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This work characterized the microstructure and evaluated the mechanical behavior of ASTM A572 steel before and after GMAW and FCAW welding processes for base metal, fusion zones, and heat-affected zones. The microstructures were observed using optical and scanning electron microscopy. Characterization techniques included optical microscopy, scanning electron microscopy, and backscattered electron diffraction. The mechanical behavior was evaluated by tensile tests, hardness tests, fracture toughness tests (linear elastic fracture mechanics), and fatigue crack propagation tests (da/dN × ΔK). The fatigue tests were performed with ratios (R = 0.1) applying empirical models from Paris (1963), Bergner (2000), and the more recent one proposed by Jones et al. (2012) to predict the material's behavior. Simulation models for the tensile test were implemented using the finite element method with Abaqus software, and simulation models for the fatigue test were implemented with Ansys software. The simulation results were compared with the tensile tests to evaluate the validity of these models. For the ASTM A572 steel, the crack propagation rate in the fusion zone of both welded joints was lower than in the base metal. The base metal and the welded joints showed an R-ratio dependence on fatigue. The empirical models were satisfactory for fitting the experimental data. Comparing the empirical and numerical results with the experimental ones, a similar behavior is observed between the curves for the base metal, where the maximum error obtained was 17%, but in both welded specimens, the error was above 20%. Therefore, a mathematical adjustment was made to the constants for the Jones model, with this change in the constant 0.036 varying with the crack propagation threshold value (ΔKthreshold) fitting the curves and providing an error of less than 2%. The methodology used for life prediction in this work can help in deciding and determining maintenance schedules for equipment and in project development for more reliable life predictions.

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Mathematical Modeling, Mechanical Properties, Fatigue Resistance of ASTM A572 Steel and Welded Joints Obtained by GMAW and FCAW

  • 章节

  • 发表日期：

    2026年

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  • Fernando Vidal dos Santos,
  • José Rubens Gonçalves Carneiro,
  • João Pedro Carneiro

摘要

This work characterized the microstructure and evaluated the mechanical behavior of ASTM A572 steel before and after GMAW and FCAW welding processes for base metal, fusion zones, and heat-affected zones. The microstructures were observed using optical and scanning electron microscopy. Characterization techniques included optical microscopy, scanning electron microscopy, and backscattered electron diffraction. The mechanical behavior was evaluated by tensile tests, hardness tests, fracture toughness tests (linear elastic fracture mechanics), and fatigue crack propagation tests (da/dN × ΔK). The fatigue tests were performed with ratios (R = 0.1) applying empirical models from Paris (1963), Bergner (2000), and the more recent one proposed by Jones et al. (2012) to predict the material's behavior. Simulation models for the tensile test were implemented using the finite element method with Abaqus software, and simulation models for the fatigue test were implemented with Ansys software. The simulation results were compared with the tensile tests to evaluate the validity of these models. For the ASTM A572 steel, the crack propagation rate in the fusion zone of both welded joints was lower than in the base metal. The base metal and the welded joints showed an R-ratio dependence on fatigue. The empirical models were satisfactory for fitting the experimental data. Comparing the empirical and numerical results with the experimental ones, a similar behavior is observed between the curves for the base metal, where the maximum error obtained was 17%, but in both welded specimens, the error was above 20%. Therefore, a mathematical adjustment was made to the constants for the Jones model, with this change in the constant 0.036 varying with the crack propagation threshold value (ΔKthreshold) fitting the curves and providing an error of less than 2%. The methodology used for life prediction in this work can help in deciding and determining maintenance schedules for equipment and in project development for more reliable life predictions.