Author(s)

Lihao Peng ¹

Affiliation(s)

¹ Xihua University, Chengdu, Sichuan, 610039, China

Corresponding Author

Lihao Peng

ABSTRACT

The fabrication of large-scale steel structures through multi-pass welding is plagued by distortion phenomena arising from complex thermo-mechanical interactions during the welding process. This investigation presents an advanced computational framework combining thermo-elasto-plastic finite element analysis (FEA) with experimental validation to predict, analyze, and mitigate welding-induced distortion in structural steel components. A comprehensive three-dimensional finite element model was developed incorporating temperature-dependent material nonlinearities, phase transformation kinetics, and transient heat transfer phenomena with moving heat source effects. The model was rigorously validated through experimental studies involving gas metal arc welding (GMAW) of 10 mm thick ASTM A36 steel plates, with extensive thermographic analysis using infrared imaging and precise distortion measurements via laser scanning interferometry. The numerical predictions demonstrated exceptional correlation with experimental observations, with distortion magnitude discrepancies below 8% and thermal profile predictions within 5% accuracy. Systematic evaluation of distortion compensation strategies revealed that optimized pre-deformation techniques could achieve up to 45% reduction in final distortion, while intelligent welding sequence optimization provided additional 35-50% improvement over conventional approaches. The study establishes a robust methodology for virtual prototyping of welding processes, offering significant potential for reducing manufacturing costs and improving dimensional accuracy in heavy fabrication industries.

KEYWORDS

Multi-pass welding distortion; Thermo-elasto-plastic analysis; Finite element simulation; Distortion compensation; Residual stress prediction

CITE THIS PAPER

Lihao Peng. Prediction and Compensation of Distortion in Multi-Pass Welding of Large-Scale Steel Structures Using Thermo–Elasto–Plastic Finite Element Analysis. Journal of Materials, Processing and Design (2026). Vol. 10, No.1, 19-26. DOI: http://dx.doi.org/10.23977/jmpd.2026.100103.

REFERENCES

[1] Dong, P., Song, S., and Pei, X. An IIW residual stress profile estimation scheme for girth welds in pressure vessel and piping components [J]. Weld World, 2016, 60(2): 283–298.
[2] Song, S. P., Dong, P., and Pei, X. A full-field residual stress estimation scheme for fitness-for-service assessment of pipe girth welds: Part I — Identification of key parameters [J]. International Journal of Pressure Vessels and Piping, 2015, 126(5): 8–70.
[3] Prakash, B., Bhardwaj, M. Y., and Bansal, V. Review on finite element analysis for estimation of residual stresses in welded structures [J]. Materials Today: Proceedings, 2017, 4(9): 10230–10234.
[4] Rong, Y., Xu, J., Huang, Y., and Zhang, G. Review on finite element analysis of welding deformation and residual stress [J]. Science and Technology of Welding and Joining, 2018, 23(3): 198–208.
[5] Arora, H., Singh, R., and Brar, G. S. Thermal and structural modelling of arc welding processes: A literature review [J]. Measurement and Control, 2019, 52(7–8).
[6] Ueda, Y., Murakawa, H., and Ma, N. Welding Deformation and Residual Stress Prevention [M]. Elsevier Inc., 2012. ISBN 978-0-12-394804-5.
[7] Coules, H. E. Contemporary approaches to reducing weld induced residual stress [J]. Materials Science and Technology, 2013, 29(1): 4–18.
[8] Marques, E. S. V., Francisco, J. G. S., and Pereira, A. B. Comparison of finite element methods in fusion welding processes — A review [J]. Metals, 2020, 10(1): 75. DOI: 0.3390/met10010075.
[9] Goldak, J. A., and Akhlaghi, M. Computational Welding Mechanics [M]. Springer, 2005.
[10] Yang, Y. P., Brust, F. W., Fzelio, A., and McPherson, N. Weld modeling of thin structures with VFT software [C]. ASME Pressure Vessels and Piping Conference, San Diego, CA, 2004, July 25–29.
[11] Long, H., Gery, D., Carlier, A., and Maropoulos, P. G. Prediction of welding distortion in butt joint of thin plates [J]. Materials & Design, 2009, 30(10): 4126–4135.
[12] Teng, T. L., Fung, C. P., Chang, P. H., and Yang, W. C. Analysis of residual stresses and distortions in T-joint fillet welds [J]. International Journal of Pressure Vessels and Piping, 2001, 78(8): 523–538.
[13] Schenk, T., Richardson, I. M., Kraska, M., and Ohnimus, S. Modeling buckling distortion of DP600 overlap joints due to gas metal arc welding and the influence of the mesh density [J]. Computational Materials Science, 2009, 46(4): 977–986.
[14] Ni, J., Zhuang, X., Wahab, M. A. Review on the prediction of residual stress in welded steel components [J]. Computers, Materials & Continua, 2020, 62(2): 495–523. 

Sponsors, Associates, and Links

---

• Forging and Forming
  
  
• Composites and Nano Engineering
  
  
• Metallic foams
  
  
• Smart Structures, Materials and Systems
  
  
• Chemistry and Physics of Polymers
  
  
• Analytical Chemistry: A Journal
  
  
• Modern Physical Chemistry Research
  
  
• Inorganic Chemistry: A Journal
  
  
• Organic Chemistry: A Journal
  
  
• Progress in Materials Chemistry and Physics
  
  
• Transactions on Industrial Catalysis
  
  
• Fuels and Combustion
  
  
• Casting, Welding and Solidification
  
  
• Journal of Membrane Technology
  
  
• Journal of Heat Treatment and Surface Engineering
  
  
• Trends in Biochemical Engineering
  
  
• Ceramic and Glass Technology
  
  
• Transactions on Metals and Alloys
  
  
• High Performance Structures and Materials
  
  
• Rheology Letters
  
  
• Plasticity Frontiers
  
  
• Corrosion and Wear of Materials
  
  
• Fluids, Heat and Mass Transfer
  
  
• International Journal of Geochemistry
  
  
• Diamond and Carbon Materials
  
  
• Advances in Magnetism and Magnetic Materials
  
  
• Advances in Fuel Cell
  
  
• Journal of Biomaterials and Biomechanics