Prediction Of Fatigue Crack Growth Rate Research Articles

Model for predicting type Ι fatigue crack growth rate in RKE field considering stress gradient

Based on the stress–strain field at the crack tip of Rice-Kujawski-Ellyin (RKE) and considering the stress gradient effect near the crack tip of type I, a fatigue crack growth rate prediction model L-SG (RKE) for type I is proposed in this paper. Firstly, the stress gradient change value of 1 % at the crack tip is considered as the characteristic distance (stress gradient influence range), and the ratio of the equivalent stress to the far-field stress in the stress gradient influence range is defined as the stress gradient influence coefficient ρ; Secondly, the new model L-SG (RKE) is proposed to quantitatively describe the fatigue crack growth behavior by using the stress–strain field at the crack tip of RKE, and the stress gradient influence coefficient ρ is introduced, and then the crack tip passivation radius rp is defined to eliminate the crack tip singularity, and the plastic strain energy failure criterion is combined.; Finally, the prediction effect of the L-SG (RKE) model is verified by 6 metal materials and the fatigue crack growth rate test results of 2 groups of 45 steel CT specimens, and compared with the SHI-CAI (RKE) model. At the same time, based on the R2 fitting effect and the different requirements of the three stages of fatigue crack propagation, the prediction effect of the two prediction models is analyzed, and comprehensive evaluation from two aspects of safety and accuracy. The results show that the L-SG (RKE) prediction model can better reflect the actual fatigue crack propagation behavior, and can meet the requirements of practical engineering for the accuracy and safety of the prediction model. Especially, the prediction results of physical cracks in 45 steel shaft parts by this model agrees well with the experimental data.

Predicting fatigue crack growth rate of cement-based and asphalt paving materials based on indirect tensile cyclic loading tests

Fatigue crack growth rate (FCGR) is a critical indicator that reflects the rate at which material deterioration occurs under cyclic loads. However, there is currently a lack of a mechanistic quantitative analysis and prediction of the FCGR of paving materials under external indirect tensile (IDT) cyclic loads. To address this issue, this study aims to develop a mechanistic model for quantitative analysis and prediction of the FCGR in paving materials subjected to external IDT cyclic loads based on the J-integral based Paris’ law. Two types of paving materials, namely cement-treated aggregates and asphalt mixtures, were selected to demonstrate the results and model of the FCGR. The results indicate that the derived J-integral serves as the driving force for crack growth and is influenced by horizontal tensile stress, initial resilient modulus, damage density, specimen size, and surface energy of the paving materials. The fatigue life of cement-treated aggregates is primarily influenced by the crack initiation stage, while for asphalt mixtures, the crack growth stage plays a more significant role. The application of Paris’ law is found to be effective in predicting the FCGR at stable crack growth stage. The coefficients of Paris’ law exhibit minimal variation across different stress levels and loading frequencies, and can be utilized to evaluate the fatigue crack resistance of different paving materials.

Optimising fatigue crack growth predictions for small cracks under variable amplitude loading

The fatigue cracks in a fighter aircraft that pose the greatest threat to structural integrity and availability are usually less than 1 mm for most of their lives. However, it has long been recognised that small cracks can grow significantly faster than long cracks at the same stress intensity range (ΔK). This means predictions for small cracks growing under realistic spectrum loading can be significantly non-conservative when using linear elastic fracture mechanics and long crack-based empirical rate data. Previous work showed empirical rate data based on small cracks grown under constant amplitude (CA) loading could significantly improve predictions. However, such data still have limitations related to an inability to predict the spectrum history effects that influence small cracks. This paper presents a method to optimise a model to predict fatigue crack growth rates for cracks loaded with realistic spectra. This method is demonstrated for small cracks in Aluminium Alloy 7050-T7451 grown under fighter wing root spectrum loading. Numerical optimisation is used to select model parameters that minimise fatigue crack growth rate prediction errors for a training dataset. This purpose-built model consistently outperformed a generic model based on the growth of small cracks under CA loading.

Fatigue Crack Growth Rate Prediction in Nickle based Super-alloys using Machine Learning Algorithm

The state-of-the-art research in any field is inclined towards the use of artificial intelligence (AI) and machine learning (ML) techniques due to their versatility and ease of application without compromise in the results. Predicting the service life of structural members subjected to fatigue loading, is a daunting task and is currently dependent on experimental, finite element (FE) and/or numerical approaches. Damage tolerant (DT) design incorporates fatigue crack growth rate (FCGR) test data to avoid catastrophic structural failure and is proven to be successful in predicting the life of a component. Such predictions also prove beneficial in applications such as structural health monitoring (SHM) and planning non-destructive inspection. Prediction methods and models, currently used, are application specific or inconsistent across different applications. Hence in the present work, an ML algorithm is proposed to predict the Paris region of the FCGR curve for nickel based super alloys, viz. GTM 720 and GTM 718. Experimental dataset for various stress ratios (R) of the alloys were used to train the back propagation neural network (BPNN) algorithm. The algorithm was appropriately tuned and evaluated so as to fit the training data well and achieve good generalization. Using this trained ML algorithm, the FCGR was predicted for a different stress ratio and compared with experimental results of GTM 720 and GTM 718, available in literature. The results obtained are quite comparable indicating promising applications for ML based algorithms in FCGR prediction.

Machine learning based short fatigue crack growth rate prediction for aluminium alloys

As a result of different fatigue characteristics influenced by intricate microstructures, comparing with fatigue crack growth rate in long fatigue crack region, the growth in the short one is more complex to be fitted with fewer parameters. There have been more restrictions for traditional models in describing the nonlinearity between the fatigue crack growth rate and stress intensity factor range in short crack regime. Due to their outstanding ability in prediction with high accuracy and in description of nonlinearity with satisfactory flexibility, machine learning approaches have been payed more attention. The machine learning models have been the better choices to deal with the limitation in fatigue-related problems which traditional solutions cannot overcome. In this paper, two machine learning algorithms: k-nearest neighbour algorithm (KNN) and random forest (RF) are implemented to predict the short fatigue crack growth rate for 2024-T3 and LC9cs aluminium alloys. The testing outcomes of these applied machine learning algorithms are compared to evaluate their prediction abilities. The final results reveal that the values of Pearson correlation coefficient R2 of the KNN are generally higher than that of another method for each material. Each of them has an excellent performance in accuracy and effectiveness, and all of them have excellent extrapolation capabilities to predict the nonlinearity.

Cyclic cohesive zone model damage parameter acquisition for fatigue crack growth considering crack closure effect

This paper presents a method to obtain damage parameters for cyclic cohesive zone model based on the crack closure experiments. The damage evolution is modified by introducing equivalent separation to quantify the nonuniform damage distribution along the crack path. The damage parameters acquisition is realized with digital image correlation analysis, where the effect of crack closure is accordingly elaborated. An adaptive cycle jump technique is established based on the damage rate, aiming to reduce the computational cost. Compared with the experimental data, the proposed model exhibits the capability in predicting fatigue crack growth rate.

Artificial neural network based fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters

In this paper, the fracture behavior and fatigue crack growth rate of the 2024-T351 aluminum alloy has been investigated. At first, the 2024-T351 aluminum alloys have been welded using friction stir welding procedure and the fracture toughness and fatigue crack growth rate of the CT specimens have been studied experimentally based on ASTM standards. After that, in order to predict fatigue crack growth rate and fracture toughness, artificial neural network is used. To obtain the best neuron number in the hidden layer of the artificial neural network, different neuron numbers are tested and the best network based on the performance is selected. Then the fitting method is applied and the fitted surfaces that illustrate the behavior of welding are shown and the results of artificial neural network and fitting method are compared. Also, multi-objective optimization algorithm is used to obtain the best welding parameters and finally sensitivity analysis is applied to measure the effect of rotational and traverse speeds on the fracture toughness and fatigue crack growth rate.

Research on fatigue crack growth behavior: Experimental and prediction method of titanium alloy

A new type of titanium alloy for the pressure shell of a manned deep-sea submersible is studied. The fatigue performance and the fracture toughness of the titanium alloy are obtained under R = 0.03, 0.3, and 0.5. The curves of fatigue crack growth rate under three load ratios are predicted based on the existing fatigue crack growth rate prediction model. The results show that the fatigue crack growth threshold decreases with the increase of the load ratio, and the fatigue crack growth rate increases with the increase of the load ratio. The fatigue crack growth prediction model can accurately predict the fatigue crack growth rate of titanium alloy under different load ratios.

Modelling fatigue crack growth in shape memory alloys

AbstractWe present a phase field‐based framework for modelling fatigue damage in Shape Memory Alloys (SMAs). The model combines, for the first time: (i) a generalized phase field description of fracture, incorporating multiple phase field formulations, (ii) a constitutive model for SMAs, based on a Drucker–Prager form of the transformation surface, and (iii) a fatigue degradation function, with damage driven by both elastic and transformation strains. The theoretical framework is numerically implemented, and the resulting linearized system is solved using a robust monolithic scheme, based on quasi‐Newton methods. Several paradigmatic boundary value problems are addressed to gain insight into the role of transformation stresses, stress‐strain hysteresis, and temperature. Namely, we compute Δε − N curves, quantify Paris law parameters, and predict fatigue crack growth rates in several geometries. In addition, the potential of the model for solving large‐scale problems is demonstrated by simulating the fatigue failure of a 3D lattice structure.

Effect of underloads in small fatigue crack growth

There is considerable cost incurred within the aircraft industry due to the inability to accurately predict fatigue crack growth rates for complex loading scenarios. This is particularly the case for small cracks. This paper aims to facilitate the improvement of fatigue crack growth by investigating the effects of underloads on small cracks grown in the common airframe structural aluminium alloy; AA7050-T7451. Six novel loading spectra were used to quantify how underload spacing, magnitude, and consecutive application impact crack growth. Quantitative fractography of post-test fractures enabled crack growth measurements to be made at crack lengths as small as 100 µm. It was found that underloads accelerate growth rates most significantly for small cracks, though this effect appears to progressively diminish as the crack grows. The results also suggest that underloads may have both short and long-term effects on crack growth. This research paves the way for accounting for the acceleration of crack growth rates caused for small cracks in predictions, which if not considered, could lead to non-conservative fatigue life predictions. Ultimately, this should allow for more accurate growth rate prediction of high strength aluminium structures subject to underloads, as well as provide quantitative basis for future mechanistic studies.

Numerical analysis of fatigue crack growth under SuperBlock2020 load sequence

The components are usually submitted to variable amplitude loading, and it is important to understand the mechanisms explaining fatigue crack growth (FCG) rate variations. The relative importance of residual stresses and crack closure, in particular, is a controversial issue. This work studies a specific load pattern, called Super Block 2020, composed of four pairs of load blocks of different amplitude (A, B, C and D) and the same maximum load, separated by overloads. The transition from the overloads to the constant amplitude load blocks occurred alternatively from the maximum or minimum loads of the overload cycles. These patterns, called i1 and i2 for load blocks i (i = A, B, C or D), produce different residual stresses ahead of crack tip. A numerical procedure was followed to predict FCG rate in the 2024-T351 aluminium alloy, based on cumulative plastic strain. This approach includes the effects of material hardening, crack tip blunting, crack closure and partial crack closure. A significant difference was found between FCG rate and crack increments produced by i1 and i2 load blocks. The numerical predictions are according the experimental trends and crack closure was found to be the main mechanism behind FCG trends.

Fatigue Crack Monitoring of T-Type Joints in Steel Offshore Oil and Gas Jacket Platform.

Several approaches have been used in the past to predict fatigue crack growth rates in T-joints of the offshore structures, but there are relatively few cases of applying structural health monitoring during the non-destructive testing of jacket platforms. This paper presents an experimental method based on the sensing of the piezoelectric sensors and finite element analysis method for studying the fatigue cracks in the offshore steel jacket structure. Three types of joints are selected in the current research work: T-type plate, T-type tube-plate, and T-type tube joints. The finite element analysis model established in the current study computes and analyzes the high stress and high strain regions in the T-type joints. The fatigue damage in the T-type joints was successfully detected by utilizing both the finite element analysis and experimental methods. The results showed that fatigue cracks of the three types of joints are prone to appear at the weld toe and spread in the welding direction. The fatigue damage location of T-type plate and T-type tube-plate joints is more concentrated in the upper weld toe area, and the fatigue damage location of the T-type tube joint is closer to the lower weld toe area.

Predicting fatigue crack growth rate under block spectrum loading based on temperature evolution using the degradation-entropy generation theorem

This study presents the temperature evolution of dual-phase steel in the prediction of the fatigue crack growth rate under block spectrum loading. The degradation coefficient that can be determined from the degradation-entropy generation theorem can be obtained based on the relationship between entropy generation and crack growth. The fatigue crack growth rate under block spectrum loading was then evaluated using the measured surface temperature evolution of the specimen during a fatigue crack growth test. The results of the present model were then compared with experimental fatigue data and the correlation coefficient $$(R^{\mathrm {2}})$$ in all conditions was observed to be more than 0.8. Therefore, the results show that entropy generation of the specimen is a reliable parameter in predicting fatigue crack growth rate under block spectrum loading using the intensity of the degradation coefficient.

A kinetics-based model of fatigue crack growth rate in bituminous material

This study aims to propose a kinetics-based model of fatigue crack growth rate coupling with temperature, strain level and damage degree for bituminous materials. The fatigue crack length is calculated by an energy-based mechanistic (EBM) approach, and kinetic parameters characterizing the fatigue crack growth rate are determined based on an Arrhenius equation. Results show that the logarithm of the fatigue crack growth rate is linear to the inverse of absolute temperature, and cracking activation energy is independent of strain level and damage degree. Besides, the proposed kinetics-based model can predict fatigue crack growth rate at arbitrary temperature, strain level and damage degree of bituminous materials.

Analytical modeling of fatigue crack propagation based on cyclic hardening and a characteristic damage length

An analytical fatigue crack growth model is developed, which combines effectively a cyclic energy dissipation approach and the strain energy density theory. The model uses cyclic material properties and relies on cyclic hardening for fatigue crack growth rate prediction. Fatigue crack propagation occurs incrementally by a characteristic damage length, which is in the length scale of striation spacing in commercial aluminum alloy, supporting the model’s physical background. Analytical crack propagation rates correlate well with existing experimental data, in material with uniform strength and strength gradient, showing the ability of the model to account for strength variation at the crack path.

Crack growth rate prediction based on damage accumulation functions for creep-fatigue interaction

The present study is concerned with formulation of a model for the creep–fatigue crack growth rate prediction on the base of fracture damage zone concepts. It is supposed that crack growth rate can be determined by integration of damage accumulation rate equations into the fracture process zone for low-cycle fatigue and creep loading independently. In the case of low-cycle fatigue loading the damage accumulation function proposed by Ye and Wang was used as well as a classical Kachanov-Rabotnov power law was employment for the creep damage accumulation characterization. Fracture process zone size is calculated on the base of the nonlinear stress intensity factors concept proposed by Shlyannikov. The background for the proposed general model of crack growth rate under creep and fatigue interaction is given in order to comparison with the experimental data. Experimental study of crack growth rate under creep and fatigue interaction is performed for compact tension specimen made from 20CrMoV5. Crack growth rate carried out at the elevated temperature of 550°C according to ASTM E2760 standard. The predictions of the crack growth rate were compared with the experimental data for the 20CrMoV5 steel obtained at an elevated temperature, and the agreement was found to be satisfactory.

Effect of kinematic hardening parameters on fatigue crack growth

The parametric study of the effect of material properties on fatigue crack growth (FCG) rarely has been addressed in literature. The consideration of plastic CTOD as crack driving force opened the opportunity to predict FCG rate numerically and therefore to develop parametric studies focused on the effect of loading, geometrical and material parameters. The objective here is to study the effect of kinematic saturation stress, XSat, and kinematic saturation rate, CX, on FCG using this numerical approach. The increase of the kinematic parameters reduced the plastic CTOD and therefore the FCG rate. The variation is non-linear and the rate of variation of δp decreases with the increase of XSat and CX. The effect of the kinematic saturation stress, XSat, is more relevant than the effect of kinematic saturation rate, CX. On the other hand, a small effect of kinematic hardening parameters on crack closure was found. Finally, the increase of the number of load cycles between crack increments produced a great reduction of crack closure but no effect of plastic CTOD on models without contact of crack flanks.

Creep–fatigue crack growth rate prediction based on fracture damage zone models

Based on a new fracture damage zone formulation and nonlinear elastic–plastic and creep crack tip fields, the prediction of creep–fatigue crack growth rate is studied. A unified crack growth rate equation is derived using the equivalent nonlinear stress intensity factor, monotonic low-cycle fatigue, and creep material properties at an elevated temperature. The crack growth rate model includes the size of the fracture process zone and damage parameters. The predicted creep–fatigue crack growth rates are compared with the experimental data of the 12Cr1MoV power plant steel and good agreement is observed.

Reliability study on fracture and fatigue behavior of pavement materials using SCB specimen

ABSTRACT Reliability of semi-circular bending (SCB) specimen for measuring the fracture behaviour of pavement materials under static and cyclic loadings has been examined. This study is divided into three phases. In the first phase a comparison between different equations suggested by several specifications and by researchers has been made. Three different SCB specimen types used for predicting mixed mode fracture behaviour of pavement materials have been evaluated in the second phase. In the third phase the applicability of using SCB specimen in predicting fatigue crack growth rate in pavement materials under mode I has been examined. 3-D finite element analysis (FEA) has been adopted. Although there is conformity of the specimen dimensions there is no unique equation to measure the fracture parameters. The prediction of the fracture behaviour of pavement materials obtained by the present FEA is acceptable. The value of KIC predicted from each specimen type has been examined for its reliability by using the concept of maximum size of non-damaged defect (d max). Mode I fracture toughness predicted by SCB-1 (standard specimen) is the only consistent value, while SCB-2 and SCB-3 (specimens with shifted crack) failed in this reliability test. To check the reliability of SCB specimen for measuring the fatigue behaviour of pavement materials, the relation between the stress intensity factor range (ΔK) and the crack mouth opening displacement (CMOD) through the whole life of the specimen has been examined. A good relation is found between the CMOD and the ΔK through the whole life of SCB specimen.

Numerical assessment of cyclic J-integral △J for predicting fatigue crack growth rate

The cyclic J-integral is a significant mechanical parameter to describe the elastic-plastic fatigue crack growth rate. A equivalent domain integral method based on finite element method was proposed for evaluating the cyclic J-integral. This numerical method was verified by comparing the results of cyclic J-integral with J-integral evaluated by using the built-in functionality of ABAQUS under monotonic tensile load. Base on this numerical method, the uniqueness of extreme value of cyclic J-integral was studied through a kinked crack and a specific code was also developed to simulate the crack propagation in 304 stainless steel (304SS) compact tension (CT) specimen under mode I loading. The expression of crack growth rate was established based on the cyclic J-integral obtained by the specific code and this expression is found to be in good agreement with the experimental results. The research contents in this paper may contribute to the damage tolerance assessment of components.