Prediction and reduction of unwanted tensile Residual Stress of welded stainless-steel plates is presented in this paper. Validated finite element analysis and Artificial Neural Network (ANN) is employed to simulate and mathematically model the process, respectively. Taguchi design of experiments tool is utilized to generate input data for finite element analyses and also to choose the most accurate ANN structures. RSs are minimized using three methods: Taguchi suggestion, Comprehensive factorial search, and Particle Swarm Optimization, whose accuracy and response pace increases and decreases respectively in this order. Furthermore, adding and removing extra weld lines was proposed to reduce unwanted residual stresses by up to 50%. Finally, the shapes and amounts of results are experimentally verified using contour method and proposed novel application of roughness testing. Micro-grain structures of the welded samples were also investigated, and RSs were discussed considering metallography images.
PilipenkoA.Computer simulation of residual stress and distortion of thick plates in multielectrode submerged arc welding: their mitigation techniques. PhD Thesis, Norwegian University of Science and Technology, Trondheim, Norway, 2001.
2.
DengDMurakawaH.Numerical simulation of temperature field and residual stress in multi-pass welds in stainless steel pipe and comparison with experimental measurements. Comput Mater Sci2006; 37: 269–277.
3.
AbidMSiddiqueM.Numerical simulation to study the effect of tack welds and root gap on welding deformations and residual stresses of a pipe-flange joint. Int J Press Vessel Piping2005; 82: 860–871.
4.
JiangW-CGuanX-W.A study of the residual stress and deformation in the welding between half-pipe jacket and shell. Mater Des2013; 43: 213–219.
5.
JiangWFanQGongJ.Optimization of welding joint between tower and bottom flange based on residual stress considerations in a wind turbine. Energy2010; 35(1): 461–467.
6.
GuoYWuDMaG, et al. Trailing heat sink effects on residual stress and distortion of pulsed laser welded Hastelloy C-276 thin sheets. J Mater Process Technol2014; 214: 2891–2899.
7.
KalaSRSiva PrasadNPhanikumarG.Studies on multipass welding with trailing heat sink considering phase transformation. J Mater Process Technol2014; 214: 1228–1235.
8.
HeinzeCSchwenkCRethmeierM.Numerical calculation of residual stress development of multi-pass gas metal arc welding. J Constr Steel Res2012; 72: 12–19.
9.
Mazar AtabakiMNikodinovskiMChenierP, et al. Experimental and numerical investigations of hybrid laser arc welding of aluminum alloys in the thick T-joint configuration. Opt Laser Technol2014; 59: 68–92.
10.
BajpeiTChelladuraiHAnsariMZ.Experimental investigation and numerical analyses of residual stresses and distortions in GMA welding of thin dissimilar AA5052-AA6061 plates. J Manuf Process2017; 25: 340–350.
11.
PenttiläSKahPRatavaJ, et al. Penetration and quality control with artificial neural network welding system. In: The 27th international ocean and polar engineering conference, San Francisco, CA, Paper Number: ISOPE-I-17-545, June 25–30, 2017.
12.
DuttaPPratiharDK.Modeling of TIG welding process using conventional regression analysis and neural network-based approaches. J Mater Process Technol2007; 184: 56–68.
13.
SathiyaPPanneerselvamKAbdul JaleelMY.Optimization of laser welding process parameters for super austenitic stainless steel using artificial neural networks and genetic algorithm. Mater Des2012; 36: 490–498.
14.
Edwin Raja DhasJKumananS. Neuro evolutionary model for weld residual stress prediction. Appl Soft Comput2014; 14: 461–468.
15.
KarpagarajAParthibanKPonmaniS.Optimization techniques used in gas tungsten arc welding process – aa review. Mater Today Proc2020; 27: 2187–2190.
16.
VinodhSBharathiSKGopiN. Parametric optimization of submerged arc welding using Taguchi method. In: Design of experiments in production engineering. Springer, 2016. pp.183–194.
17.
SchneiderCLisboaCSilvaR, et al. Optimizing the parameters of TIG-MIG/MAG hybrid welding on the geometry of bead welding using the Taguchi method. J Manuf Mater Process2017; 1: 14.
18.
CorreiaDSGonçalvesCVda CunhaSS, et al. Comparison between genetic algorithms and response surface methodology in GMAW welding optimization. J Mater Process Technol2005; 160: 70–76.
19.
SrivastavaSGargRK.Process parameter optimization of gas metal arc welding on IS:2062 mild steel using response surface methodology. J Manuf Process2017; 25: 296–305.
20.
SathishTDinesh KumarSMuthukumarK, et al. Natural inspiration technique for the parameter optimization of A-GTAW welding of naval steel. Mater Today Proc2020; 21: 843–846.
21.
ChenFFXiangJThomasDG, et al. Model-based parameter optimization for arc welding process simulation. Appl Math Model2020; 81: 386–400.
22.
BenyounisKYOlabiA-G.Optimization of different welding processes using statistical and numerical approaches – aa reference guide. Adv Eng Softw2008; 39: 483–496.
23.
IslamMBuijkARais-RohaniM, et al. Process parameter optimization of lap joint fillet weld based on FEM–RSM–GA integration technique. Adv Eng Softw2015; 79: 127–136.
24.
AcheboJOdinikukuWE.Optimization of gas metal arc welding process parameters using standard deviation (SDV) and multi-objective optimization on the basis of ratio analysis (MOORA). J Miner Mater Char Eng2015; 3: 298–308.
25.
KumarAKhuranaMKYadavPK.Optimization of gas metal arc welding process parameters. IOP Conf Ser: Mater Sci Eng2016; 149: 012002.
26.
AnsaripourNHeidariAEftekhariSA.Multi-objective optimization of residual stresses and distortion in submerged arc welding process using genetic algorithm and harmony search. Proc IMechE, Part C: J Mechanical Engineering Science2020; 234: 862–871.
27.
RossiniNSDassistiMBenyounisKY, et al. Methods of measuring residual stresses in components. Mater Des2012; 35: 572–588.
28.
SmithMLevesqueJ-BBichlerL, et al. Residual stress analysis in linear friction welded in-service Inconel 718 superalloy via neutron diffraction and contour method approaches. Mater Sci Eng A2017; 691: 168–179.
29.
Richter-TrummerVTavaresSMMoreiraPM, et al. Residual stress measurement using the contour and the sectioning methods in a MIG weld: effects on the stress intensity factor. Ciência & Tecnologia dos Materiais2008; 20: 114–119.
30.
TurskiMEdwardsL.Residual stress measurement of a 316l stainless steel bead-on-plate specimen utilising the contour method. Int J Press Vessel Piping2009; 86(1): 126–131.
31.
WanYJiangWLiJ, et al. Weld residual stresses in a thick plate considering back chipping: neutron diffraction, contour method and finite element simulation study. Mater Sci Eng A2017; 699: 62–70.
32.
ThibaultDBocherPThomasM, et al. Residual stress characterization in low transformation temperature 13%Cr–4%Ni stainless steel weld by neutron diffraction and the contour method. Mater Sci Eng A2010; 527: 6205–6210.
33.
SoniSKThomasB. Experimental investigation and optimization of welding process parameters for various steel grades using NN tool and Taguchi method. In: AIP conference proceedings, Karnataka, India, 29–31 January 2018, p.020051. AIP Publishing LLC.
34.
American Society of Mechanical Engineers. ASME boiler and pressure vessel code. Section V, nondestructive examination. New York, NY: American Society of Mechanical Engineers, 2015.
35.
American Society of Mechanical Engineers. Boiler and pressure vessel code. Section IX qualification standard for welding, brazing, and fusing procedures; welders; brazers; and welding, brazing, and fusing operators-welding, brazing and fusing qualifications. New York, NY: American Society of Mechanical Engineers, 2019.
36.
GoldakJAAkhlaghiM.Computational welding mechanics. New York: Springer Science & Business Media, 2006.
37.
ChungPSzklarska-SmialowskaS.The effect of heat treatment on the degree of sensitization of type 304 stainless steel. Corrosion1981; 37: 39–50.
38.
JiaXXuJLiuZ, et al. A new method to estimate heat source parameters in gas metal arc welding simulation process. Fusion Eng Des2014; 89: 40–48.
39.
ParkJ-UAnGLeeH-W.Effect of external load on angular distortion in fillet welding. Mater Des2012; 42: 403–410.
40.
ArgyrisJHSzimmatJWilliamKJ. Finite element analysis of arc-welding processes. In: LewisRWMorganK (eds) Numerical methods in heat transfer III, 1985, pp. 1–34. New York: John Wiley.
41.
ASTM Standard. E3, standard guide for preparation of metallographic specimens. West Conshohocken, PA: ASTM International, 2001.
42.
MirshekariGRTavakoliEAtapourM, et al. Microstructure and corrosion behavior of multipass gas tungsten arc welded 304L stainless steel. Mater Des2014; 55: 905–911.
43.
HajianniaIShamanianMKasiriM.Microstructure and mechanical properties of AISI 347 stainless steel/A335 low alloy steel dissimilar joint produced by gas tungsten arc welding. Mater Des2013; 50: 566–573.
44.
PagliaroPPrimeMBRobinsonJS, et al. Measuring inaccessible residual stresses using multiple methods and superposition. Exp Mech2011; 51: 1123–1134.
45.
GuoPZouBHuangC, et al. Study on microstructure, mechanical properties and machinability of efficiently additive manufactured AISI 316L stainless steel by high-power direct laser deposition. J Mater Process Technol2017; 240: 12–22.
46.
LippoldJ.Solidification behavior and cracking susceptibility of pulsed-laser welds in austenitic stainless steels. Weld J Incl Weld Res Suppl1994; 73: 129s.
47.
LippoldJSavageW.Solidification of austenitic stainless steel weldments: part 2—the effect of alloy composition on ferrite morphology. Weld J1980; 59: 48s–58s.
48.
LiuYLiuDYouC, et al. Effects of grain size on the corrosion resistance of pure magnesium by cooling rate-controlled solidification. Front Mater Sci2015; 9: 247–253.
49.
WangKYShenTDQuanMX, et al. Hall-Petch relationship in nanocrystalline titanium produced by ball-milling. J Mater Sci Lett1993; 12: 1818–1820.
50.
RanganathSGuoCHoltS. Experimental investigations into the carbide cracking phenomenon on inconel 718 superalloy material. In: ASME 2009 international manufacturing science and engineering conference, West Lafayette, IN, 4–7 October 2009, Vol. 2, pp.33–39. New York, NY: ASME.
51.
GiangNAKunaMHütterG.Influence of carbide particles on crack initiation and propagation with competing ductile-brittle transition in ferritic steel. Theor Appl Fract Mech2017; 92: 89–98.
52.
CallisterWDJrRethwischDG.Callister’s materials science and engineering. John Wiley & Sons, 2020.
53.
CoulsonS.Analysis of additively manufactured 17-4PH stainless steel. Master of Applied Sciencethesis, McMaster University, Hamilton, ON, Canada, 2018.
