The Fatigue Life Prediction Method of Steel Frame Structure Based on the Average Stress Correction Method

Introduction: The classic Goodman, Dietman, and Gerber average stress correction models have limitations in predicting the fatigue life of materials such as Q235 steel, especially under conditions of multiple stress ratios and high amplitude loads, where their accuracy is insufficient, which restricts the safety assessment of infrastructure and the optimization management of resources. Methods: Based on the Goodman, Dietman, and Gerber models, this patent proposes a new average stress correction model and conducts room-temperature uniaxial tensile and compressive fatigue tests on Q235 steel (including stress ratios R=-1, -0.75, and -0.5 at each stress level). The fatigue life was calculated using the new model and three classical models. The model accuracy is evaluated by the average, maximum, and standard deviation of the absolute values of the relative errors between the predicted life and the test life. Results: The average of the absolute relative error for the newly revised model's prediction results is 30.52%, the maximum value is 113.58%, and the standard deviation is 43.35%. Compared with the three classical models, there are significant differences, and the overall performance is better, indicating that this model has higher accuracy and stability in predicting the fatigue life of Q235 steel under different stress ratios and maximum stress combinations. Discussion: Evaluation against the existing model indicates significant improvements in the revised model: a minimum reduction of 9.66% in the mean absolute relative error and a minimum reduction of 6.76% in the standard deviation. The data confirms that the revised model is better suited for predicting fatigue in Q235 steel. Conclusion: The new average stress correction model proposed in this patent significantly improves the accuracy and stability of fatigue life prediction for Q235 steel. By supporting the safe operation and maintenance of energy infrastructure to reduce material waste, promoting the recycling of steel to lower carbon emissions, and enhancing the safety and resilience of critical facilities, we contribute to sustainable social development.