Fatigue Reliability Assessment Research Articles

CCZM‐based fatigue analysis and reliability assessment for wind turbine blade adhesive joints considering parameter uncertainties

AbstractWind turbine blades are complex structures composed of multiple bonded components. The fatigue performance of these adhesive joints is crucial for ensuring operational safety over the blade's lifespan. Traditional structural fatigue analysis methods are inadequate for evaluating the fatigue properties of these joints due to the unique characteristics of adhesive materials. Variations in material and dimensional parameters, as well as fluctuating operational loads, further complicate the fatigue analysis of adhesive joints in wind turbine blades. To tackle this issue, this study introduces a fatigue analysis and reliability assessment method for the adhesive joints of wind turbine blades, employing the Cyclic Cohesive Zone Model (CCZM) and accounting for parameter uncertainties. Specifically, a novel methodology for fatigue analysis based on the CCZM is presented. The methodology is programmatically implemented to obtain a fatigue life dataset through multiple simulations, considering uncertainties in material parameters, adhesive dimensions, and loads. Subsequently, a fatigue reliability model is formulated to evaluate the fatigue reliability of adhesive joints in wind turbine blades under different parameter conditions, and the sensitivity of fatigue reliability to each parameter is investigated. The findings offer valuable insights for improving the safety and reliability of adhesive structures in wind turbine blades.

An approach to estimate the low cycle fatigue probabilistic curves of PBF-LB/M 316L steel from small size datasets using the remora optimization algorithm

The significant dispersion in fatigue properties is a prevalent attribute observed in metals manufactured by the Additive Manufacturing (AM). To ascertain the safety of components subjected to low cycle fatigue (LCF) loadings at a temperature of 550 °C, it is necessary to carry out a fatigue reliability assessment of AM metals. Nevertheless, the number of LCF life tests is limited owing to time-consuming nature of test and high total production cost of AM materials. Such a small size dataset cannot satisfy the criteria of the traditional reliability assessment method. This work aims to develop a novel method to evaluate the LCF reliability of 316L stainless steel manufactured by laser-based powder bed fusion of metals (PBF-LB/M) technology. Firstly, the Weibull model is coupled with the Coffin-Manson-Basquin relationship in order to characterize the dispersion of life data points at various strain levels. Secondly, reliability results from a small size dataset show a maximum relative error in fatigue life of less than 25 %, which is similar to results from a large size dataset and the traditional method using fatigue data from public sources. Among this step, the remora optimization algorithm is firstly applied to calculate the characteristic parameters of newly-proposed method. Thirdly, the LCF reliability of PBF-LB/M 316L based on the small size dataset is evaluated. The N95% is equivalent to 44 % of N50%. Finally, the PBF-LB/M 316L is compared with traditional 316L considering the reliability. The LCF properties of PBF-LB/M 316L is similar to the traditional 316L at 50 % reliability, however it’s slightly worse at 95 % reliability.

Reliability analysis of fatigue crack growth in shallow shell structures using the Dual Boundary Element Method

This work presents a novel methodology for fatigue life reliability analysis using a newly developed Dual Boundary Element Method-based Implicit Differentiation Method (DBEM-IDM) in shallow shell structures. The proposed DBEM formulations evaluate stress intensity factors and fatigue life sensitivities in shallow shells considering geometrical variables and curvature. The IDM formulations, obtained through direct differentiation of the shallow shell DBEM formulations, uses the First-Order Reliability Method (FORM) to assess the reliability index and probability of failure of shallow shell structures with multiple cracks. Two numerical examples were simulated to illustrate the effectiveness of the proposed methodology. The first example examines a shallow shell with a centre hole and cracks subjected to various loads. The critical crack length required to ensure structural reliability and inspectability is determined. Fatigue reliability assessment is performed for the same example, employing limit state functions expressed in terms of fatigue life. FORM results are compared with the results of Monte Carlo Simulations (MCS), and provided a maximum difference of 3.67%. Parametric analyses are conducted to identify significant variables that affect reliability, and it was found that precise determination of design parameters is necessary to reduce the probability of failure, particularly for the Paris law constants. The second example, featuring more complex geometry, involved assessing fatigue reliability in a cylindrical shallow shell structure with multiple cracks. The results of this example indicate a 3.49% maximum difference between FORM and MCS. The results exhibit a low error compared to the MCS, and the inherent efficiency of the IDM-based FORM underscores its suitability for addressing uncertainty in reliability analysis.

Fatigue Reliability Assessment for Orthotropic Steel Decks: Considering Multicrack Coupling Effects

Multiple fatigue cracks are generally present in practical engineering due to the existence of welding; the size and number of cracks of orthotropic steel bridge decks are greatly uncertain. The component failure conditions caused by these cracks may have correlations. Currently, it is still a challenging issue to develop a physical model of multiple fatigue crack propagation in bridge decks and perform a fatigue reliability assessment, which is also the motivation that drives the innovation of this study. A fatigue reliability evaluation method is presented for orthotropic steel bridge decks, considering the coupling effect of multiple cracks and the randomness of vehicle loading. A numerical simulation method for multifatigue crack growth is developed by combining the ABAQUS and FRANC3D programs. The equivalent crack depth under different spacing and depths of collinear cracks is calculated by using numerical simulation and the multicrack equivalent characterization method. The critical damage accumulation function of multiple fatigue cracks is established using linear elastic fracture mechanics. Subsequently, the critical damage accumulation function of multiple fatigue cracks is established based on linear elastic fracture mechanics. In order to solve the time-consuming problem of traditional Monte Carlo method, the iHL-RF method and AK-MCS method are developed for fatigue reliability analysis. The results show that compared with the single-crack model, the fatigue reliability of orthotropic steel deck will be crucially reduced considering the coupling effect of double cracks. The MCS, iHL-RF and AK-MCS methods can effectively solve the fatigue reliability analysis problem. Compared with the MCS method, the reliability calculation time based on AK-MCS method is significantly reduced. The AK-MCS method-based method reduces the time for calculating the reliability of orthotropic steel decks by 50% compared with the iHL-RF method. The reliability analysis of orthotropic steel deck bridge based on AK-MCS method is proved to be efficient and accurate.

Experimentally calibrated finite element fatigue reliability assessment of an offshore platform in the Persian Gulf

Experimentally calibrated finite element fatigue reliability assessment of an offshore platform in the Persian Gulf

Data-physics-model based fatigue reliability assessment methodology for high-temperature components and its application in steam turbine rotor

Data-physics-model based fatigue reliability assessment methodology for high-temperature components and its application in steam turbine rotor

Fatigue reliability assessment of load‐carrying cruciform welded joints with undercuts and misalignments

AbstractThe additional local stress concentration caused by undercut and misaligned defects could lead to lower fatigue strength of welded joints. The paper aims to investigate the effects of undercuts and misalignments on fatigue performance and reliability of Load‐carrying Cruciform Welded Joint (LCWJ) quantitatively by probabilistic statistics theory and fracture mechanics theory. Firstly, the geometrical characteristics of undercut and misalignment are summarized from the literature and our experiments. Subsequently, the probabilistic distributions of material fracture properties, the configurations of geometries, and flaws were evaluated under specific loading conditions. The fatigue strengths are further estimated by the probabilistic reliability theory by combining the actual fatigue data. The results demonstrate a clear disparity of fatigue crack growth threshold and resistances for the tested data of base metal and weldment. The level of defects determines the interval of fatigue life, and the larger the dispersion accompanying earlier fatigue failure occurs.

Fatigue Reliability Assessment of RC Beams in Heavy-Haul Railways Based on Point Estimate Method.

Heavy-haul railways have a high passing frequency of trains with a large axle weight, causing rapid accumulation of fatigue damage in reinforced concrete (RC) bridge structures, which significantly affects the safety of the bridges. To study the fatigue reliability of RC beams in heavy-haul railways, the fatigue performance function for RC beams in heavy-haul railways was established, and the fatigue reliability assessment method for bridge structures in heavy-haul railways based on the point estimate method (PEM) was developed. An 8 meter-span plate beam in an existing heavy-haul railway illustrates the method. The train axle weight and dynamic coefficient were considered random variables, and the first four moments of equivalent stress ranges were obtained. The traffic quantity of the heavy-haul railways was investigated, and the fatigue reliability was evaluated using the proposed method. In addition, the effects of annual freight volume and train axle weight on fatigue reliability were discussed. Results indicate that PEM can effectively and accurately evaluate the fatigue reliability of RC beams in heavy-haul railways. In the first 20 years of operation, the fatigue failure probability was less than the limit value specified in the standard. The increase in annual traffic volume and train axle weight will cause a significant increase in fatigue failure probability. The research results of this paper are expected to provide an important basis for the design and maintenance of reinforced concrete bridges for heavy-haul railways in the future.

A framework of cable wire failure mode deduction based on Bayesian network

Because of the cable structure comprises many parallel steel wires, the service performance of the cable structure is determined by the performance change of the parallel steel wires. The parallel steel wire will be subjected to cyclic load during the service period, which will reduce its fatigue life and even lead to the parallel steel wire broken. In addition, the corrosion pits may appear on the cable steel wire in corrosion environments, which will affect the fatigue life of parallel steel wires. In other words, the cable steel wire may be corroded and broken during its service life, which will decrease in the reliability of the cable system. In this paper, a component level to system-level fatigue reliability assessment model is proposed with considering parallel steel wire broken, corroded, and broken-corroded coupling based on the Bayesian network. Specially, the S-N curve considering the broken parallel steel wire is established based on the traditional S-N curve. In addition, the S-N curve for parallel steel wire corrosion is established with the influence of the corrosive environment in mind. Furthermore, the service state of each parallel steel wire, i.e., the failure probability of each parallel steel wire, can be calculated by using a Bayesian network. Finally, the five numerical simulation studies are used to validate the proposed model’s effectiveness and the effects of the number of broken parallel steel wires and the number of corrosion parallel steel wires on the fatigue reliability of cable systems is investigated.

On the fatigue behaviour and reliability assessment of high strength welded details

This research focusses on the fatigue behaviour of welded components made of high strength duplex (EN 1.4162) and carbon steel. It starts by investigating the base material alongside welded cruciform joints submitted to cyclic loading through experiments and finite element models. The obtained results are then compared with existing research on high strength (carbon and stainless) steel equivalents. This collated database of >500 reference test results is then used to assess the applicability of the current Eurocode and IIW provisions to predict the fatigue life of higher strength steels and to propose new rules that include the benefit of their higher material strength. Proposals are made to upgrade certain fatigue classes (e.g., transverse stiffeners and butt welds) when high strength steel grades are employed. The reliability of these proposals is then supported by the use Weibull models, commonly used in survival analysis.

Research on fatigue reliability assessment of engine cylinder head based on neural network

Fatigue reliability (FR) evaluation is crucial for extending the service life and improving the reliability of automotive engines. This study proposed a general framework for assessing high cycle FR based on the back propagation neural network (BPNN). Using a diesel engine cylinder head (CH) as an example, the stochastic finite element analysis was implemented by considering the uncertainties of materials and loads. Subsequently, the stochastic finite element calculation process was replaced with the BPNN model to expedite fatigue life prediction. Ultimately, the reliability assessment of the CH was conducted, taking into account the influence of the load sequence. The research findings indicated that the reliable life t0.95 of the CH considering the load sequence was approximately 75 h, representing a 7.1% increase compared to the linear cumulative damage. During the service life of the CH, the failure probability sensitivity factor for the gas force load exceeded 0.9, offering an important reference for optimizing FR.

A probabilistic fatigue life prediction method under random combined high and low cycle fatigue load history

In this paper, a probabilistic high and low cycle fatigue (H-LCF) life prediction framework is proposed to consider random load history into fatigue life prediction of structures. First, the random load history is generated and quantified by finite element analysis (FEA) and Monte Carlo simulation (MCS). Subsequently, based on the quantification approach and an improved H-LCF damage curve, the framework of probabilistic H-LCF life prediction is then established. A turbine shaft is analyzed by the proposed method, which confirms the superior accuracy of the proposed method than the existing ones. Overall, the proposed method provides an effective way for structures’ fatigue life and reliability assessment.

Fatigue reliability assessment of offshore catenary risers conveying internal slug flow

AbstractThis paper proposes a fatigue reliability assessment method of offshore steel catenary risers (SCRs) caused by internal slug flow. Offshore risers subject to slug flow are modeled first by employing a finite element method scheme. Subsequently, a combination of Kriging metamodel and Monte Carlo simulation (MCS) is established to assess the fatigue reliability of SCRs conveying internal slug flow. An explanatory example of a 16‐inch SCR is presented to validate the performance of the proposed method and the results indicate that the failure rates of the SCR are significantly affected by the frequency of slug flow. Moreover, the accuracy and feasibility of the present method are validated by a comprehensive comparison with the existing experiments and numerical results. The present method contributes to the design and maintenance of offshore risers with internal slug flow.

Fatigue reliability assessment method for wind power gear system based on multidimensional finite element method

As a core strategic technology industry, the wind power plays an important role in protecting national energy reserves. The large gear component is one of the core foundation parts in wind turbines, and its quality indexes greatly affect the service performance of the wind turbine drive chain and even the wind turbine as a whole. This paper calculates the fatigue load history of the wind power large gear system under the coupling mechanism of elastic behavior based on a multidimensional finite element method, and obtains the probabilistic fatigue strength of gear teeth through the gear low circumference fatigue test and life distribution transformation method, and deeply explores the inherent characteristics of the wind power gear system in functional implementation and then establishes a system fatigue reliability evaluation model. Finally, a mapping path from the global structural elements of the wind power gearbox to the reliability indexes of the gear system is constructed with significant simulation and test cost advantages. It can provide structural optimization guidance in the development and design of large wind power gear systems, and significantly reduce the cost of achieving reliability indexes in the design iterations of such large high-end equipment. At the same time, it can provide cost-effective training data for intelligent optimization algorithms such as the deep reinforcement learning, which will eventually achieve multi-objective optimal stiffness matching for wind power gearboxes under reliability index constraints.

Improved Fatigue Reliability Analysis of Deepwater Risers Based on RSM and DBN

The fatigue reliability assessment of deepwater risers plays an important role in the safety of oil and gas development. Physical-based models are widely used in riser fatigue reliability analyses. However, these models present some disadvantages in riser fatigue reliability analyses, such as low computational efficiency and the inability to introduce inspection data. An improved fatigue reliability analysis method was proposed to conduct the fatigue reliability assessment of deepwater risers. The data-driven models were established based on response surface methods to replace the original physical-based models. They are more efficient than the physics-based model, because a large number of complex numerical and iterative solutions are avoided in fatigue reliability analysis. The annual crack growth model of the riser based on fracture mechanics was established by considering the crack inspection data as a factor, and the crack growth dynamic Bayesian network was established to evaluate and update the fatigue reliability of the riser. The performance of the proposed method was demonstrated by applying the method to a case. Results showed that the data-driven models could be used to analyze riser fatigue accurately, and the crack growth model could be performed to analyze riser fatigue reliability efficiently. The crack inspection results update the random parameters distribution and the fatigue reliability of deepwater risers by Bayesian inference. The accuracy and efficiency of fatigue analysis of deepwater risers can be improved using the proposed method.

Reliability-based fatigue life assessment using random road load condition and local damage criteria

This study presents a fatigue reliability assessment of a vehicle coil spring based on random road load conditions for fatigue life characterisation. Fatigue life data characterisation was carried out to accelerate the durability analysis by retaining the higher amplitude cycles in the original strain signals and thus indicate the fatigue damage. To collect experimental data, road testing was conducted using various road profiles, which contributed significantly to the fatigue failure performance of the vehicle coil spring. Fatigue reliability analysis was performed to assess the failure behaviour of the coil spring utilising the probabilistic Gumbel distribution model to forecast the probability distribution of the fatigue life data. Furthermore, the highest and lowest mean-cycles-to-failure (McTF) of 5.44 × 107 and 2.46 × 105 blocks were estimated for the Coffin-Manson and Smith-Watson-Topper models from the highway and rural road profiles. The findings demonstrate that the lowest hazard rate corresponded to the highest McTF, making this an acceptable model to be implemented in reliability assessments of road profiles. Hence, the fatigue reliability assessment provided a hazard rate based on the fatigue life predictions for risk assessments when characterising the fatigue life data.

A fatigue reliability assessment approach for wind turbine blades based on continuous time Bayesian network and FEA

AbstractWind turbine blades made by composite materials (CWTBs), encounter fatigue failures, such as cracks, fractures, delamination, etc. Finite Element Analysis (FEA) is applied for fatigue performance simulations of CWTBs as the full‐scale testing is costly. To consider correlated failures and uncertainties in load and material parameters, this paper proposes a fatigue reliability assessment method based on continuous time Bayesian network and FEA. Specifically, the dangerous regions of each component of CWTBs are determined by finite element fatigue simulation. The failure probability distributions of components are then computed by quantifying the uncertainties of several factors including the load and material parameters. A continuous time Bayesian network model is constructed for the fatigue reliability of CWTBs. The performance of the proposed method is verified by a comprehensive analysis with the results of discrete time Bayesian networks.

Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions

The aim of this paper is to characterise the fatigue reliability for various random strain loads under extreme value distribution while considering the cycle sequence effect condition in fatigue life prediction. The established strain-life models, i.e., Morrow and Smith-Watson-Topper, considered a mean stress effect and strain amplitude; nevertheless, it excluded the load sequence effect, which involves the fatigue crack closure that is subjected to overload or underload. A FESEM-EDX analysis is conducted to characterise the failure features that occurred on the leaf spring. A finite element is simulated to determine the critical region in order to obtain the strain load behaviour. In addition, the strain signal is captured experimentally at 500 Hz for 100 s under operating conditions for three different road loads based on the critical location obtained from the finite element analysis. The fatigue life correlation shows that the Pearson correlation coefficients are greater than 0.9, which indicates the effective strain damage model is linearly correlated with the strain-life models. The fatigue life data are modelled using extreme value distribution by considering the random strain loads as extreme data. The reliability rate for the fatigue life is reported to be more than 0.59 within the hazard rate range of 9.6 × 10-8 to 1.2 × 10-7 based on the mean cycle to the failure point. Hence, the effective strain damage model is proposed for a fatigue reliability assessment under extreme conditions with higher reliability and provides fatigue life prediction when subjected to cycle sequence effects.

A fatigue reliability assessment model for welded structures based on the structural stress method

Since many factors affect the fatigue life of welded structures and the relationships between them are complex, finding effective ways to improve the fatigue reliability of welded structures has always been a challenge for the industry. A fatigue reliability assessment model and design method for welded structures based on the structural stress method is proposed. According to the limit state equation of the model, the design-life fatigue reliability and the service fatigue reliability assessment approaches are presented. Then, a first-order second-moment method is employed to reveal quantitative fatigue reliability for welded joints and structures. The relationships between the fatigue reliability and the influence variables are used to analyze and improve the welded structure design. Fatigue reliability of T-joint examples was assessed by accounting for weld leg sizes, plate thicknesses, penetration depths, and single-sided and double-sided forms. Furthermore, the assessment model was verified with a welded bogie frame. The fatigue reliability of the frame was improved based on the evaluation results. The model and method can be applied to other types of welded joints and welded structures.

Fatigue life and fatigue reliability assessment for long-span spatial structure based on long-term health monitoring data

Based on the structural health monitoring system of long-span cantilevered spatial structure in Taiyuan Botanical Garden, the welded details strain of the main truss welded tubular joints is monitored for a long time, and the massive monitoring data processing method and the structural fatigue performance evaluation method are studied. First, the key component of the structure is determined through using the measured data, to propose the empirical mode decomposition (EMD) method to compress the load time history, and the rain-flow counting method to extract the stress cycle to obtain the standard daily stress spectrum. Next, through the Palmgren-Miner linear cumulative damage criterion and the S-N curve, the fatigue damage analysis and fatigue life estimation method are established. Consequently, the Monte-Carlo method is used to analyze the fatigue reliability of the key component, on which basis, the influence of considering the load growth effect on the fatigue life and fatigue reliability index is analyzed. The study shows that the weld fatigue damage is mainly caused by the small number of medium amplitude strain cycles. When the load growth effect is considered, the fatigue damage development rate of the weld is significantly accelerated, resulting in a significant decrease in the fatigue life and fatigue reliability index of the weld.