Search

A new fatigue life prediction method using the energy‐based approach under uniaxial and multiaxial random loadings is proposed. The uniqueness of the proposed model is based on a time‐derivative damage accumulation unlike classical cycle‐based damage accumulation models. Thus, damage under arbitrary random loading can be directly obtained using time‐domain integration without cycle counting. First, a brief review of existing models is given focusing on their applicability to uniaxial/multiaxial, constant/random, and high cycle fatigue/low cycle fatigue loading regimes. Next, formulation of time‐derivative damage model is discussed in detail under uniaxial random loadings. Then, an equivalent energy concept for general multiaxial loading conditions is used to convert the random multiaxial loading to an equivalent random uniaxial loading, where the time‐derivative damage model can be used. Finally, the proposed model is validated with extensive experimental data from open literature and in‐house testing under various constant and random spectrum loadings. [ABSTRACT FROM AUTHOR]

A probabilistic fatigue life prediction framework for concrete bridges is proposed in this study that considers the stress history from the construction stage to the operation stage. The proposed fatigue analysis framework combines the fatigue crack growth-based material life prediction model and a nonlinear structural analysis method. A reliability analysis is proposed using the developed probabilistic model to consider various uncertainties associated with the fatigue damage. A Bayesian network is established to predict the fatigue life of a concrete bridge according to the proposed framework. The proposed methodology is demonstrated using an experimental example for fatigue life prediction of a concrete box-girder. Comparison with experimental data of fatigue life shows a satisfactory accuracy using the proposed methodology, and the ratio of the posterior predicted mean (updating time n = 8) to the test value decreases to 33%–1% in the current investigation. [ABSTRACT FROM AUTHOR]

A critical plane-based mixed-mode delamination growth model for composite materials under fatigue loadings is proposed in this study. A brief review for mixed-mode delamination is given and the special focus in the study is on a critical plane-based fracture criterion since it can automatically adapt for different local failure modes. An equivalent energy release rate range suitable for fatigue analysis is proposed for the delamination growth rate prediction under general proportional and non-proportional multiaxial loadings. The proposed methodology is validated with extensive experimental data available in the open literature. A general good agreement is observed between model predictions and experimental observations. Finally, some discussion and conclusions are drawn based on the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, a real-time composite fatigue life prognosis framework is proposed. The proposed methodology combines Bayesian inference, piezoelectric sensor measurements, and a mechanical stiffness degradation model for in-situ fatigue life prediction. First, the composites stiffness degradation is introduced to account for the composites fatigue damage accumulation under cyclic loadings and a new growth rate-based stiffness degradation model is developed. Following this, the general Bayesian updating-based fatigue life prediction method is discussed. Several sources of uncertainties and the developed stiffness degradation model are included in the prognosis framework. Next, an in-situ composites fatigue testing with piezoelectric sensors is designed and performed to collected sensor signal and the global stiffness data. Signal processing techniques are implemented to extract damage diagnosis features. The detected stiffness degradation is integrated in the Bayesian inference framework for the remaining useful life (RUL) prediction. Prognosis performance on experimental data is validated using prognostics metric. Finally, some conclusions and future work are drawn based on the proposed study. [ABSTRACT FROM AUTHOR]

A general framework for probabilistic prognosis and uncertainty management under fatigue cyclic loading is proposed in this article. First, the general idea using the Bayesian updating in prognosis is introduced. Several sources of uncertainties are discussed and included in the Bayesian updating framework. An equivalent stress level model is discussed for the mechanism-based fatigue crack growth analysis, which serves as the deterministic model for the lap joint fatigue life prognosis. Next, an in situ lap joint fatigue test with pre-installed piezoelectric sensors is designed and performed to collect experimental data. Signal processing techniques are used to extract damage features for crack length estimation. Following this, the proposed methodology is demonstrated using the experimental data under both constant and variable amplitude loadings. Finally, detailed discussion on validation metrics of the proposed prognosis algorithm is given. Several conclusions and future work are drawn based on the proposed study. [ABSTRACT FROM PUBLISHER]

An integrated experimental and numerical investigation of fatigue damage diagnosis in composite plates is presented in this study. First, the fatigue testing setup for carbon–carbon composite coupons is described with corresponding health monitoring approach through Lamb wave–based diagnostic data collection. In order to study the effects of degradation evolution, a finite element model is used to simulate the effect on Lamb wave propagation due to fatigue-induced delamination and matrix cracking. Simulation results are compared with the experimental testing to first validate the model and then develop several features as potential damage indicators. A parametric study is conducted on the effects of varying degrees of delamination and matrix cracking on these features. Results from the model simulations are presented along with the data analysis and discussions on the capability and limitations of the approach. Finally, some conclusions are drawn and future work is proposed based on the results obtained so far. [ABSTRACT FROM PUBLISHER]

Abstract: A novel in situ scanning electron microscope (SEM) fatigue testing is proposed in this paper to investigate the fatigue crack growth mechanisms within one cyclic loading under plane stress conditions. The objectives of the experimental study are to verify the hypotheses of a small time scale fatigue crack growth model and to develop a new experimental methodology for the detailed mechanism investigation of fatigue crack growth. During the testing, one loading cycle is uniformly divided into a certain number of steps. At each step, high resolution images are taken around the crack tip region. Imaging analysis is used to quantify the crack growth kinetics and crack tip deformation behavior at any time instant in a loading cycle. Crack closure phenomenon is directly observed during the crack growth process in the current investigation. It is also observed that crack growth is not uniformly distributed within a loading cycle and only happens during a small portion of the loading path. Multiple mechanisms exist within one cyclic loading, which is not able to be captured using the classical cycle-based approaches. A detailed discussion is given based on the current investigation to explain some well-known issues in the classical fatigue theory. [Copyright &y& Elsevier]

A new methodology for concurrent dynamic analysis and structural fatigue prognosis is proposed in this paper. The proposed methodology is on the basis of a novel small time scale formulation of material fatigue crack growth that calculates the incremental crack growth at any arbitrary time within a loading cycle. It defines the fatigue crack kinetics on the basis of the geometric relationship between the crack tip opening displacement and the instantaneous crack growth rate. The proposed crack growth model can be expressed as a set of first-order differential equations. The structural dynamics analysis and fatigue crack growth model can be expressed as a coupled hierarchical state-space model. The dynamic response (structural level) and the fatigue crack growth (material level) can be solved simultaneously. Several numerical problems with single degree-of-freedom and multiple degree-of-freedom cases are used to show the proposed methodology. Model predictions are validated using coupon testing data from open literature. Following this, the methodology is demonstrated using a steel-girder bridge. The proposed methodology shows that the concurrent structural dynamics and material fatigue crack growth analysis can be achieved. The cycle-counting method in the conventional fatigue analysis can be avoided. Comparison with experimental data for structural steels and aluminum alloy shows a satisfactory accuracy using the proposed coupled state-space model. [ABSTRACT FROM AUTHOR]

Abstract: A general probabilistic life prediction methodology for accurate and efficient fatigue prognosis is proposed in this paper. The proposed methodology is based-on an inverse first-order reliability method (IFORM) to evaluate the fatigue life at an arbitrary reliability level. This formulation is different from the forward reliability problem, which aims to calculate the failure probability at a fixed time instant. The variables in the fatigue prognosis problem are separated into two categories, i.e., random variables and index variables. An efficient searching algorithm for fatigue life prediction is developed to find the corresponding index variable at a certain confidence level. Numerical examples using direct Monte Carlo simulation and the proposed IFORM method are compared for algorithm verification. Following this, various experimental data for metallic materials are used for model prediction validation. [Copyright &y& Elsevier]

A new methodology for concurrent dynamic analysis and structural fatigue prognosis is proposed in this paper. The proposed methodology is based on a novel small timescale formulation of material fatigue crack growth that calculates the incremental crack growth at any arbitrary time within a loading cycle. It defines the fatigue crack kinetics based on the geometric relationship between the crack-tip opening displacement and the instantaneous crack growth rate. The proposed crack growth model can be expressed as a set of first-order differential equations. The structural dynamics analysis and fatigue crack growth model can be expressed as a coupled hierarchical state-space model. The dynamic response (structural level) and the fatigue crack growth (material level) can be solved simultaneously. Several numerical problems with single-degree-of-freedom and multiple-degree-of-freedom cases are used to show the proposed methodology. Model predictions are validated by using coupon testing data from open literature. Following this, the methodology is demonstrated by using a steel girder bridge. The proposed methodology shows that concurrent structural dynamics and material fatigue crack growth analysis can be achieved. Cycle-counting method in the conventional fatigue analysis can be avoided. Comparison with experimental data for structural steels shows a satisfactory accuracy by using the proposed coupled state-space model. [ABSTRACT FROM AUTHOR]

Abstract: A new fatigue crack growth formulation at the small time scale is proposed in this paper. This method is fundamentally different from the classical reversal-based fatigue analysis and is based on the incremental crack growth at any time instant within a cycle. It can be used for fatigue analysis at various time and length scales and is very convenient for the fatigue analysis under random variable-amplitude loadings without cycle-counting. Stress ratio effect is intrinsically considered in the proposed fatigue model since the stress state is directly used instead of using the cyclic stress range. In the proposed methodology, the reverse plastic zone concept is adopted to determine the lower integration limit during the time integral for crack length calculation. Model validation is performed using extensive experimental observations for various metallic materials under both constant amplitude and variable-amplitude loadings. Statistical error analysis is used to compare the proposed model with existing fatigue crack growth codes. Generally, very good correlations are observed between model predictions and experimental observations. [Copyright &y& Elsevier]

Abstract: Corrosive environment causes corrosion pits at material surface and reduces the fatigue strength significantly. Fatigue crack usually initiates at and propagates from these locations. In this paper, a general methodology for fatigue life prediction for corroded specimens is proposed. The proposed methodology combines an asymptotic stress intensity factor solution and a power law corrosion pit growth function for fatigue life prediction of corroded specimens. First, a previously developed asymptotic interpolation method is proposed to calculate the stress intensity factor (SIF) for the crack at notch roots. Next, a growing semi-circular notch is assumed to exist on the specimen’s surface under corrosive environments. The notch growth rate is different under different corrosion conditions and is assumed to be a power function. Fatigue life can be predicted using the crack growth analysis assuming a crack propagating from the notch root. Plasticity correction is included into the proposed methodology for medium-to-low cycle fatigue analysis. The proposed methodology is validated using experimental fatigue life testing data of aluminum alloys and steels. Very good agreement is observed between experimental observations and model predictions. [Copyright &y& Elsevier]

Abstract: Mechanical components have stress risers, such as notchs, corners, welding toes and holes. These geometries cause stress concentrations in the component and reduce the fatigue strength and life of the structure. Fatigue crack usually initiates at and propagates from these locations. Traditional fatigue analysis of notched specimens is done using an empirical formula and a fitted fatigue notch factor, which is experimentally expensive and lacks physical meaning. A general methodology for fatigue limit prediction of notched specimens is proposed in this paper. First, an asymptotic interpolation method is proposed to estimate the stress intensity factor (SIF) for cracks at the notch root. Both edge notched and center notched components with finite dimension correction are included into the proposed method. The small crack correction is included in the proposed asymptotic solution using El Haddad’s fictitious crack length. Fatigue limit of the notched specimen is estimated using the proposed stress intensity factor solution when the realistic crack length is approaching zero. A wide range of experimental data are collected and used to validate the proposed methodology. The relationship between the proposed methodology and the traditionally used fatigue notch factor approach is discussed. [Copyright &y& Elsevier]

Abstract: A new methodology is proposed in this paper to calculate the equivalent initial flaw size (EIFS) distribution. The proposed methodology is based on the Kitagawa–Takahashi diagram. Unlike the commonly used back-extrapolation method for EIFS calculation, the proposed methodology is independent of applied load level and only uses fatigue limit and fatigue crack threshold stress intensity factor. The advantage of the proposed EIFS concept is that it is very efficient in calculating the statistics of EIFS. The developed EIFS methodology is combined with probabilistic crack growth analysis to predict the fatigue life of smooth specimens. Model predictions are compared with experimental observations for various metallic materials. [Copyright &y& Elsevier]

Abstract: A general methodology for fatigue reliability degradation of railroad wheels is proposed in this paper. Both fatigue crack initiation and crack propagation life are included in the proposed methodology using previously developed multiaxial fatigue models by the same authors. A response surface method in conjunction with design of experiments is used to develop a closed form approximation of the fatigue damage accumulation with respect to the input random variables. The total fatigue life of railroad wheels under stochastic loading is simulated, accounting for the spatial and temporal randomness of the fatigue damage. The field observations of railroad wheel fatigue failures are compared with the numerical predictions using the proposed methodology. [Copyright &y& Elsevier]

Abstract: A new multiaxial high-cycle fatigue initiation life prediction model for railroad wheels is proposed in this paper. A general fatigue damage analysis methodology for complex mechanical components is developed and applied to the wheel/rail rolling contact fatigue problem. A 3-D elasto-plastic finite element model is used for stress analysis. A submodeling technique is used to achieve both computational efficiency and accuracy. Then the fatigue damage in the wheel is evaluated numerically using the stress history during one revolution of the wheel rotation. The effects of wheel diameter, vertical loading, material hardness, and material fatigue properties on fatigue crack initiation life are investigated using the proposed model. [Copyright &y& Elsevier]

Alloy 617 is a primary candidate material to be used in the next generation of nuclear power plants. Structural materials for these plants are expected to undergo creep and fatigue at temperatures as high as 950 °C. This study uses a hybrid-control creep-fatigue loading profile, as opposed to the traditional strain-controlled loading, to generate creep dominated failure. Qualitative and quantitative image analysis through SEM, EDS, and EBSD, is used to show that hybrid control testing is capable of producing creep dominated failure and that time fraction approach is not a valid indicator of creep or fatigue dominated damage. The focus of image analysis is on surface fatigue cracks and internal creep voids. A creep-fatigue damage interaction diagram based on these micro-scale features is plotted. It is shown that the classical time fraction approach suggested by the ASME code does not agree with the experimental findings and has a poor correlation with observed microscale damage features. A new definition of creep damage fraction based on an effective hold time is found to correlate well with the micro-scale image analysis. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a method for fatigue damage propagation model selection, updating, and averaging using reversible jump Markov chain Monte Carlo simulations. Uncertainties from model choice, model parameter, and measurement are explicitly included using probabilistic modeling. Response measurement data are used to perform Bayesian updating to reduce the uncertainty of fatigue damage prognostics. All the variables of interest, including the Bayes factors for model selection, the posterior distributions of model parameters, and the averaged results of system responses are obtained by one reversible jump Markov chain Monte Carlo simulation. The overall procedure is demonstrated by a numerical example and a practical fatigue problem involving two fatigue crack growth models. Experimental data are used to validate the performance of the method. [Copyright &y& Elsevier]

Abstract: A general methodology is proposed in this paper for fatigue-life prediction using crack growth analysis. This is the part II of the paper and focuses on the fatigue-life prediction under proportional and nonproportional multiaxial loading. The proposed multiaxial fatigue-life prediction is based on a critical plane-based multiaxial fatigue damage model and the Equivalent Initial Flaw Size (EIFS) concept. An equivalent stress intensity factor under general multiaxial proportional and nonproportional loading is defined. The fatigue life is predicted by integration of the crack growth rate curve from the EIFS to the critical crack length. The proposed model can automatically adapt for different materials experiencing different local failure modes. The numerical fatigue-life prediction results calculated by the proposed approach are validated with experimental data for a wide range of metallic materials available in the literature. Reasonable agreements are observed between the model predictions and the experimental observations under proportional and nonproportional loading. [Copyright &y& Elsevier]

This study introduces an innovative methodology for predicting fatigue properties of additively manufactured Titanium alloy (Ti–6Al–4V) fabricated using laser powder bed fusion (LPBF). This study entails two key components: a classification model to identify sites likely to initiate cracks and a Probabilistic Physics-Guided Neural Network (PPgNN 2.0) to forecast fatigue life. The classification model capitalizes on parameters related to surface roughness and internal defects. This methodology minimizes false positives and negatives by leveraging computed tomography (CT) images for accurate surface topology and internal defects morphology. Data augmentation techniques were employed to address the challenge of imbalanced data distribution. PPgNN 2.0 represents an advancement over classical regression models due to its incorporation of physics-based constraints and probabilistic approaches, leading to highly accurate and physically consistent predictions. Training of the model involves multiple stress–fatigue life (S–N) curve datasets from literature and pertinent morphological data, while evaluation uses data extracted from in-house testing and imaging. The key strength of PPgNN 2.0 lies in its ability to offer flexible and robust fatigue life predictions, encompassing point estimates and uncertainties in the form of mean and standard deviation. A new loss function is proposed, which effectively captures the underlying distribution, contributing to minimizing prediction errors. • A methodology for extracting microstructural information from CT scan-built STLs. • Formulation of crack initiation site prediction as a classification problem. • Physics and data fusion using physics-guided neural network design. • Probabilistic fatigue life prediction using uncertainty-aware neural network. [ABSTRACT FROM AUTHOR]

To assess fatigue damage accumulation for civil infrastructure, Miner’s rule or linear elastic fracture mechanics (LEFM) are usually used in many codes and specifications. However, large uncertainties are found when the short cracks are initiated. Currently, most physics-based models for crack initiation are built for constant amplitude loads (CA). Since the environmental or service load-induced stresses at local details for crack initiation are time-variant, these physics-based models could not be directly applied for real civil infrastructure. In this paper, a two-fold nonlinear grain-based fatigue damage model is proposed to process the variable amplitude loads (VA) induced fatigue damages by combining Persistent Slip Band (PSB)-based short fatigue crack model and grain-based Miner’s rule. In the sub-grain regime, linear damage accumulation is adopted. For the repeated stress blocks with variable amplitude, the stress block is rain-flow counted and the damage accumulation is modeled as short crack extension. Therefore, the crack associated damage will be accumulated grain by grain until it reaches characteristic length of a long crack. The damage accumulation from a stress block is added for each grain. Effect from subcritical loads is also considered in this damage accumulative model. Finally, a numerical demonstration is performed on statistical representative elements under variable stress histories from a long span bridge. [ABSTRACT FROM AUTHOR]

Abstract: A new subcycle-based delamination growth model is proposed. The key idea is to model delamination growth at any time instant within a cyclic loading, rather than the cycle-averaged growth kinetics. First, some existing models are briefly reviewed for the fatigue delamination growth analysis of composite materials. Following this, two hypotheses are given for the derivation of the subcycle delamination growth model: (1) delamination growth does not happen during the unloading path and (2) delamination growth does not happen when the applied loading is below a reference level during the loading path. Mathematical expression is given for the calculation of delamination growth rate. Next, the extension of the proposed model is discussed to use both stress intensity factor and energy release rate as the driving force parameters, which are widely used in the open literature. Finally, the model predictions are compared with extensive experimental data under different stress ratios for model validation. One of the advantages of the proposed model is that the stress ratio dependent delamination growth can be predicted. Some conclusions and future work are drawn based on the proposed method. [Copyright &y& Elsevier]

Abstract: A general probabilistic inference procedure is proposed in this paper based on the Maximum relative Entropy (MrE) approach which generalizes both Bayesian and Maximum Entropy (MaxEnt) inference methodologies. The construction of the conditional probability (likelihood function) for general model-based inference problems is discussed in detail to systematically manage uncertainties from mechanism modeling, model parameters, and measurements. Analytical and numerical examples are used to investigate the sequence effect in the probabilistic inference using point observations and moment constraints. The developed methodology is applied to the engineering fatigue crack growth problem with experimental data for demonstration and validation. Following this, a detailed comparison between the classical Bayesian inference and the MrE inference is given. [Copyright &y& Elsevier]

• A new framework for probabilistic fatigue life prediction under random loadings. • PSRC is proposed to transform random loading in a piecewise and randomized manner. • Mean stress corrected random fatigue limit model is proposed. • Both loading and material uncertainties are considered. • Influence of step size and block sequence randomization in PSRC is discussed. A new framework is proposed for probabilistic fatigue life prediction considering randomness from both loadings and material properties. Piecewise stochastic rainflow counting (PSRC) is proposed to transform random loading spectrums to block loadings in a piecewise way with block randomization. The PSRC can be integrated with both linear and nonlinear damage accumulation rules. Mean stress corrected random fatigue limit model is proposed for uncertainty quantification of material fatigue properties under constant amplitude loadings. Probabilistic fatigue life prediction with both loading and material uncertainties is conducted using Monte Carlo simulation and is validated with experimental data from literature and in-house testing. Impact of different mean stress correction models on the fatigue life prediction under random loadings is investigated in detail. The influence of block piece length and block sequence randomization is discussed with respect to the mean and scatter behavior of the probabilistic life prediction results. [ABSTRACT FROM AUTHOR]

• Uncertainty quantification for fatigue S - N curves with sparse data is studied. • A novel Hierarchical Bayesian data augmentation (HBDA) method is proposed. • HBDA shows significant performance gain, especially with small sample size. • HBDA is applied to fatigue quantification of the Pearl Harbor Memorial Bridge. A novel statistical uncertainty quantification (UQ) method for fatigue S- N curves with sparse data is proposed in this paper. Sparse data observation is very common in fatigue testing due to various reasons, such as time and budget constraints, availability of testing materials and resources. A brief review of existing UQ methods for fatigue properties with sparse data is given. Following this, a new method, called Hierarchical Bayesian data augmentation (HBDA) is proposed to integrate the hierarchical Bayesian modeling (HBM) and Bayesian data augmentation (BDA) to deal with sparse data problem specifically for fatigue S - N curves. The key idea is to use: (1) HBM for analyzing the variability of S-N curves both within one stress level and across stress levels; (2) BDA to build up a large-size sample of fatigue life data based on the observed sparse samples. Four strategies to estimate the probabilistic S-N curves with sparse data are proposed: (1) hierarchical Bayesian modeling (HBM) only, (2) Bayesian data augmentation (BDA) only, (3) posterior information from HBM used as prior information for BDA (HBM + BDA), and (4) augmented data from BDA used by HBM (BDA + HBM). The strategy (3) and (4) are named HBDA hereafter. Next, the four strategies are validated and compared using aluminum alloy data and laminate panel data from open literature. Convergence study and confidence estimation is performed, and it is shown that the HBDA methods (i.e., HBM + BDA or BDA + HBM) have better performance compared with the classical method and HBM/BDA alone. The performance gain is especially significant when the number of available data samples is small. Finally, the proposed methodology is applied to a practical engineering problem for fatigue property quantification of the demolished Pearl Harbor Memorial Bridge, where only limited samples are available for testing. Conclusions and future work are drawn based on the proposed study. [ABSTRACT FROM AUTHOR]

• A stress-based fatigue model under arbitrary random multiaxial loading is proposed in this paper. • The proposed model is based on the Liu-Mahadeven critical plane concept. • An equivalent stress transformation reduces a random loading to a simple constant loading. • The model is validated successfully for Al-7076-T6 under different loading conditions. A multiaxial fatigue life prediction model under general multiaxial random loadings is proposed in this paper. First, a brief review for existing multiaxial fatigue models is given with a special focus is on the Liu- Mahadevan critical plane concept, which can be applied to both brittle and ductile materials. Next, the new model development based on the Liu-Mahadevan critical plane concept for random loading is presented. The key concept is to use two-steps to identify the critical plane: identify the maximum damage plane due to normal stress and calculate the critical plane orientation with respect to the maximum damage plane due to normal stress. Multiaxial rain-flow cycle counting method with mean stress correction is used to estimate the damage on the critical plane. Equivalent stress transformation is proposed to convert the multiaxial random load spectrum to an equivalent constant amplitude spectrum. The equivalent stress is then used for fatigue life predictions. The proposed model is validated with both literature and in-house testing data generated using an Al 7075-T6 alloy under various random uniaxial and multiaxial spectrums. Comparison between experimental and predicted fatigue life lives shows good agreements; thus, demonstrating efficacy of the proposed model. Finally, concluding remarks and future work based on the results obtained are discussed. [ABSTRACT FROM AUTHOR]