Fatigue Database Research Articles

Construction of Fatigue Criteria Through Positive‐Unlabeled Learning

AbstractThe reliability of vehicles is a significant issue for automotive manufacturers, with mechanical fatigue representing a pivotal aspect of the design process. To accelerate the development of novel mechanical components, automotive manufacturers are increasingly employing numerical simulations with the objective of markedly reducing the number of prototype validation tests. This requires the utilization of efficient fatigue criteria capable of accurately identifying critical zones in numerical models. However, the current fatigue criteria frequently fail to demonstrate a satisfactory correlation with the results obtained from fatigue test rigs. In response, this paper proposes a probabilistic Dang Van criterion that accounts for variability in fatigue results within a multiaxial context. Additionally, a fatigue database comprising numerical results and test reports on automotive chassis components is introduced. A novel approach utilizing positive‐unlabeled learning is developed to enhance the predictive accuracy of the fatigue criterion. Its effectiveness is demonstrated through application to the fatigue database.

Cyclic creep strain rate criterion for short-fibre reinforced thermoplastics: Validation of creep and fatigue performance across a wide range of load ratios

The fatigue and creep responses of short-fibre reinforced thermoplastic matrix composites are influenced by numerous parameters such as load ratio for fatigue. Fatigue criteria, based solely on the evolution of the cyclic creep of the mean strain, are effective for load ratios greater than zero (tension/tension) but have limitations for negative load ratios (tension/compression).The aim of this study was to propose a unified creep and fatigue criterion, based on the evolution of the cyclic creep of the maximum strain, that allowed both load ratio domains to be covered. To investigate a wide range of load ratios (-1 to 0.8), an existing creep and fatigue database was augmented with purely alternated tension/compression tests. This database, which included 489 tests, considered the variations in parameters that influence the creep and fatigue responses, such as fibre orientation, water content and specifically for fatigue load ratio and frequency. This was used to validate a unified criterion based on the cyclic creep of the maximum strain. This criterion improved fatigue life prediction compared to existing criteria and allowed fatigue and creep results to be unified with 87% of estimated lifetimes within a scatter band of factor two.

A re-assessment of Ti-685 as a dwell sensitive titanium alloy and a definition for engineering relevant dwell behaviour

It is believed that the near-α titanium alloy Ti-685 was the first to demonstrate dwell sensitive fatigue behaviour whilst under engineering service as a gas turbine fan disc material. New fatigue data, micro-textural characterisation and fractography from a recent study which utilised remnant Ti-685 specimens originally manufactured for previous laboratory campaigns based at Swansea dating back to the late 1980s are now reported. In isolation, the present results failed to demonstrate a significant dwell effect in either aligned or basketweave microstructural variants. On this occasion, the limited sensitivity to dwell loading was explained by the combination of heat treatment artifacts and selection of a relatively small test specimen geometry. However, the present data were also reviewed in the context of the wider fatigue database generated by multiple studies over the past fifty years. In combination, stress-life (SN) curves defined the magnitude in applied peak stress necessary to demonstrate a dwell effect in this alloy. Ultimately, this facilitated a fundamental definition of dwell sensitivity that is relevant to the engineering community.

Numerical Simulation of Fatigue Behavior of Four Ti2AlNb Alloy Structural Parts

Abstract In aerospace engineering, many titanium alloy structures are subjected to fatigue loads and thus fail. Based on the Seeger fatigue life theory and the improved Lemaitre damage evolution theory, the fatigue behavior of four Ti2AlNb alloys is investigated. First, finite element models of four structural parts are established by ABAQUS software. Meanwhile, the fatigue life of four Ti2AlNb alloys is predicted by referring to the damage model parameters determined by previous work. Under the same initial conditions, the average errors of the predicted fatigue lives of the four structural parts are 20.1, 19.8, 20.9, and 19.5 %, respectively. The effects of load amplitude, temperature, and structural characteristics on the fatigue properties of Ti2AlNb alloy structural parts are studied. The stability of the two fatigue life simulation methods is analyzed. By comparing fatigue data of Ti2AlNb structural parts from various literature, the rationality of the simulated data is confirmed. Finally, the application of the Ti2AlNb structural fatigue database to machine learning is illustrated. These results provide a numerical simulation method for evaluating the fatigue life of various Ti2AlNb alloy aviation structural parts.

Fatigue database of complex metallic alloys

The past few decades have witnessed rapid progresses in the research and development of complex metallic alloys such as metallic glasses and multi-principal element alloys, which offer new solutions to tackle engineering problems of materials such as the strength-toughness conflict and deployment in harsh environments and/or for long-term service. A fatigue database (FatigueData-CMA2022) is compiled from the literature by the end of 2022. Data for both metallic glasses and multi-principal element alloys are included and analyzed for their statistics and patterns. Automatic extraction and manual examination are combined in the workflow to improve the efficiency of processing, the quality of published data, and the reusability. The database contains 272 fatigue datasets of S-N (the stress-life relation), ε-N (the strain-life relation), and da/dN-ΔK (the relation between the fatigue crack growth rate and the stress intensity factor range) data, together with the information of materials, processing and testing conditions, and mechanical properties. The database and scripts are released in open repositories, which are designed in formats that can be continuously expanded and updated.

Fatigue database of additively manufactured alloys

Fatigue is a process of mechanical degradation that is usually assessed based on empirical rules and experimental data obtained from standardized tests. Fatigue data of engineering materials are commonly reported in S-N (the stress-life relation), ε-N (the strain-life relation), and da/dN-ΔK (the relation between the fatigue crack growth rate and the stress intensity factor range) data. Fatigue and static mechanical properties of additively manufactured (AM) alloys, as well as the types of materials, parameters of AM, processing, and testing are collected from thousands of scientific articles till the end of 2022 using natural language processing, machine learning, and computer vision techniques. The results show that the performance of AM alloys could reach that of conventional alloys although data dispersion and system deviation are present. The database (FatigueData-AM2022) is formatted in compact structures, hosted in an open repository, and analyzed to show their patterns and statistics. The quality of data collected from the literature is measured by defining rating scores for datasets reported in individual studies and through the fill rates of data entries across all the datasets. The database also serves as a high-quality training set for data processing using machine learning models. The procedures of data extraction and analysis are outlined and the tools are publicly released. A unified language of fatigue data is suggested to regulate data reporting for the fatigue performance of materials to facilitate data sharing and the development of open science.

On material-agnostic fatigue life prediction using Buckingham Pi Theorem

A robust, quantitative analysis is needed to prevent frequent, catastrophic failure of components in powerplants and aircraft, to cite but two examples, due to cyclic loading that could lead to fatigue failure. The model presented in this research will be useful in the reliable design and safe operation of components and equipment. A fatigue life (the dependent variable) prediction model, which employs both stress-based, and stress–strain based criteria is presented that uses the Buckingham Pi Theorem with the experimental parameters influencing fatigue behaviour taken as the independent variables. The validation of the model is done using reliable, frequently used uniaxial fatigue data, culled from the NIMS (National Institute for Materials Science, Tsukuba, Japan) fatigue database on important industrial alloys that experience fatigue loading in service. (No reliable data on such a scale were available to test the validity of this model under multi-axial fatigue loading conditions.) It is demonstrated that the model predicts the experimental results accurately. The accuracy of prediction is examined for every case and compared with that of some other existing methods. Moreover, the potential applicability of this analysis in areas not yet validated is examined.

Fatigue dataset of high-entropy alloys

Fatigue failure of metallic structures is of great concern to industrial applications. A material will not be practically useful if it is prone to fatigue failures. To take the advantage of lately emerged high-entropy alloys (HEAs) for designing novel fatigue-resistant alloys, we compiled a fatigue database of HEAs from the literature reported until the beginning of 2022. The database is subdivided into three categories, i.e., low-cycle fatigue (LCF), high-cycle fatigue (HCF), and fatigue crack growth rate (FCGR), which contain 15, 23, and 28 distinct data records, respectively. Each data record in any of three categories is characteristic of a summary, which is comprised of alloy compositions, key fatigue properties, and additional information influential to, or interrelated with, fatigue (e.g., material processing history, phase constitution, grain size, uniaxial tensile properties, and fatigue testing conditions), and an individual dataset, which makes up the original fatigue testing curve. Some representative individual datasets in each category are graphically visualized. The dataset is hosted in an open data repository, Materials Cloud.

On the impact of undercuts and lack of penetration of cruciform joints from fatigue tests

The assumption of the detail categories in EN1993-1-9 is the presence of a certain weld quality level. In order to find out the sensitivity of the resulting fatigue strength for cases where a worse or better quality level compared to the selected level of EN ISO 5817 is achieved, in this paper, special fatigue experiments are presented. The experiments refer to the load-carrying cruciform joint with lack of penetration and root fusion as well as undercuts. The performed fatigue investigations on cruciform joints are based on and accompanied by further fatigue test results of literature, documented in a detailed fatigue database containing 147 test series. Detailed information on mechanical properties, fabrication and metallurgical characteristics of the cruciform specimens are given. Extensive 3D laser scans of the specimens and ultrasonic testing as well as magnetic particle testing have been performed in order to analyse the imperfection sizes and scatters. The fatigue test results of the cruciform joints show, that undercuts lead to lower fatigue strength at the weld toe, as was to be expected. When reducing the fatigue resistance, undercuts could however be tolerated at secondary structural elements or marginally fatigue stressed components. A lack of penetration and/or root fusion can be tolerated, if the fatigue verification at the weld root is performed. A verification at the weld root can only be neglected in case of lack of penetration and/or root fusion, if the weld toe is decisive due to undercuts or large enough weld angels, here shown for 45°.

Predicting fatigue life of metal LPBF components by combining a large fatigue database for different sample conditions with novel simulation strategies

This study presents a unique methodology to systematically predict and evaluate the fatigue behaviour of additively manufactured components. A multitude of factors influence the fatigue performance of end-use application components. To analyse this effect, fatigue behaviour of samples manufactured by laser powder bed fusion (LPBF) is evaluated for different process conditions, namely, build orientation, heat treatment and surface treatment. An extensive experimental test campaign is performed to develop a database of fatigue results capturing all these influencing factors. A Gaussian process is then trained with the observed experimental results to predict the fatigue behaviour for unknown process conditions. This machine learning method is subsequently validated to confirm its capability to represent the experimental data on one hand and to generalize well to unseen data on the other hand. In addition, the method is integrated in a fatigue durability prediction solver. The predictive capability of large-scale simulations was demonstrated for low pressure steam turbine blades manufactured by LPBF and subjected to different combinations of post processes. Subsequent experimental fatigue testing of the blades indicated that the durability solver accurately predicted the crack initiation location. For a combination of stress relieved microstructure and as-fabricated surface, the experimental fatigue lives lie within 95% confidence interval of the lifetimes predicted by the durability solver. For the components with full annealed microstructure and machined surface, the durability solver predicted conservative lifetimes compared to the experimental fatigue lives, demonstrating the capability to predict fatigue behaviour of end-use components in the field. • A new methodology is developed to predict fatigue of additively manufactured metals. • Fatigue behaviour of samples is investigated for different process conditions. • Machine learning and finite element analysis are used to predict fatigue lifetimes of components. • Predicted crack initiation sites coincide with experimental tests.

Statistical analysis of S/N-curves by means of a fatigue database for polypropylene

Material databases of plastics are becoming more and more the focus of applied science and commercial use in industry. Material properties of material manufacturers are often provided in publicly accessible material databases, which usually contain processing and mechanical properties under static loadings. Fatigue strength values are usually not accessible. The fatigue data for thermoplastics is of particular interest, as these materials have a particularly high lightweight construction potential and can be processed with a high degree of automation and reproducibility.Individual fatigue strength parameters for a specific material, environmental condition, geometry and loadings have been investigated in numerous publications. However, no work has been found in which fundamental interactions of different materials, environmental conditions, geometries and loadings on the course of the S/N-Curve have been investigated.In this paper, different effect relationships between temperature, filler type and filler content, fiber orientation and load ratio will be presented for the material Polypropylene (PP). A fatigue strength database of 11 different material manufacturers, from 71 different S/N-Curves with 606 tested samples, serves as a basis. The fatigue database enables a digital twin, which is used for the design of structural components to add a third dimension with artificial intelligence, and which is trained by an engineer. From the determined effect relationships, fatigue factors are to be derived and can be used to evaluate the fatigue strength of a component in the design process and to train the digital twin. The fatigue-strength values from the database also allow a statistical consideration of the slope k and the scattering of the S/N-Curve. The different S/N-Curves are transferred into a Haigh diagram, from which the functional course of the mean stress is determined.

A cuckoo search based neural network to predict fatigue life in rotor blade composites

In modern wind turbine blades industry, fiber-reinforced composites are mostly used for their good mechanical characteristics: high stiffness, low density and long fatigue life. Wind turbine blades are constructed in different structural elements from a variety of composite laminates, often including Unidirectional (UD) material in spars and multiple forms of Multidirectional (MD) in skins and webs. The purpose of this paper is to identify materials that have appropriate fiber orientations to improve fatigue life. By using Cuckoo Search-based Neural Network (CSNN), we have developed a model to predict fatigue life under tension-tension charges for five composite materials, with different fiber stacking sequences embedded in three types of resin matrices (epoxy, polyester and vinylester), which are all appropriate for the design of wind turbine blades. In the CSNN approach used in this work, the cost function was assessed using the Mean Square Error (MSE) computed as the squared difference between the predicted values and the target values for a number of training set samples, obtained from an experimental fatigue database. The results illustrate that the CSNN can provide accurate fatigue life prediction for different MD/UD composite laminates, under different angles of fiber orientation.

Fatigue criteria for short fiber-reinforced thermoplastic validated over various fiber orientations, load ratios and environmental conditions

Design of reinforced plastic parts against fatigue failure has become a serious issue these last few years for increasing engineering field applications. This is indeed a complex problem due to the strong anisotropy induced by the orientation of the fibers during the injection process and to the non-linear dissipative behavior of the matrix. This generates strong influences of numerous parameters (fiber orientation, environment, strain rate, load ratio, …), which complicates both the description of the constitutive response and the definition of a robust and efficient fatigue criterion. This paper presents a very wide fatigue database (480 tension-compression tests) obtained on Polyamide 66 reinforced with 50% of glass fibers (PA66 GF50), for an extended range of load ratios (from −0.5 to 0.7), three orientations from the injection direction (0°, 45°, 90°) and two environmental conditions (50% humidity ratio and 80 °C, 80% humidity ratio and 23 °C). Beyond these experimental results, the goal of this paper is to compare the ability of numerous fatigue criteria to provide a robust description of the fatigue database, possibly with a unified set of parameters. Classical models as well as very recent ones are discussed and two variants of a new fatigue criterion are finally defined. This criterion is able to describe very accurately the full database with only four parameters. Finally, a focus is given to determine the minimal amount of experimental data needed to obtain a reliable description of the fatigue results, on the full ranges of load ratios, orientations and environmental conditions.

Estimation of the Strength Coefficient and Strain Hardening Exponent from Monotonic Tensile Properties of Steels

In order to derive a method for estimating the strength coefficient and strain hardening exponent of steel, the performance parameters of 86 kinds of steel taken from American Iron and Steel Institute (AISI) Bar Steel Fatigue Database were examined and equations that related the strength coefficient and strain hardening exponent to the ultimate tensile strength and yield strength were developed. Correlations from the literature among the strength coefficient, strain hardening exponent and other monotonic tensile properties were also examined and compared to the relationships proposed in this study using the data of 86 kinds of steel. The proposed method was shown to be better used to estimate the strength coefficient and strain hardening exponent.

Investigation on multiaxial strength reduction for multi-directional laminates under variable amplitude loading

Due to their excellent ratio of high strength and stiffness to low density, the use of composite materials in lightweight solutions is growing in widely varying industry sectors. Most of the lightweight structures are loaded cyclically and therefore there is the need for optimized computation models concerning the fatigue of composite materials. The present study mainly focuses on the fatigue life estimation of continuous fibre reinforced plastics under variable amplitude loads. The approach is based on iterative ply-wise calculation of multiaxial stress states using classical laminate theory and a subsequent analysis of the material effort with the use of the failure criteria by Puck. A number of suitable linear and nonlinear residual strength models are examined for an in-depth approach on the multiaxial strength reduction at the ply-level. The aim of this study is to calculate fatigue life of multi-directional laminates with input data from uni-directional plies only. The model is finally validated for a multi-directional laminate under variable amplitude loads with arbitrary pulsating and alternating stress ratios using experimental data from the well documented composite fatigue data base OptiDAT.

INCEFA-PLUS (Increasing safety in NPPs by covering gaps in environmental fatigue assessment)

INCEFA-PLUS is a European Project (funded by the EC HORIZON2020 program) started in July 2015 and lasts five years (until June 2020). The project involves 16 members from all over Europe and its main goal is to guarantee safety in operations of Nuclear Power Plants (NPPs) by delivering experimental data to support the development of improved environmental fatigue assessment guidelines. The issues of common interest are being studied: the effects of mean strain/stress, hold time, strain amplitude and surface finish on the fatigue performance of austenitic stainless steels in the LWR (Light Water Reactor) environment. Within the framework of the CEN (European Committee for Standardization) workshop FATEDA, the consortium developed a fatigue data format, used in an online environmental fatigue database, available for all participants. The paper describes phase one (of three) testing, including conditions such as surface finish and hold time. The plans that are being made for phase two testing will be detailed. The materials used in the tests, the surface finish data and some experimental results for phase one are presented, together with a summary of the INCEFA-PLUS testing protocol. Finally, a review of existing assessment methodologies and a summary of dissemination activities are provided.

Prediction of the critical stress to crack initiation associated to the investigation of fatigue small crack

ABSTRACT. Fatigue design is of vital importance to avoid fatigue small crack growth in engineering structures. This study shows that the critical fatigue design stress can be defined below the usual endurance limit, considered in rules and codes. The material constitutive behaviour is using linear isotropic elasticity. Lassere and Pallin-Luc [1-2] use the elastic energy and over-energy under uniaxial load (tension and rotating bending). The authors deduce the influencing critical stress value corresponding to ?*. It’s a linear approach. We propose an over-energy under dissymmetrical rotating bending and expressed in the ellipse axes. An asymptotic approach is transformed the over-energy in polynomial function of critical stress. Unknown depend on experimental service conditions, endurance limit of tension and rotating bending of specimen. The fatigue database of 30NCD16 steel studied by Froustey and Dubar [3-13] is used. Critical stresses are evaluated (Fig. 2). The research done by Manning and all [4] has shown the small crack effect to be as large as 0.3 mm. Small crack and critical stress are illustrated here in as resulting from pure bending approach expressed by Bazant law [7]. It’s reproduces well the Kitagawa diagram [6] (Fig. 3). When the short cracks are hidden in the material, we shows that the number cycles during small crack growth be significantly higher (Fig. 4) than the corresponding cycles of large cracks growth (ONI’s fatigue test) for the same physically crack size. Indeed its evolution can be blocked by a microstructural barrier (grain boundary, for example). Hence, the considerations of small crack growth are strongly influencing the fatigue life of a component or structure. KEYWORDS. Tensile; Dissymmetrical rotating bending; Over-energy; Critical stress; Small crack; Fatigue cycle.

INCEFA-PLUS Programme Overview and Update

INCEFA-PLUS is a five year project supported by the European Commission HORIZON2020 programme which commenced in mid 2015. 16 organisations from across Europe have combined forces to deliver new experimental data and a fatigue assessment procedure which will support the development of improved guidelines for assessment of environmental fatigue damage to ensure safe operation of nuclear power plants.Prior to the start of INCEFA-PLUS, an in-kind study was undertaken by several European organisations with the aim of developing the current state of the art for this technical area. This study identified three experimental variables which required further study in order to support improved assessment methodology for environmental fatigue, namely the effects of mean stress/strain, hold time and surface finish. Within INCEFA-PLUS, the effects of these three variables, plus strain amplitude, on fatigue endurance of austenitic stainless steels in light water reactor environments are therefore being studied experimentally. The data obtained will be collected and standardised in an online environmental fatigue database. In order to facilitate the exchange of fatigue data a standardized data format will be developed in the framework of a CEN workshop, to which international participants are welcome to participate. The outcome of the workshop will be a pre-normative document, a CEN Workshop Agreement (CWA) which will set a standard for enabling the exchange of fatigue data not only within the project but within the fatigue community. Based on the data generated and the resulting improvement in understanding, it is planned that INCEFAPLUS will develop and disseminate methods for including the new insights into assessment procedures for environmental fatigue degradation. This will take better account of the effects of mean strain, hold time and surface finish.This paper will provide more details on the background to this project and the way the project is organized to meet its objectives. Details will be provided as to how uncertainties due to variations in testing practice and specimen preparation have been minimized. Additionally, the choices associated with testing for the effects of surface finish, hold time and mean stress will be described along with the status of decisions so far within the project. The paper will also report current status of the project and when findings are likely to be disseminated.

A Case Study of Finite Element Analysis and Designing with Data from the AFS Strain-Life Fatigue Database

This paper estimates total fatigue and transition life using strain-controlled fatigue data generated for various cast materials, using a practical example of a structural hub casting that has been in service for many years. The material data generated from recent testing, service loads and boundary conditions from the potential failure modes are entered into a finite element analysis (FEA) to predict the stress amplitudes using the same geometry that is employed for predicting the fatigue life.

Yawn analysis with mouth occlusion detection

One of the most common signs of tiredness or fatigue is yawning. Naturally, identification of fatigued individuals would be helped if yawning is detected. Existing techniques for yawn detection are centred on measuring the mouth opening. This approach, however, may fail if the mouth is occluded by the hand, as it is frequently the case. The work presented in this paper focuses on a technique to detect yawning whilst also allowing for cases of occlusion. For measuring the mouth opening, a new technique which applies adaptive colour region is introduced. For detecting yawning whilst the mouth is occluded, local binary pattern (LBP) features are used to also identify facial distortions during yawning. In this research, the Strathclyde Facial Fatigue (SFF) database which contains genuine video footage of fatigued individuals is used for training, testing and evaluation of the system.