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Accurate fatigue life predictionFatigue Life Prediction is essential for ensuring the reliability and performance of Powder Bed Fusion (PBF) components. This study introduces an advanced approach that combines elastoplastic thermomechanical simulationThermomechanical Simulation with residual stress analysisResidual stress analysis and stochastic anomaly weighting to enhance fatigue life predictionsFatigue Life Prediction. Our sophisticated simulationSimulation algorithm incorporates isotropic strain hardeningStrain hardening, the cyclic hardening effect, the Bauschinger effect, and stochastic methods to account for anomalies (defects) in the material. This approach uses the Goodman mean stress correction method, adjusting the mean stress to account for residual stressesResidual stress and the probabilistic impact of defects. This method can map the fatigueFatigue life on the printed sample, allowing us to determine whether stress relief heat treatment is necessary for a desired application based on the predicted local fatigueFatigue life and residual stressResidual stress profile. This study advances the understanding of fatigueFatigue and fracture behavior in additive manufacturingAdditive manufacturing metals.

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Fatigue Life Prediction in Powder Bed Fusion Method Using Modified Goodman Diagram with Residual Stress and Anomalies Weighting: Incorporating Strain Hardening, Cyclic Hardening, and Bauschinger Effect

  • 会议论文

  • 发表日期：

    2025年

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  • Hamed Hosseinzadeh

摘要

Accurate fatigue life predictionFatigue Life Prediction is essential for ensuring the reliability and performance of Powder Bed Fusion (PBF) components. This study introduces an advanced approach that combines elastoplastic thermomechanical simulationThermomechanical Simulation with residual stress analysisResidual stress analysis and stochastic anomaly weighting to enhance fatigue life predictionsFatigue Life Prediction. Our sophisticated simulationSimulation algorithm incorporates isotropic strain hardeningStrain hardening, the cyclic hardening effect, the Bauschinger effect, and stochastic methods to account for anomalies (defects) in the material. This approach uses the Goodman mean stress correction method, adjusting the mean stress to account for residual stressesResidual stress and the probabilistic impact of defects. This method can map the fatigueFatigue life on the printed sample, allowing us to determine whether stress relief heat treatment is necessary for a desired application based on the predicted local fatigueFatigue life and residual stressResidual stress profile. This study advances the understanding of fatigueFatigue and fracture behavior in additive manufacturingAdditive manufacturing metals.