On fatigue life predictions for notched members by the nominal stress-based and the local strain-based methods

An autofrettaged thick-walled pressure vessel with an external groove subjected to a pulsating internal pressure can have fatigue failures at the external groove root due to the combination of tensile autofrettage residual stress, operating stress, and stress concentration. To predict the fatigue life of the autofrettaged thick-walled pressure vessel with an external groove, the local strain approach was applied. The residual stress distribution due to autofrettage and the operating stress distribution due to internal pressure were determined using finite element analysis which resulted in theoretical stress concentration factors. To account for the mean stress effects on the fatigue life prediction of the pressure vessel, low-cycle fatigue behavior with several strain ratios was obtained using smooth axial specimens taken from the ASTM A723 thick-walled steel pressure vessel. Fatigue life predictions were made by incorporating the local strains determined from the linear rule and Neuber’s rule and the Morrow and SWT mean stress parameters determined from low-cycle fatigue tests. The predicted fatigue lives were within factors of 2 to 4, compared to simulated experimental fatigue lives based upon fatigue cracks of 2.5 mm in length. These procedures appear to be realistic for evaluating fatigue lives for this complex pressure vessel.

The shear connector of a steel composite bridge is designed by predicting fatigue life using the fatigue strength curves (S-N curve) based on push-out test results. The fatigue strength curves of the current design codes present only a linear relationship between the stress range and fatigue life on a log scale based on push-out experiment results. However, an alternative to the current empirical formula is necessary for the fatigue design of shear connections involving many detailed variations or high strength steel materials. This study collected and reanalyzed data from push-out fatigue tests to determine the factors influencing fatigue life and propose a machine learning-based fatigue life prediction model. The proposed machine learning model demonstrated an improvement in predictive performance of approximately 2 to 8 times compared to the existing design codes when evaluated against experimental data. Feature importance analysis based on the proposed model revealed that the stress range most significantly influenced fatigue life prediction. Model validation results indicated that the proposed model provided reliable predictions with accuracy and generalization performance. Moreover, it effectively accounted for uncertainty by incorporating features previously overlooked in existing design codes. Plans for fine-tuning pretrained models were also discussed.

A Walker-based mean strain correction model of low-cycle fatigue (LFC) life prediction is proposed for high loaded parts. The model is based on a function depending on the strain range and strain ratio controlled in the strain-controlled LCF test of fatigue specimens and a constant reflecting the material sensitivity to strain ratio. The independence from the stress cycle parameters which can change during the strain-controlled LCF test is an obvious advantage of the model. The model was verified using the results of strain-controlled LCF tests of smooth titanium alloy Ti-6A1-4V ELI and iron-based alloy specimens conducted at room temperature. The proposed model was compared to the Smith - Watson - Topper and Walker models that take into account the mean stress effect. The proposed model provided the best prediction accuracy for titanium alloy. For Iron-based alloys the results obtained by the Walker model and the model proposed are close to each other. A simplified model based on the analysis of model parameters tailing into account the mean strain effect for predicting fatigue life of aeroengine critical parts is developed using a limited amount of experimental data when only the results of Rε = 0 tests are known. A comparison of the predicted life with the number of cycles to failure showed satisfactory results of fatigue life prediction for Ti-6A1-4V ELI and Iron-based alloys specimens.

ABSTRACTMixed‐mode (I and II) overloads are often encountered in an engineering structure due to either alteration of the loading direction or the presence of randomly oriented defects. Prediction of fatigue life in these cases is more complex than that of mode‐I overloads. The objective of this study is to explore the use of an artificial neural network (ANN) model for the prediction of fatigue crack growth rate under interspersed mixed‐mode (I and II) overload. The crack growth rates as predicted by the ANN method on two aluminium alloys, 7020 T7 and 2024 T3 have been compared with the experimental data and an Exponential Model. It is observed that the predicted results are in good agreement and facilitate determination of residual fatigue life.

Welded joints are used in many engineering applications, including aerospace, automotive, and structural engineering. However, notches in the welded components reduce their fatigue strength and lead to early failure through stress concentration. It is, therefore, crucial to comprehend and estimate the fatigue behaviour of friction-welded joints with a notch to ensure the structural integrity and component durability. This study aims to examine the notch fatigue behaviour of friction welded joints of UNS S31603 stainless steel and to build up regression models based on Machine Learning, such as Gaussian Process Regression (GPR) and Support Vector Regression (SVR) for accurate fatigue life prediction. Fatigue tests were performed on friction-welded UNS S31603 stainless steel specimens under strain-controlled conditions with fully reversed loading (R=-1) at a constant strain amplitude of 0.3%. The effect of notch width, depth and central angle on fatigue life was investigated. Experimental data was used to train the ML models, and hyperparameter tuning was done using grid search and 4-fold cross-validation. Model accuracy was measured by R², RMSE and MAPE values. The experimental results indicated that the fatigue life of notched welded joints is drastically reduced compared to the base metal, and deeper notches reduce the fatigue strength by up to 84%. It was observed that GPR outperformed SVR in the prediction of fatigue life and had an R² value of 0.9932 with RMSE of 8.61 for the parent material and an R² value of 0.9933 with RMSE of 15.76 for the welded joints. The results highlight the need to optimise notch design and welding conditions to enhance fatigue resistance in engineering applications. Major Findings: The current research investigated the detrimental effect of notch parameters on the fatigue life of both parent material and friction welded joints of UNS S31603. The work also found the GPR model to be the best fit regression model compared to the SVR.

A transfer learning-based approach to fatigue life prediction of corroded bimetallic steel bars using small samples

Butt Welds in Unstiffened Plates Butt welds are important connections in most types of welded structures. Examples are plated structures used in ships, floating offshore platforms, frame structures fabricated from tubular sections, tethers connecting tension leg platforms to the sea bottom, shell structures used in semi-submersible platforms for oil and gas production, towers for support structures for wind turbines, foundation piles, pipelines, risers, umbilicals, and so on. Many of these structures are subject to dynamic loading, and a reliable assessment of the hot spot stress at these connections is required for calculation of fatigue life. A stress concentration factor (SCF) can be defined as a stress magnification at a detail due either to the detail itself or to a fabrication tolerance, with the nominal stress as a reference value. The maximum stress is often referred to as the hot spot stress and is used in conjunction with S-N data for fatigue life calculation. It is also termed geometric stress or structural stress. This hot spot stress is derived as the SCF multiplied by the nominal stress. The effects of misalignment due to eccentricities at plate thickness transitions and fabrication tolerances on the hot spot stress also need to be considered. In scaled plate test specimens, additional stress due to angular misalignment resulting from welding distortion may also be of importance for the resulting hot spot stress, as explained in Section 2.2.1. However, such an effect is normally considered to be of less significance for actual structures than laboratory test specimens due to differences in boundary conditions during fabrication and loading. The angular deviation may be more significant for structures with thinner plates. SCFs due to misalignment at butt welds in plates were presented by Maddox (1985) and have been included in fatigue design rules for plated structures for many years. A simple butt weld between two plates, as shown in Figure 5.1, is considered as an introduction to the derivation of SCFs for butt welds. It is assumed that the plates are welded together from plates of the same size, with an eccentricity, δ, and without angular misalignment. The plates are subjected to a membrane loading per unit width N = σ nominal · t, where σ nominal is nominal stress and t = thickness of the plates.

Critical plane based method for multiaxial fatigue analysis of 316 stainless steel

Fatigue life prediction of laser and mechanically formed commercially pure grade 2 titanium alloy plates

Critical region method-based fatigue life prediction of notched steel wires of long-span bridges

In this study, a new fatigue life prediction and optimization strategy utilizing the Failure Tensor Polynomial in Fatigue (FTPF) model with exponential fitting and numerical bisection method for fiber reinforced polymer composites has been proposed. Within the experimental stage, glass/epoxy composite laminates with [Formula: see text], [Formula: see text], and [Formula: see text] lay-up configurations were fabricated, quasi-static and fatigue mechanical behavior of GFRP composites was characterized to be used in the FTPF model. The prediction capability of the FTPF model was tested based on the experimental data obtained for multidirectional laminates of various composite materials. Fatigue life prediction results of the glass/epoxy laminates were found to be better as compared to those for the linear fitting predictions. The results also indicated that the approach with exponential fitting provides better fatigue life predictions as compared to those obtained by linear fitting, especially for glass/epoxy laminates. Moreover, an optimization study using the proposed methodology for fatigue life advancement of the glass/epoxy laminates was performed by a powerful hybrid algorithm, PSA/GPSA. So, two optimization scenarios including various loading configurations were considered. The optimization results exhibited that the optimized stacking sequences having maximized fatigue life can be obtained in various loading cases. It was also revealed that the tension-compression loading and the loadings involving shear loads are critical for fatigue, and further improvement in fatigue life may be achieved by designing only symmetric lay-ups instead of symmetric-balanced and diversification of fiber angles to be used in the optimization.

In spite of the tough pitch copper material is used for the many kinds of conductors of electrical machining devices, the fatigue phenomenon of the tough pitch copper material does not still clarify under variable stresses considering to a service loading. Then, constant stress amplitude fatigue tests were carried out for the tough pitch copper sheet material and then the fatigue life under variable stresses were predicted by Miner's law using constant stress tests results as shown S-Ndiagram. The program fatigue tests consist of two steps and multifold stress levels were carried out for tough pitch copper sheet specimens compared with the fatigue lives predicted by using Miner's law. As it was clear that the fatigue lives predicted by using Miner's law were shorter than the experimental program fatigue lives under variable stresses in service loading, so new practical diagram modified from original S-N diagram was proposed. The fatigue lives predicted by using new S-N diagram coincide with experimental fatigue lives under variable stress consist of two or three step and multifold stress levels.

An energy density zone (EDZ) model is developed for the prediction of fatigue life. The microscopic effects can be involved in the EDZ model. Three scale transitional functions in the model are utilized to describe the trans‐scale behaviours of fatigue failure from micro‐scale to macro‐scale. Fatigue failure behaviours of a low‐alloy and ultra‐high‐strength steel material (i.e. 40CrNi2Si2MoVA steel) is investigated. Two fatigue parameters in the model are determined from the experimental S–N curves for the smooth cylinder specimens (the stress concentration factor, SCF, Kt = 1). Then, fatigue lives of notched specimens with SCFs Kt = 2 and Kt = 3 are predicted respectively by the proposed model. The predicted S–N curves are satisfactory in comparison with the experimental results. Scatter of the fatigue test data can be depicted when the microscopic effects are considered. Influences of microscopic effects on the fatigue behaviours are explored by means of numerical simulations.

The main objective of this paper is to accurately obtain fatigue life prediction for the key components of a turning mechanism using the improved theory of critical distances (TCD). The irregularly shaped rotating arm is the central stressed part of the turning mechanism, which contains notches. It has been found that TCD achieves good results in predicting the fatigue strength or fatigue life of notched components with regular shape but is less commonly used for notched components with irregular shape. Therefore, TCD was improved and applied broadly to predict the fatigue life of an irregularly shaped rotating arm. Firstly, the notch depth and structure net width parameters were introduced into the low-order and low-accuracy classical TCD function to obtain a novel stress function with high computational efficiency and high accuracy, whereas the stress concentration factor was introduced to modify the length of critical distance. Secondly, the improved TCD was used to predict the fatigue strength of notched components with regular shape, and its accuracy was demonstrated by a fatigue experiment. Finally, the improved TCD was applied to predict the fatigue life of an irregularly shaped rotating arm. The deviation between prediction results and experimental results is less than 18%. The results demonstrate that the improved TCD can be applied effectively and accurately to predict the fatigue life of key components of turning mechanisms.

Previously published studies have proposed fatigue life prediction models for dense graded asphalt pavement based on flexural fatigue test. This study focused on the fatigue life prediction of High Modulus Asphalt Concrete (HMAC) pavement using the local strain-stress method and direct tension fatigue test. First, the direct tension fatigue test at various strain levels was conducted on HMAC prism samples cut from plate specimens. Afterwards, their true stress-strain loop curves were obtained and modified to develop the strain-fatigue life equation. Then the nominal strain of HMAC course determined using finite element method was converted into local strain using the Neuber method. Finally, based on the established fatigue equation and converted local strain, a method to predict the pavement fatigue crack initiation life was proposed and the fatigue life of a typical HMAC overlay pavement which runs a risk of bottom-up cracking was predicted and validated. Results show that the proposed method was able to produce satisfactory crack initiation life.