Predict Crack Growth Research Articles

Validation of assessment methods for creep crack growth rates in irradiated components from Nimonic PE16 Tie-Bar tests

Creep crack growth is a life-limiting failure mechanism in high-temperature metallic components. The creep crack growth response is linked to the underlying creep deformation and failure properties, such as creep ductility. Irradiation effects such as helium (He) embrittlement in high-temperature reactor components trigger decreases in creep ductility. Creep crack growth (CCG) data obtained from unirradiated and irradiated Nimonic PE16 tie-bars confirm the accelerated crack growth rates under neutron irradiated conditions. The exact same data were also used to validate the analytical defect assessment procedure for transient creep crack growth in Code Case N-934 of ASME BPVC Section XI Division 2, developed from unirradiated material data. To do so, the mechanics-based creep crack growth law of Nikbin-Smith-Webster (NSW) is adopted to estimate the crack growth rates in unirradiated PE16, and then adjusted through changes in bulk mechanical properties in the irradiated case to estimate the changes in crack growth rates. The estimated ȧ-C∗ trend was employed as part of the analytical defect assessment procedure for transient creep crack growth in Code Case N-934 of ASME BPVC Section XI Division 2. Evaluation of results via the procedure and the estimated trends confirm the validity of the approach to predict increases in creep crack growth in neutron irradiated components, as observed in experimental data. The approach yields moderately conservative predictions for crack growth rates, and accurately captures the relative increase in creep crack growth rates for the irradiated case. The predictions were independently validated by predicting the C*-values expected in the loading configuration for a given recorded crack growth rate ȧ. The validation of the defect assessment method introduced in Code Case N-934 against both unirradiated and irradiated PE16 CCG data provides a practical path to its implementation in metallic components across high-temperature reactor designs. This is particularly useful where crack growth data in irradiated material may not be readily available. The technique also allows for propagating uncertainties in crack growth predictions which stems from compounding effects such as variability in unirradiated properties, degree of irradiation and corresponding embrittling effects, crack size and load perturbations. The relevance of mechanical properties accurately depicting aspects of the He embrittlement process for practical applications in plant and the importance of creep crack growth testing are discussed.

AI-Enhanced Prediction of Pavement Crack Propagation: A Study Using Traffic Load, Environmental and Material Data

This study develops an AI-based predictive model for forecasting pavement crack propagation by integrating traffic load, environmental conditions, and material property data. Traditional pavement management systems often struggle to accurately predict crack growth due to the complex interactions between these influencing factors. By leveraging data from various sources, including sensor-based traffic metrics, meteorological data, and material composition tests, this study identifies significant variables contributing to crack initiation and progression. The proposed model utilizes a blend of machine learning algorithms, including Random Forest and neural networks, with a cross-validation approach to ensure robustness. Results indicate that the model achieves high prediction accuracy, with an RMSE of 1.2 mm/year and an R-squared value close to 0.93. The findings support the use of AI-enhanced models as reliable tools for road infrastructure planning and maintenance, promising reductions in maintenance costs and improved pavement durability.

Prognosis of reflective pavement cracking development with Bayesian updating and surrogate models

ABSTRACT The main objective of this study is to establish an integrated prognostic method for predicting the development of thermal-induced reflective cracking in asphalt overlay on concrete pavement. The integrated prognosis process for crack growth is developed on the modified Paris’ law and includes three steps: (1) calculation of J-integral; (2) Bayesian updating of crack growth parameters and (3) prediction of remaining life. Finite element modelling (FEM) was conducted to calculate J-integrals at different crack depths and cold weather conditions. A surrogate model was built based on the original Kriging method and it shows high accuracy in predicting J-integrals from maximum air temperature, temperature drop and crack depth. The Bayesian updating process starts from the laboratory-measured distribution of fracture model parameters (A and n) in Paris’ Law and converges to the true values to match the measured crack depths at different loading cycles from field inspection. On the other hand, the consideration of material damage in asphalt overlay avoids over-estimation of remaining loading cycles for reflective cracking to reach the pavement surface. Further study is recommended to accurately assess in-situ pavement modulus and detect crack depth over concrete joints for implementation of the proposed prognostics method.

Application of ANN Concepts for Prediction of Crack Growth and Remaining Life of Circumferentially Cracked Piping Components under Different Loading Scenarios

This paper presents the details of Artificial Neural Network (ANN) based models to predict crack depth and remaining life of circumferentially part-through cracked piping components used in the nuclear industry. Crack growth data from experimental studies on (i) straight pipes made up of SA 312 Type 304LN stainless steel having part-through circumferential notch under combined bending and torsion and (ii) dissimilar metal pipe weld joints having circumferential through-wall crack in the weld were used. The dissimilar metal pipe weld joint is made up of SA312 Type 304LN austenitic stainless steel and SA508 Gr. 3 Cl. 1 low alloy carbon steel and joined by Nickel-rich Inconel alloy weld. About 75% of the mixed experimental data has been used for development of model and the remaining data for validation. For the development of ANN model, (i) back propagation technique (ii) sigmoidal transfer functions and (iii) Levenberg-Marquardt algorithm are used. The maximum percentage difference observed between the predicted and the experimental results for crack depth and remaining life was 19.59% and 15.78% respectively. The efficiency of the developed model was verified using several statistical parameters. The developed models are useful for the structural integrity assessment of piping components under different loading scenarios.

A deformation-diffusion interactive model to study crack-tip behaviour and predict crack growth rate under fatigue and hydrogen-embrittlement conditions

Hydrogen is accepted as a cleaner and more sustainable energy source, since it carries abundant energy and does not produce any effluent gas from burning when compared to fossil fuels. However, long-term degradation in mechanical properties, attributed to hydrogen embrittlement, is reported for metallic materials exposed to gaseous hydrogen, leading to accelerated crack growth behaviour under fatigue. In this paper, a visco-plastic deformation-diffusion interactive model is developed to study fatigue crack growth behaviour in a nickel-based superalloy under hydrogen-embrittlement condition. In the model, cyclic deformation is described by visco-plasticity constitutive model, while hydrogen diffusion is simulated by a modified form of Fick’s first law of diffusion which can address hydrogen diffusion driven by the hydrostatic stress gradient. In particular, trapped hydrogen, expressed as dependent on both diffusible hydrogen concentration and inelastic strain, is considered in the modelling of hydrogen diffusion. The model also describes the effects of hydrogen concentration on mechanical deformation by considering its influence on the evolution of isotropic hardening as well as on the strain state. Interaction between cyclic deformation and hydrogen diffusion is therefore studied for a crack tip in a compact tension specimen subjected to fatigue and hydrogen attack, showing a strong dependency on both loading frequency and stress intensity factor range. Subsequently, a two-parameter criterion is proposed for fatigue crack growth prediction, which accounts for the contributions of both cyclic deformation and hydrogen diffusion. The predictions show a good agreement with experimental data in terms of crack growth rate under fatigue and hydrogen-embrittlement conditions.

Investigation of the Process Parameters in Rotary Friction Welded Dissimilar AA7075/AA5083 Aluminum Alloy Joints on Fatigue Initiation using FEA and ANN

The rotary friction welding (RFW) method is one of the most widespread methods in the world for producing bimetallic components that require high mechanical strength. Simulations play a vital role in improving energy efficiency and reducing environmental impact, aligning with the sustainability goals of modern industry. A neural network (NN)-based incremental learning system was developed to predict crack growth and fatigue for AA5083 and AA7075 aluminum alloys. The results indicate the ability of this method to accommodate the input temperatures and the S-N curve and provide reliable predictions of expected fatigue. This method can reduce labor costs and time spent on crack propagation tests, enhancing the effectiveness of production processes and reducing process costs. This work also reveals the ability of neural . It maynetworks (NN) in monotonic function extrapolation like the S-N curve, which may pave the way for a wide variety of monotonic function-predicting problems. In future studies, a neural network (NN)-based increment learning scheme could be trained with random parts of individual S–N curves and applied to predict the rest. Additionally, the verification utilizing AISI 2205 and AISI 1020 steel has observed that neural networks may obtain S-N curve values for another metal with less than an 8% error rate. Friction pressure increases temperature, deformation, and stress in welding processes. Friction pressure 17 MPa increases temperature to 355 degrees Celsius, while Friction pressure 23 MPa increases deformation to 0.020 mm. A friction pressure of 29 MPa increases equivalent stress to 110 MPa. The indication of the S-N curve shows that increasing welding pressure increases Alternating Stress. Friction pressure also increases life, with minimum life cycles reaching 171040 cycles at 17 MPa, 195560 cycles at 23 MPa, and 283690 cycles at 29 MPa. Comparing research and simulation results, convergence is less than 8%, reducing error.

Numerical prediction on the fatigue debonding behaviour in a complex bi-material interface: A case study on wrapped composite joints

Debonding is one of the most critical failure modes for bonded joints under fatigue loads. Numerical prediction on the fatigue debonding behaviour of bonded interfaces with complex geometry still remains a problem. This paper proposes a numerical methodology based on fracture mechanics to predict crack growth in a complex bi-material interface and illustrates the prediction procedure by a case study on wrapped composite joints. Interface coupon tests provide the fatigue crack growth properties at the composite-to-steel interface used as inputs for finite element (FE) modelling. The FE model is calibrated against fatigue tests of small scale wrapped composite joints with different steel surface roughness subject to different load levels. A sensitivity analysis is conducted to investigate the influence of key modelling parameters. The calibrated model is validated against fatigue tests on upscaled joints. Good agreements are shown between the test and modelling results in terms of crack growth and stiffness degradation, demonstrating the potential of the proposed numerical methodology for predicting fatigue debonding behaviour of complex bi-material interfaces.

Simulation of fatigue crack growth in aluminium alloy 7075-T7351 under spike overload and aircraft spectrum loading

The trend towards virtual testing and digital-twin assisted management means that the accurate and reliable simulation of fatigue crack propagation behaviour is more important than ever. Reliable but conservative approaches to support this are in widespread use in the aerospace industry. Nevertheless, the conservatism comes at a significant cost in terms of reduced structural life and an increased ongoing inspection requirement and, as such leads to questions about the economic burden of these approaches. Recent comparisons between blind predictions and test results revealed the extent of the issue for cracking in aluminium alloy 7075-T7351 coupons with configuration and loading representative of military transport aircraft wing skins. The current models were generally conservative by a factor of two or more in terms of crack propagation life. This suggested that there was significant scope to improve the modelling to better reflect all the complex contributing factors. The current work has investigated the issue of changes in the crack front constraint as the crack progresses from a state of high constraint (close to plane strain) to a lower constraint (approaching plane stress). This issue was investigated both experimentally and with the development of an improved analytical model. A test program was conducted on several specimens, loaded under constant-amplitude, constant-amplitude with spike-overloads and a variable amplitude spectrum. Crack-opening stress levels were measured at key points in the tests and the results were used to develop and evaluate improved modelling approaches. The improved model was generally able to predict crack growth within about ± 30 % of that demonstrated along with the correct form of the crack growth, which is a significant advance and will lead to reduced costs and increased safety.

A Simplified Failure Assessment to Identify Crack Growth Behavior in the Gas Pipeline by Post-Hydrostatic Pressure

Hydrostatic pressure tests on pipelines have been found to be an inadequate means of critical integrity management due to the frequency of false negatives, which result from the inability of these tests to detect crack growth. It can be argued that focusing on pipe leakage does not guarantee future operability. A study presents a failure assessment methodology based on the failure assessment diagram (FAD), which aims to predict crack growth during hydrotesting. The calibrated pipe spool is validated by the application of data from hydrostatic tests and analytical techniques to ascertain the potential growth in circumferential surface cracks. A variety of factors, including pressure, material grades, flaw dimensions, and elliptical flaw angles, were examined in an effort to assess cracks. The results demonstrate that there is no pipeline leakage and minimal trapped air. Despite its location within the plastic zone, with a normalized pressure index of ≤1, the pipeline is deemed to be within acceptable limits according to the criteria established by the FAD. The assessment point was found to be predominantly influenced by the toughness ratio of the material grade. The crack propagated in the opposite direction with a maximum length a/c= 0.125 and a crack depth a/t= 0.2, which limited the toughness ratio. The load ratio indicates uniformity in elliptical angle flaw results. In this simplified failure assessment, the parameter describing the flaw size, which exhibits a strong correlation with the toughness ratio, plays a pivotal role. Further research and recommendations are also proposed.

Residual Pyramidal GAN (RP-GAN) for crack detection and prediction of crack growth in engineered cementitious composites

Crack detection has recently gained credence in the field of engineering automation. Engineered cementitious composites (ECC) are a durable, and environmentally friendly construction material and a suitable replacement for conventional concrete. As such, there is a need to automate the process of detecting the unique ductile crack formation and growth in ECC. This research focuses on detecting ECC cracks, accurately mapping the crack morphology, and predicting the crack growth patterns of this advanced material. We design and present a novel generative adversarial algorithm named Residual Pyramidal Generative Adversarial Network (RP-GAN), capable of ECC crack detection. RP-GAN is an enhanced and improved version of the typical Pix2Pix GAN for paired image-to-image translation. It is an extensive network that could be used for macro and micro-segmentation purposes in addition to domain translation tasks. In this research, we first investigate the ability of RP-GAN to detect ECC micro-cracks and map the dimensions of each crack. Secondly, we compared RP-GAN’s crack detection results with those of known state-of-the-art architectures. We then developed an algorithmic pipeline for live crack tracking using an experimental framework. Finally, we evaluate the possibility of detecting ECC crack growth and propagation using sequential images by re-engineering RP-GAN and fusing Convolutional-LSTM into its architecture. The mean intersection over union (IOU) test results of RP-GAN for ECC crack detection equaled 81.28%, and 77.76% for ECC crack propagation prediction.

Finite element analyses of rail head cracks: Predicting direction and rate of rolling contact fatigue crack growth

A numerical framework in 3D for predicting crack growth direction and rate in a rail head is presented. An inclined semi-circular surface-breaking gauge corner crack with frictionless crack faces is incorporated into a 60E1 rail model. The investigated load scenarios are wheel–rail contact, rail bending, thermal loading, and combinations of these. The crack growth direction is predicted using an accumulative vector crack tip displacement criterion, and Paris-type equations are employed to estimate crack growth rates. Results are evaluated along the crack front for varying crack radii and crack plane inclinations. Under the combined load cases and in the presence of tractive forces, the crack is generally predicted to go deeper into the rail than under pure contact. Crack growth rates for the combined load cases are higher than (but still close to) that for pure contact. A tractive force will increase growth rates for smaller cracks, whereas a steeper (45°) inclination will decrease the growth rate under the studied conditions as compared to a shallower (25°) inclination. Results should be of use for rail maintenance planning where deeper cracks require more machining efforts.

Insights into fatigue crack propagation behaviour of WAAM produced SS316 stainless steel: Molecular dynamics simulation and experimental analysis

The current work focuses on the crack growth mechanism / behavior of wire arc additively manufactured SS316L. Beside the experimental investigation, a molecular dynamics based polycrystalline model is developed to simulate the crack propagation under cyclic loading. The purpose of this work is to understand the crack growth behavior of wire arc additively manufactured SS316L, particularly the directional dependence of crack propagation. The experiments and molecular dynamics analysis are performed for the crack propagation along the build and traverse direction for the SS316L deposit. The experimental procedure involves fatigue crack growth rate tests, while the molecular dynamics simulations model the crack propagation in polycrystalline structures of different grain sizes. The ultimate tensile strength in build and traverse direction were 535±2 MPa and 495 ± 2 MPa, respectively. The experimental results reveal faster crack propagation along build direction in comparison to traverse direction. The values for Paris law material constants i.e. C and m are 7x10-15 and 6.78 along build direction while 8x10-14 and 6.02 along traverse direction, respectively. The crack growth along the build direction is primarily intergranular, which leads to high crack growth rate. The molecular dynamics simulations reveal the initiation and closure of secondary cracks for the traverse direction, which leads to slower crack growth rate along the traverse direction. The fractography of the fractured surfaces from fatigue crack growth rate test also indicate the formation of secondary cracks for the case of traverse direction. The molecular dynamics simulations performed with three grain sizes and thickness variation indicate the insensitivity of predicted crack growth mechanisms with respect to grain sizes used for simulations.

Prediction of crack growth in polycrystalline XH73M nickel-based alloy at thermo-mechanical and isothermal fatigue loading

Prediction of crack growth in polycrystalline XH73M nickel-based alloy at thermo-mechanical and isothermal fatigue loading

Probabilistic Fatigue Crack Growth Prediction for Pipelines with Initial Flaws

This paper presents a probabilistic method to predict fatigue crack growth for surface flaws in pipelines using a particle filtering method based on Bayes theorem. The random response of the fatigue behavior is updated continuously as measured data are accumulated by the particle filtering method. Fatigue crack growth is then predicted through an iterative process in which particles with a high probability are reproduced more during the update process, and particles with a lower probability are removed through a resampling procedure. The effectiveness of the particle filtering method was confirmed by controlling the depth and length direction of the cracks in the pipeline and predicting crack growth in one- and two-dimensional cases. In addition, the fatigue crack growth and remaining service life with a 90% confidence interval were predicted based on the findings of previous studies, and the relationship between the fatigue crack growth rate and the crack size was explained through the Paris’ law, which represents fatigue crack growth. Finally, the applicability of the particle filtering method under different diameters, aspect ratios, and materials was investigated by considering the negative correlation between the Paris’ law parameters.

Predicting the mixed-mode fracture propagation in single-leg bending using a radial point interpolation meshless method

Adhesive bonding is a widely used joining technique with increasing applications in the automotive and aircraft industries. However, the numerical simulation of adhesively bonded joints is challenging due to the intricate mechanical behavior of the bonding layer, especially when structures are subjected to mixed-mode loading. This work proposes a meshless fracture propagation algorithm to simulate mixed-mode fracture propagation in single-leg bending (SLB) adhesive joints. The proposed algorithm combines the radial point interpolation method (RPIM) with a mixed-mode strain-based criterion to predict crack growth. The RPIM permits a flexible discretization of the fracture region and eases the geometric remeshing of the integration cells to account for the crack tip propagation. Additionally, the RPIM provides accurate and smooth strain/stress fields, allowing implementation of the mixed-mode fracture criterion. The numerical model was validated against experimental data for SLB adhesive joints with a brittle adhesive. The results showed that the proposed algorithm can accurately predict the resistance curves and critical energy release rates of the adhesive joints.

Fatigue Crack and Residual Life Prediction Based on an Adaptive Dynamic Bayesian Network

Monitoring the health status of aerospace structures during their service lives is a critical endeavor, aimed at precisely evaluating their operational condition through observation data and physical modeling. This study proposes a probabilistic assessment approach utilizing Dynamic Bayesian Networks (DBNs), enhanced by an improved adaptive particle filtering technique. This approach combines physical modeling with various predictive sources, encompassing cognitive uncertainties inherent in stochastic predictions and crack propagation forecasts. By employing crack observation data, it facilitates predictions of crack growth and the residual life of metal structure. To demonstrate the efficacy of this method, the research leverages data from three-point bending and single-edge tension fatigue tests. It gathers data on crack length during the fatigue crack progression, integrating these findings with digital twin theory to forecast the residual fatigue life of the specimens. The outcomes show that the adaptive DBN model can precisely predict fatigue crack propagation in test specimens, offering a potential tool for the online health assessment and life evaluation for aerospace structures.

Defect-free grinding of silicon nitride at high material removal rate

Owing to the extreme hardness and toughness of sintered silicon nitride (Si3N4), the material is used in high stress and/or temperature applications such bearings, turbines, and combustion engines. Unfortunately, the same properties which make it ideal for use also make it particularly difficult to machine -- microcracks, inclusions and spalling are all common. While prior research has shown that it is possible to grind sintered Si3N4 without inducing surface damage so long as material is removed entirely under ductile flow, but grind forces associated with ductile Si3N4 material flow are so small as to render the material removal rate (MRR) impractical. Prior researchers have attempted to solve the MRR problem through laser-assisted machining. Laser ablation, by inducing a steep thermal gradient, weakens material through surface and subsurface cracks. Grinding of fractured weakened Si3N4 has been done at upwards of 50 % higher MRR. There are, however, issues with laser ablation, which prevent its widespread use. Laser ablation severely disrupts the microstructure of Si3N4. Because cracks propagate along and through grain boundaries, the irregular morphology makes accurately predicting crack growth from ablation and during subsequent grinding highly problematic. In this proof-of-concept work, researchers determined that it is possible to irradiation weaken Si3N4 without cracking it, and the material can be ground defect-free at a highly productive MRR. Findings suggest present laser-assisted machining methods which fracture weaken Si3N4 prior to grinding may not be the best way to maximize MRR.

Mastering the art: Proficient finite element implementation and robust evaluation of a strain-hardening porous ductile material crack growth prediction model at finite strain

Accurate prediction of crack extension is crucial for ensuring the structural integrity of metal components exposed to diverse loads. While the Gurson model and its extensions are widely accepted for delineating ductile fracture stages, especially in porous materials with a rigid-perfectly plastic matrix, their efficacy diminishes in the presence of strain-hardening matrices. To address this limitation, our study introduces a robust numerical implementation and assessment of Perrin's model. In contrast to Gurson's approach, Perrin's model incorporates two distinct strain-hardening parameters derived from an intricate analysis of a strain-hardening hollow sphere subjected to axisymmetric loading.Moving beyond theoretical discussions, this paper actively engages in the rigorous evaluation of Perrin's model under various scenarios, encompassing isotropic, kinematic, and mixed isotropic-kinematic hardening conditions. The model's effectiveness is convincingly demonstrated through meticulous comparisons between numerical simulations and real-world experimental observations conducted on pre-cracked specimens.Facing challenges related to achieving global elastic-plastic convergence in large-scale simulations, our research introduces a sophisticated approach. Leveraging stiffness tangent moduli ensure the maintenance of quadratic convergence in global Newton method iterations. This not only enhances the reliability of our simulations but also underscores the practical applicability of our findings.The study also focuses on the necking and crack propagation of a cylindrical specimen through meticulous computational modeling. Our mesh captures intricate details and addresses stress gradients, revealing coplanar crack propagation contrary to prior beliefs. The confirmation of the cup-cone fracture effect challenges previous interpretations, emphasizing the critical role of void nucleation. This reinforces the credibility and applicability of our approach in advancing the understanding of material fracture behavior.In summary, this study significantly contributes to existing knowledge in fracture prediction models, offering a robust framework for predicting ductile fracture under substantial deformations. The presented findings pave the way for advancements in structural engineering, providing invaluable insights for optimizing the performance and resilience of metal structures in real-world applications.

Fatigue Crack Propagation of 51CrV4 Steels for Leaf Spring Suspensions of Railway Freight Wagons.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible, which can lead to economic and human catastrophes. The aim of this document was to precisely characterise the mechanical crack growth behaviour of the chromium-vanadium alloyed steel representative of leaf springs under cyclic conditions, that is, the crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio were also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

The effect of fibre orientation on fatigue crack propagation in CFRP: Finite fracture mechanics modelling for open-hole configuration

The demand to capture translaminar crack growth under fatigue loading scenarios led this work contribution to carry out the Finite Fracture Mechanics (FFM) method in fatigue damage growth and the application of the Paris model to generate the translaminar damage propagation prediction. The purpose of this study is to analyse the effect of fibre orientation on translaminar crack propagation rate using the FFM model, which includes cycle damage increment estimation and fractographic analysis. The results confirm the feasibility of FFM in predicting crack growth and estimating life under cyclic loading. However, C-scan analysis and the revised crack propagation direction are critical in determining the realistic crack length, considering adhesive failure along the fibre direction. Additionally, this work contribution is also related to the application of the Paris model (based on dL/dN vs ΔK) to generate the translaminar damage propagation prediction model. The most dominant damage mechanism was the splitting pattern, which changed the aspect of failure for each laminate architecture as a function of fibre orientation. The laminate with multidirectional fibre orientation exhibited higher resistance to translaminar crack propagation due to the growth of splitting and delamination in multiple directions. The fibre orientation changed the propagation path, which influenced the fracture toughness and crack propagation rate behaviour.