Shun-Peng Zhu

Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty

A probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs operating under uncertainty is developed. The framework incorporates the overall uncertainties appearing in a structural integrity assessment. A comprehensive uncertainty quantification (UQ) procedure is presented to quantify multiple types of uncertainty using multiplicative and additive UQ methods. In addition, the factors that contribute the most to the resulting output uncertainty are investigated and identified for uncertainty reduction in decision-making. A high prediction accuracy of the proposed framework is validated through a comparison of model predictions to the experimental results of GH4133 superalloy and full-scale tests of aero engine high-pressure turbine discs.

Fatigue Life Estimation Considering Damaging and Strengthening of Low amplitude Loads under Different Load Sequences Using Fuzzy Sets Approach

In this study, based on the Miner rule, a new linear damage accumulation rule is proposed to consider the strengthening and damaging of low amplitude loads with different sequences using fuzzy sets theory. This model improves the application of the traditional Miner rule, by considering not only the damaging and strengthening of low amplitude loads, but also the load sequence effects. To apply the proposed model, the law of selecting membership functions for different load spectra is found, and different membership functions are investigated to show the important influence on estimating fatigue life. Applicability of the method is validated by comparing with the experimental data. It is also found that the predicted fatigue life by the proposed method is more accurate and reliable than that by the traditional ones.

Probabilistic Low Cycle Fatigue Life Prediction Using an Energy-Based Damage Parameter and Accounting for Model Uncertainty

Probabilistic methods have been widely used to account for uncertainty of various sources in predicting fatigue life for components or materials. The Bayesian approach can potentially give more complete estimates by combining test data with technological knowledge available from theoretical analyses and/or previous experimental results, and provides for uncertainty quantification and the ability to update predictions based on new data, which can save time and money. The aim of the present article is to develop a probabilistic methodology for low cycle fatigue life prediction using an energy-based damage parameter with Bayes’ theorem and to demonstrate the use of an efficient probabilistic method, moreover, to quantify model uncertainty resulting from creation of different deterministic model parameters. For most high-temperature structures, more than one model was created to represent the complicated behaviors of materials at high temperature. The uncertainty involved in selecting the best model from among all the possible models should not be ignored. Accordingly, a black-box approach is used to quantify the model uncertainty for three damage parameters (the generalized damage parameter, Smith–Watson–Topper and plastic strain energy density) using measured differences between experimental data and model predictions under a Bayesian inference framework. The verification cases were based on experimental data in the literature for the Ni-base superalloy GH4133 tested at various temperatures. Based on the experimentally determined distributions of material properties and model parameters, the predicted distributions of fatigue life agree with the experimental results. The results show that the uncertainty bounds using the generalized damage parameter for life prediction are tighter than that of Smith–Watson–Topper and plastic strain energy density methods based on the same available knowledge.

Bivariate Analysis of Incomplete Degradation Observations Based on Inverse Gaussian Processes and Copulas

Modern engineering systems are generally composed of multicomponents and are characterized as multifunctional. Condition monitoring and health management of these systems often confronts the difficulty of degradation analysis with multiple performance characteristics. Degradation observations generally exhibit an s-dependent nature and sometimes experience incomplete measurements. These issues necessitate investigating multiple s-dependent degradations analysis with incomplete observations. In this paper, a new type of bivariate degradation model based on inverse Gaussian processes and copulas is proposed. A two-stage Bayesian method is introduced to implement parameter estimation for the bivariate degradation model by treating the degradation processes and copula function separately. Degradation inferences for missing observation points, and for future observation points are investigated. A simulation study is presented to study the effectiveness of the dependence modeling and degradation inference of the proposed method. For demonstration, a bivariate degradation analysis of positioning accuracy and output power of heavy machine tools subject to incomplete measurements is provided.

Mean stress effect correction in strain energy-based fatigue life prediction of metals

A new mean stress corrected strain energy model is proposed for fatigue life prediction of metals. Specifically, a mean stress sensitivity parameter is incorporated into modify the dissipated strain energy by introducing two mean stress correction factors. The prediction accuracy of the proposed model is compared with those of Walker, Smith–Watson–Topper, Morrow, and generalized damage parameter models by using 13 experimental data sets. All data points for each material are, respectively, fitted into a single mean stress corrected strain energy-life curve. More accurate predictions are achieved by the proposed model for all data sets with lower model prediction errors than others.

An efficient life prediction methodology for low cycle fatigue–creep based on ductility exhaustion theory

Low cycle fatigue–creep is the main reason for the failures of many engineering components under high temperature and cyclic loading. Based on the exhaustion of the static toughness and dissipation of the plastic strain energy during fatigue failure, a new low cycle fatigue–creep life prediction model that is consistent with the fatigue–creep damage mechanism and sensitive to the fatigue damage process is presented in an attempt to develop viscosity-based approaches for general use in isothermal and thermo-mechanical loading. In this model, the theory of ductility exhaustion is used to describe the process of fatigue–creep interaction. It was assumed that the ductility exhaustion related only to the plastic strain and creep strain caused by tensile stress under stress-controlled conditions. In addition, the mechanisms of loading waveform, creep and mean stress effects were taken into account in a low cycle fatigue–creep regime. The predicted lives by the proposed model agree well with the reported experimental data from literature under different temperature loading conditions.

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

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.

A unified criterion for fatigue–creep life prediction of high temperature components:

A unified ductility criterion for fatigue–creep life prediction is presented based on the static fracture toughness exhaustion and dissipated cyclic strain energy density of high temperature components. It provides a general failure criterion for both low and high cycle fatigue regimes. The effects of mean stress, creep and loading waveform on fatigue life are incorporated into this criterion. Applicability and prediction accuracy of the newly proposed criterion was validated through comparing model predictions to experimental results taken from the literature. The results show that the proposed criterion is robust for different loading conditions and more accurate than other existing strain energy/ductility-based methods.

A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades

As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB) and Fatemi-Socie (FS) models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT) model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models.

A modified nonlinear fatigue damage accumulation model

This paper presents a modified nonlinear fatigue damage accumulation model accounting for load interaction effects. The original model is based on physical property degradation of materials, from which the load interaction effects are ignored. However, the load interaction effects have a significant influence on the fatigue life. In the study, by analyzing five damage models, a load interaction parameter is obtained and added to the original model. Experimental work is then carried out to verify the modified model of four categories of experimental data from smooth and notch specimens under two-level stress loading. Moreover, comparison is made among the results calculated by the test data, the Miner’s rule, the original model, and the modified model.