Strain Measurement during Quasi-Static and Cyclic Loads in AL-6XN Material Using Digital Image Correlation Technique.

A customized digital image correlation (DIC) system was implemented to monitor the strain produced in a cold-rolled AL-6XN stainless steel plate, 3.0 mm thick, subjected to quasi-static and cyclic loading tests. A comparison of the DIC strain measurements was made against those provided by conventional extensometers. Furthermore, the DIC system was used to monitor the fatigue crack initiation in low-cycle fatigue tests. The true stress-strain behavior for the AL-6XN material was properly captured by the DIC measurements. For low-cycle fatigue tests (strain control), the strain mapping generated by DIC allowed for identifying zones with higher strain than the nominal strain amplitude applied (εa) since the first stages of the fatigue life (FL). These zones become potential fatigue crack initiation sites.

Mechanical testing dataset of cast copper alloys for the purpose of digitalization.

This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled "Toward a digital materials mechanical testing lab" [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.

Study on the Deformation Behavior of Two Phases during the Low Cycle Fatigue of UNS S32750 Duplex Stainless Steel.

In this paper, the deformation behavior of UNS S32750 (S32750) duplex stainless steel during low cycle fatigue was studied by controlling the number of cycles. The microstructure of the specimens under different cycles was characterized by optical microscope (OM), scanning electron microscope (SEM), electron backscatter diffraction (EBSD), and transmission electron microscope (TEM). The microhardness of the two phases was measured by a digital microhardness instrument. The results showed that the microhardness of ferrite increases significantly after the first 4000 cycles, while the austenite shows a higher strain hardening rate after fatigue fracture, and the microhardness of ferrite and austenite increases by 23 HV and 87 HV, respectively. The two-phase kernel average misorientation (KAM) diagram showed that the continuous accumulation of plastic deformation easily leads to the initiation of cracks inside the austenite and at the phase boundaries. The evolution of dislocation morphology in the two phases was obviously different. With the increase in cycle number, the dislocation in ferrite gradually transforms from dislocation bundles and a dislocation array to a sub-grain structure, while the dislocation in austenite gradually develops from dipole array to an ordered Taylor lattice network structure.

Modeling of LCF Behaviour on AISI316L Steel Applying the Armstrong-Frederick Kinematic Hardening Model.

The combination of kinematic and isotropic hardening models makes it possible to model the behaviour of cyclic elastic-plastic steel material, though the estimation of the hardening parameters and catching the influence of those parameters on the material response is a challenging task. In the current work, an approach for the numerical simulation of the low-cycle fatigue of AISI316L steel is presented using a finite element method to study the fatigue behaviour of the steel at different strain amplitudes and operating temperatures. Fully reversed uniaxial LCF tests are performed at different strain amplitudes and operating temperatures. Based on the LCF test experimental results, the non-linear isotropic and kinematic hardening parameters are estimated for numerical simulation. On comparing, the numerical simulation results were in very good agreement with those of the experimental ones. This presented method for the numerical simulation of the low-cycle fatigue on AISI316 stainless steel can be used for the approximate prediction of the fatigue life of the components under different cyclic loading amplitudes.

Crystal Plasticity Parameter Optimization in Cyclically Deformed Electrodeposited Copper-A Machine Learning Approach.

This paper describes an application of a machine learning approach for parameter optimization. The method is demonstrated for the elasto-viscoplastic model with both isotropic and kinematic hardening. It is shown that the proposed method based on long short-term memory networks allowed a reasonable agreement of stress-strain curves to be obtained for cyclic deformation in a low-cycle fatigue regime. The main advantage of the proposed approach over traditional optimization schemes lies in the possibility of obtaining parameters for a new material without the necessity of conducting any further optimizations. As the power and robustness of the developed method was demonstrated for very challenging problems (cyclic deformation, crystal plasticity, self-consistent model and isotropic and kinematic hardening), it is directly applicable to other experiments and models.

Low-Cycle Fatigue Behavior and the Combined Cyclic Hardening Material Model of Plate-Shaped Zn-22Al Alloy for Seismic Dampers.

This study investigates the potential of the plate-shaped Zn-22 wt.% Al (Zn-22Al) alloy as an innovative energy dissipation material for seismic damping devices, since plate-shaped material is more suitable to fabricate large-scale devices for building structures. The research begins with the synthesis of Zn-22Al alloy, given its unavailability in the commercial market. Monotonic tensile tests and low-cycle fatigue tests are performed to analyze material properties and fatigue performance of plate-shaped specimens. Monotonic tensile curves and cyclic stress-strain curves, along with SEM micrographs for microstructure and fracture surface analysis, are acquired. The combined cyclic hardening material model is calibrated to facilitate finite element analysis. Experimental results reveal exceptional ductility in Zn-22Al alloy, achieving a fracture strain of 200.37% (1.11 fracture strain). Fatigue life ranges from 1126 to 189 cycles with increasing strain amplitude (±0.8% to ±2.5%), surpassing mild steel by at least 6 times. The cyclic strain-life relationships align well with the Basquin-Coffin-Manson relationship. The combined kinematic/isotropic hardening model in ABAQUS accurately predicts the hysteretic behavior of the material, showcasing the promising potential of Zn-22Al alloy for seismic damping applications.

Influence of Severe Plastic Deformation and Aging on Low Cycle Fatigue Behavior of Al-Mg-Si Alloys.

Strain-controlled low cycle fatigue (LCF) tests were conducted on conventionally grained (CG) and ultrafine-grained (UFG) Al-Mg-Si alloys treated under various aging conditions. In the cyclic stress response (CSR) curves, CG peak-aged (PA) alloys showed initial cyclic hardening and subsequent saturation, whereas CG over-aged (OA) alloys displayed cyclic softening behavior close to saturation. The UFG materials exhibited continuous cyclic softening except for UFG 3; it originates from the microstructural stability of the UFG materials processed by severe plastic deformation (SPD). Using a strain-based criterion, the LCF behavior and life of the CG and UFG materials were analyzed and evaluated; the results are discussed in terms of strengthening mechanisms and microstructural evolution. In the CG materials, the LCF life changed markedly owing to differences in deformation inhomogeneity depending on the precipitate state. However, the UFG materials displayed a decreasing LCF life as cyclic softening induced by dynamic recovery became more severe; additionally, a relationship between the microstructural stability of the UFG materials and the cyclic strain hardening exponent n' was suggested.

Energy-Based Unified Models for Predicting the Fatigue Life Behaviors of Austenitic Steels and Welded Joints in Ultra-Supercritical Power Plants.

The development of a cost-effective and accurate model for predicting the fatigue life of materials is essential for designing thermal power plants and assessing their structural reliability under operational conditions. This paper reports a novel energy-based approach for developing unified models that predict the fatigue life of boiler tube materials in ultra-supercritical (USC) power plants. The proposed method combines the Masing behavior with a cyclic stress-strain relationship and existing stress-based or strain-based fatigue life prediction models. Notably, the developed models conform to the structure of the modified Morrow model, which incorporates material toughness (a temperature compensation parameter) into the Morrow model to account for the effects of temperature. A significant advantage of this approach is that it eliminates the need for tensile tests, which are otherwise essential for assessing material toughness in the modified Morrow model. Instead, all material constants in our models are derived solely from fatigue test results. We validate our models using fatigue data from three promising USC boiler tube materials-Super304H, TP310HCbN, and TP347H-and their welded joints at operating temperatures of 500, 600, and 700 °C. The results demonstrate that approximately 91% of the fatigue data for all six materials fall within a 2.5× scatter band of the model's predictions, indicating a high level of accuracy and broad applicability across various USC boiler tube materials and their welded joints, which is equivalent to the performance of the modified Morrow model.

Thermodynamic Entropy-Based Fatigue Life Assessment Method for Nickel-Based Superalloy GH4169 at Elevated Temperature Considering Cyclic Viscoplasticity.

This paper develops a thermodynamic entropy-based life prediction model to estimate the low-cycle fatigue (LCF) life of the nickel-based superalloy GH4169 at elevated temperature (650 °C). The gauge section of the specimen was chosen as the thermodynamic system for modeling entropy generation within the framework of the Chaboche viscoplasticity constitutive theory. Furthermore, an explicitly numerical integration algorithm was compiled to calculate the cyclic stress-strain responses and thermodynamic entropy generation for establishing the framework for fatigue life assessment. A thermodynamic entropy-based life prediction model is proposed with a damage parameter based on entropy generation considering the influence of loading ratio. Fatigue lives for GH4169 at 650 °C under various loading conditions were estimated utilizing the proposed model, and the results showed good consistency with the experimental results. Finally, compared to the existing classical models, such as Manson-Coffin, Ostergren, Walker strain, and SWT, the thermodynamic entropy-based life prediction model provided significantly better life prediction results.

Effect of Testing Conditions on Low-Cycle Fatigue Durability of Pre-Strained S420M Steel Specimens.

S420M steel subjected to strain-controlled low-cycle fatigue does not exhibit a period of cyclic properties stabilization. The maximum stress on a cycle continuously drops until fracture. For this reason, it is difficult to plan experimental research for different types of control in such a way that their results can be considered comparable. The aim of this paper is to present and discuss the results of tests conducted in various conditions of low-cycle fatigue of S420M steel specimens, both undeformed and pre-strained. In both loading conditions, after initial deformation, a significant change in the cyclic properties of steel described by the parameters of the hysteresis loop was observed. Also, the fatigue life of the pre-strained specimens appeared to be different from unstrained specimens and was affected by the test loading conditions. The reduction in life under controlled stress conditions was attributed to the increase in the extent of plastic deformation and stress and the occurrence of creep.

Mechanical properties and constitutive models of shape memory alloy for structural engineering: A review.

Shape Memory Alloys (SMAs) are an innovative material with the unique features of superelasticity and energy dissipation capabilities under extreme loads. Due to their unique features, they have a great potential to be employed in structural engineering applications under different conditions. However, in order to effectively use SMAs in civil engineering structures and model their behaviors accurately in Finite Element (FE) packages, it is crucial for structural engineers to comprehend the mechanical properties and cyclic behavior of different SMA compositions under varying loading conditions. While previous studies have focused mainly on the cyclic behavior of SMAs under tensile loading, it is important to evaluate their fatigue behavior under cyclic tension-compression loading for seismic applications. This literature review aims to discuss the current gaps in the existing literature on the behavior of SMA rebars under low-cycle fatigue (LCF). The review provides a comprehensive overview of the primary characteristics of SMAs, summarizes the mechanical properties of SMAs presented in the literature and the parameters that affect them, and critically evaluates the effects of cyclic loading and LCF on SMAs. The review also provides a summary of the different constitutive models of SMAs and compares their advantages and limitations, which helps structural engineers to employ an appropriate constitutive model for predicting the accurate behavior of SMAs in FE software.

Low cycle fatigue lifetime prediction of superplastic shape memory alloy structures: Application to endodontic instruments.

In this paper we propose a methodology for a fast numerical determination of low cycle fatigue lifetime of superelastic shape memory alloy structures. This method is based on the observation that generally, in low cycle fatigue, shape memory alloy (SMA) structures are subject to loadings that lead to a confined non-linear behaviour at stress concentration points, such as notches. Numerical fatigue lifetime prediction requires the computation of the mechanical state at critical points. However, classical computational methods, like the non-linear finite element method, lead to a prohibitive computation time in a non-linear cyclic framework. To overcome this issue, we propose to use fast prediction methods, based on localization laws. Following the determination of the stabilized behaviour, an energetic fatigue criterion is applied. The numerical fatigue life prediction model is validated experimentally on SMA endodontic instruments.

Low-Cycle Fatigue Behavior of Wire and Arc Additively Manufactured Ti-6Al-4V Material.

Additive manufacturing (AM) techniques, such as wire arc additive manufacturing (WAAM), offer unique advantages in producing large, complex structures with reduced lead time and material waste. However, their application in fatigue-critical applications requires a thorough understanding of the material properties and behavior. Due to the layered nature of the manufacturing process, WAAM structures have different microstructures and mechanical properties compared to their substrate counterparts. This study investigated the mechanical behavior and fatigue performance of Ti-6Al-4V fabricated using WAAM compared to the substrate material. Tensile and low-cycle fatigue (LCF) tests were conducted on both materials, and the microstructure was analyzed using optical microscopy and scanning electron microscopy (SEM). The results showed that the WAAM material has a coarser and more heterogeneous grain structure, an increased amount of defects, and lower ultimate tensile strength and smaller elongation at fracture. Furthermore, strain-controlled LCF tests revealed a lower fatigue strength of the WAAM material compared to the substrate, with crack initiation occurring at pores in the specimen rather than microstructural features. Experimental data were used to fit the Ramberg-Osgood model for cyclic deformation behavior and the Manson-Coffin-Basquin model for strain-life curves. The fitted models were subsequently used to compare the two material conditions with other AM processes. In general, the quasi-static properties of WAAM material were found to be lower than those of powder-based processes like selective laser melting or electron beam melting due to smaller cooling rates within the WAAM process. Finally, two simplified estimation models for the strain-life relationship were compared to the experimentally fitted Manson-Coffin-Basquin parameters. The results showed that the simple "universal material law" is applicable and can be used for a quick and simple estimation of the material behavior in cyclic loading conditions. Overall, this study highlights the importance of understanding the mechanical behavior and fatigue performance of WAAM structures compared to their substrate counterparts, as well as the need for further research to improve the understanding of the effects of WAAM process parameters on the mechanical properties and fatigue performance of the fabricated structures.

The Low-Cycle Fatigue Behavior, Microstructure Evolution, and Life Prediction of SS304: Influence of Temperature.

To study the fatigue failure and microstructure evolution behavior of SS304, low-cycle fatigue tests are conducted at room temperature (RT), 300 °C, and 650 °C. The results indicate that, because of the influence of the dislocation walls, carbon-containing precipitates, and deformation twins, the cyclic hardening behavior is presented at RT. However, different from the cyclic hardening behavior at RT, the cyclic softening behavior of SS304 can be observed due to the dynamic recovery and recrystallization containing dislocation rearrangement and annihilation at 300 °C and 650 °C. In addition, two fatigue crack initiation modes are observed. At RT, the single fatigue crack initiation mode is observed. At high temperatures, multiple crack initiation modes are presented, resulting from the degradation of material properties. Furthermore, a new fatigue life prediction model considering the temperature is conducted as a reference for industrial applications.

Effects of V-N Microalloying on Low-Cycle Fatigue Property in the Welded Joints of Constructional Steel.

Low-cycle fatigue testing was carried out for the welded joints of constructional steels containing 0% V + 0.0021% N and 0.10% V + 0.0078% N, and the effects of V-N microalloying on the low-cycle fatigue property of the welded joints were investigated. The results showed that when the total strain amplitudes were 1.2%, 1.4% and 1.6%, the mean low-cycle fatigue lives of the welded joints of steel containing 0.10% V + 0.0078% N were 5050, 2372 and 1535 cycles, respectively, which were significantly higher than those of the welded joints of steel containing 0% V + 0.0021% N; however, when the total strain amplitudes increased to 1.8% and 2.0%, the mean low-cycle fatigue lives of the welded joints of steel containing 0.10% V + 0.0078% N were 575 and 367 cycles, respectively, which were gradually lower than those of the welded joints of steel containing 0% V + 0.0021% N. The reasons causing the difference of low-cycle fatigue life were explained by the dislocation structure and precipitates in the welding heat-affected zone, plastic strain energy density of the welded joints, and fatigue fracture morphology. When the low-cycle fatigue life is between 100 and 200 cycles, the cyclic toughness of the welded joint of steel containing 0.10% V + 0.0078% N is between 57.48 and 78.22 J/cm3, which is higher than that of the welded joint of steel containing 0% V + 0.0021% N, indicating that the welded joint of steel containing 0.10% V + 0.0078% N is able to absorb more energy in a seismic condition, therefore possessing better seismic resistance.

Fatigue Behavior of the FGH96 Superalloy under High-Temperature Cyclic Loading.

Strain-controlled low-cycle fatigue (LCF) tests and stress-controlled creep-fatigue interaction (CFI) tests on the FGH96 superalloy were carried out at 550 °C to obtain the cyclic softening/hardening characteristics at different strain amplitudes and ratcheting strain characteristics under different hold time. The failure mechanism of the FGH96 superalloy under different loading conditions was analyzed through fracture observations. The results show that the FGH96 superalloy exhibits different cyclic softening/hardening characteristics at different strain amplitudes, and the introduction of the hold time at peak stress exacerbates the ratcheting strain of the FGH96 superalloy under asymmetric stress cycles. Fracture observations show that the magnitude of the strain amplitude, high-temperature oxidation, and the introduction of the hold time will affect the mechanical properties of the FGH96 superalloy and change its fracture mode.

Fatigue reliability analysis of aeroengine blade-disc systems using physics-informed ensemble learning.

For the fatigue reliability analysis of aeroengine blade-disc systems, the traditional direct integral modelling methods or separate independent modelling methods will lead to low computational efficiency or accuracy. In this work, a physics-informed ensemble learning (PIEL) method is proposed, i.e. firstly, based on the physical characteristics of blade-disc systems, the complex multi-component reliability analysis is split into a series of single-component reliability analyses; moreover, the PIEL model is established by introducing the mapping of multiple constitutive responses and the multi-material physical characteristics into the ensemble learning; finally, the PIEL-based system reliability framework is established by quantifying the failure correlation with the Copula function. The reliability analysis of a typical aeroengine high-pressure turbine blade-disc system is regarded as an example to verify the effectiveness of the proposed method. Compared with the direct Monte Carlo, support vector regression, neural network, ensemble learning and physics-informed neural network, the proposed method exhibits the highest computing accuracy and efficiency, and is validated to be an efficient method for the reliability analysis of blade-disc systems. The current work can provide a novel insight for physics-informed modelling and fatigue reliability analyses. This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.

Effect of Polymer Matrix on Inelastic Strain Development in PI- and PEI-Based Composites Reinforced with Short Carbon Fibers under Low-Cyclic Fatigue.

Since the inelastic strain development plays an important role in the low-cycle fatigue (LCF) of High-Performance Polymers (HPPs), the goal of the research was to study the effect of an amorphous polymer matrix type on the resistance to cyclic loading for both polyimide (PI)- and polyetherimide (PEI)-based composites, identically loaded with short carbon fibers (SCFs) of various lengths, in the LCF mode. The fracture of the PI and PEI, as well as their particulate composites loaded with SCFs at an aspect ratio (AR) of 10, occurred with a significant role played by cyclic creep processes. Unlike PEI, PI was less prone to the development of creep processes, probably because of the greater rigidity of the polymer molecules. This increased the stage duration of the accumulation of scattered damage in the PI-based composites loaded with SCFs at AR = 20 and AR = 200, causing their greater cyclic durability. In the case of SCFs 2000 µm long, the length of the SCFs was comparable to the specimen thickness, causing the formation of a spatial framework of unattached SCFs at AR = 200. The higher rigidity of the PI polymer matrix provided more effective resistance to the accumulation of scattered damage with the simultaneously higher fatigue creep resistance. Under such conditions, the adhesion factor exerted a lesser effect. As shown, the fatigue life of the composites was determined both by the chemical structure of the polymer matrix and the offset yield stresses. The essential role of the cyclic damage accumulation in both neat PI and PEI, as well as their composites reinforced with SCFs, was confirmed by the results of XRD spectra analysis. The research holds the potential to solve problems related to the fatigue life monitoring of particulate polymer composites.

Low cycle fatigue properties of porcine aorta - Pilot study.

INTRODUCTION: Biomechanical rupture risk assessment of aortic tissues is commonly based on computed stress to measured uniaxial static strength comparison. Loading of the arterial wall, however, is cyclic; thus, the static strength may not be a proper limit value. This study investigates the low cycle fatigue of porcine aortic samples tested in a circumferential direction. METHODS: 7 porcine descending aorta (both thoracic and abdominal) were harvested and 56 dogbone-shaped samples were prepared. Static strength was measured, the limit of engineering stress was chosen and then force controlled cyclic loading was performed up to 100,000 cycles. Efforts were made to obtain a sufficient number of points across the entire range of 0-100,000 cycles. Data were fitted by both linear and logarithmic law and extrapolated towards 1 cycle for validation against static strength/ultimate tension. Data dispersion was evaluated via normalised root mean square error. RESULTS: Out of 56 samples from 7pigs, 28 samples from 4 pigs were successfully tested. There was a strong negative correlation between applied stress/tension and number of cycles to failure. The fitting of both linear and logarithmic values resulted in a similar accuracy (R2=0.72 and 0.71 for stress and R2=0.62 and 0.7 for tension, respectively), while predicting static failure properties was more accurate by logarithmic law. NRMSE was lower for absolute values (20-21%) than for relative values (27-30%). CONCLUSIONS: Absolute values of cyclic strength and tension are less dispersed than relative ones. Logarithmic fits are more robust in predicting static strength from cyclic data, while linear fits serve as a lower limit estimation.

Influence of Pre-Strain on Static and Fatigue Properties of S420M Steel.

This paper reports the results of static tensile and low-cycle fatigue tests on S420M steel specimens. As-received (unstrained) and pre-strained specimens were used during the tests. Based on the static tensile tests carried out, no effect of pre-strain on the basic strength parameters of the S420M steel was found. Low-cycle fatigue tests showed that the pre-strain of the specimens causes a change in the cyclic properties of the steel and a slight increase in fatigue life compared to that of the as-received specimens. The greatest increase in durability was observed at the lowest strain levels.