Probabilistic modeling of damage accumulation for time-dependent fatigue reliability analysis of railway axle steels

Abstract

From the viewpoint of engineering applications, the prediction of the failure of railway axles plays an important role in preventing the occurrence of fatigue fractures. Combining a nonlinear damage accumulation model, a probabilistic S-N curve, and a one-to-one probability density functions transformation technique, a general probabilistic methodology for modeling damage accumulation is developed to analyze the time-dependent fatigue reliability of railway axle steels. The damage accumulation is characterized as a distribution in a general degradation path, which captures a nonlinear damage accumulation phenomenon under variable-amplitude loading conditions; its mean and variability change with time. Moreover, a framework for fatigue reliability assessments and service life prediction is presented based on the estimation of the evolution and probabilistic distribution of fatigue damage over time. The proposed methodology is then validated by experimental data obtained for a railway axle (45 steel and LZ50 steel). The time-dependent reliability is analyzed and demonstrated through probabilistic modeling of cumulative fatigue damage, and good agreement between the predicted results and the experimental measurements under different variable amplitude loadings is obtained.

Failure Analysis and Reliability of Ni–Ti-Based Dental Rotary Files Subjected to Cyclic Fatigue

“…Probabilistic modeling of fatigue failure and reliability assessment has been done for various engineering components such as turbine blades [19], turbine disc [20], and railway axles [21], which Statistical analysis of the empirical data is essential for the proper interpretation and prediction of results. There are many statistical methods such as analysis of variance (ANOVA), regression analysis, and correlation for analyzing data and representation of results [16].…”

“…However, there was no significant difference between PTU F2 and PTN X3 in terms of CF resistance. Probabilistic modeling of fatigue failure and reliability assessment has been done for various engineering components such as turbine blades [19], turbine disc [20], and railway axles [21], which are subjected to variable loading conditions. Reliability analysis is important for the establishment of suitable safety levels for any device or system.…”

Multidisciplinary reliability design optimization under time-varying uncertainties

“…14,15 The product performance degrades gradually over time. The degradation process of product performance is a dynamic timevarying process.…”

“…The degradation process of product performance is a dynamic timevarying process. 15 Time-varying reliability method is often applied to deal with time-varying uncertainties. Time-varying reliability means that the failure rate p f (t 0 -t 1 ) of limit state function is less than the given failure rate during time interval t 0 -t 1 .…”

“…There are variant timevarying uncertainties in complex mechanical systems, such as performance degradation of electronic component, strength decrease, material aging, wear, oxidation, and corrosion. 14,15 Although research methods to deal with aleatory and epistemic uncertainties in MDO may largely improve the reliability of complex systems, however, these research methods cannot accurately describe the sources, essential characteristics, and propagation properties of time-varying uncertainties and School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu, P.R. China cannot simply be applied to deal with time-varying uncertainties in MDO.…”