Uncertainty for fatigue life of low carbon alloy steel based on improved bootstrap method

Fatigue testing is a crucial technique for assessing the fatigue performance of materials and components. However, the testing process often involves numerous uncertainties, such as variations in part roughness and size, and the collected data typically constitutes small samples. This paper proposes an improved bootstrap method with cycle of uncertainty to address the limitations of traditional bootstrap methods in estimating uncertainties in small sample sizes. The proposed method was applied to estimate the effect of surface roughness and common normal size on fatigue tests, resulting in improved estimation accuracy. The research contributes to the development of improved methods for fatigue life estimation, which has practical implications for mechanical component design and optimization.

Automated summary

Fatigue testing is crucial for assessing material and component fatigue performance, but it often faces uncertainties and small sample sizes. This paper proposes an improved bootstrap method to estimate uncertainties in small samples by addressing the limitations of traditional methods. The method was applied to estimate the effect of surface roughness and size on fatigue tests, resulting in improved estimation accuracy. The research contributes to the development of improved methods for fatigue life estimation, with practical implications for mechanical component design and optimization.