)722–728.

[23] J.C. Lippold, D.J. Kotecki, Welding Metallurgy andWeldability of Stainless Steels, John Wiley, Hoboken,NJ, 2005.

[24] R.W. Messler Jr., Principles of Welding: Processes,Physics, Chemistry and Metallurgy, John Wiley, NewYork, 1999.

[25] J.T. Norris, M.S. thesis, New Mexico Institute of Miningand Technology, 2010.

[26] T. Webber, T. Lieb, J. Mazumder, Laser beam welding,in: ASM Handbook, vol. 6A, ASM International, Mate-rials Park, OH, 2011, pp. 556–569.

[27] R. Mendoza, J. Alkemper, P.W. Voorhees, Metall. Mater.Trans. A 34A (2003) 481–489.

[28] D. Kammer, R. Mendoza, P.W. Voorhees, Scripta Mater.55 (2006) 17–22.

[29] D. Kammer, P.W. Voorhees, Acta Mater. 54 (2006) 1549–1558.

[30] J. Alkemper, P.W. Voorhees, Acta Mater. 49 (2001) 897–902.

[31] D.J. Rowenhorst, J.P. Kuang, K. Thornton, P.W. Voo-rhees, Acta Mater. 54 (2006) 2027–2039.

[32] J.L. Fife, P.W. Voorhees, Acta Mater. 57 (2009) 2418–2428.

[33] D. Kammer, P.W. Voorhees, MRS Bull. 33 (2008) 611–619.

[34] A.L. Genau, P.W. Voorhees, K. Thornton, Scripta Mater.60 (2009) 301–304.

[35] X. He, P.W. Fuerschbach, T. DebRoy, J. Phys. D: Appl.Phys. 36 (2003) 1388–1398.

[36] X. He, J.T. Norris, P.W. Fuerschbach, T. DebRoy, J.Phys. D: Appl. Phys. 39 (2006) 525–534.