Strain controlled fatigue of P92 steel with various strain hold dwells introduced at the peak loading point were conducted at 625 °C. Two features which depend on the cycle and strain range level ...were observed under the fatigue-creep condition for the viscous and cyclic softening material. The first one is the accelerated cyclic softening response which is ascribed to the accumulated inelastic strain transformation from the creep mechanism during the strain dwell period and becomes more significant with the decrease of strain ranges. The second one is the decelerated stress relaxation behavior which is caused by the reduced viscous stress related to the continuous cyclic softening and fades with the decrease of cyclic strain ranges. Accordingly, a new unified viscoplastic constitutive model within the framework of Chaboche model was developed by improving the nonlinear isotropic hardening rule and the kinematic hardening rule with a cyclic softening parameter. As a result, the accelerated cyclic softening and decelerated stress relaxation response of fatigue-creep interaction was finely reproduced by the proposed model.
•Strain controlled fatigue of P92 with various strain hold dwells introduced at the peak loading point were conducted at 625 °C.•The accelerated cyclic softening response increases with the decrease of strain ranges due to the strain dwell.•The decelerated stress relaxation behavior fades with the decrease of cyclic strain ranges due to the continuous cyclic softening.•A unified viscoplastic constitutive model was developed by improving the kinematic hardening rule with a cyclic softening parameter.
Axially loaded push-pull cyclic tests of a precipitation-hardened stainless steel with different sampling orientations were conducted in high cycle and very high cycle fatigue regimes. Results showed ...apparent fatigue anisotropy with non-metallic inclusions dominating crack initiation behavior. A fatigue lifing model was developed by combining size, location and shape of inclusions into a new form of Z parameter to rationalize the orientation effect. Using a multi-scale and full-field approach, the inclusion-induced interior cracking mechanisms were found to be associated with inclusion-microstructure interaction resulted plasticity. Micro-hardness at the cracking site was the lowest on the fracture surface, and surrounding microstructures showed formation of small grains with clear interfaces. The fine granular area was characteristic of several nano-scale fine grains formed in terms of dislocation cell structures by martensitic laths breakdown. The coalescence of interfaces or micro-crackings finally became interior early fatigue cracks. The mechanistic modeling of “fragmentation of martensitic laths and formation of dislocation cells” revealed a microstructure-dependent crack initiation and stage I growth for interior fatigue cracking. All these inform the significance of combining metallurgical and processing factors in designing against fatigue of engineering materials.
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•A general machine learning life prediction method is proposed for creep, fatigue and creep-fatigue conditions.•Creep, fatigue and creep-fatigue data are integrated into a unified dataset.•DNN ...exhibits better prediction accuracy than conventional machine learning models.
Deep learning is a particular kind of machine learning, which achieves great power and flexibility by a nested hierarchy of concepts. A general life prediction method for components under creep, fatigue and creep-fatigue conditions is proposed. Fatigue, creep and creep-fatigue data of a typical austenitic stainless steel (i.e., 316) are integrated. Conventional machine learning models (e.g., support vector machine, random forest, Gaussian process regression, shallow neural network) and deep learning model (e.g., deep neural network) are applied for life predictions. Results show that deep learning model exhibits better prediction accuracy and generalization ability than conventional machine learning model.
•The application of machine learning in fatigue life prediction is reviewed.•The shift from data-driven to physics-based hybrid approaches is discussed.•The approaches of combining physics-based and ...data-driven models are described.•The future challenges and development directions of fatigue life prediction are discussed.
Fatigue life prediction is critical for ensuring the safe service and the structural integrity of mechanical structures. Although data-driven approaches have been proven effective in predicting fatigue life, the lack of physical interpretation hinders their widespread applications. To satisfy the requirements of physical consistency, hybrid physics-informed and data-driven models (HPDM) have become an emerging research paradigm, combining physical theory and data-driven models to realize the complementary advantages and synergistic integration of physics-based and data-driven approaches. This paper provides a comprehensive overview of data-driven approaches and their modeling process, and elaborates the HPDM according to the combination of physical and data-driven models, then systematically reviews its application in fatigue life prediction. Additionally, the future challenges and development directions of fatigue life prediction are discussed.
Single‐atom catalysts (SACs) have garnered enormous interest due to their remarkable catalysis activity. However, the exploitation of universal synthesis strategy and regulation of coordination ...environment of SACs remain a great challenge. Herein, a versatile synthetic strategy is demonstrated to generate a series of transition metal SACs (M SAs/NC, M = Co, Cu, Mn; NC represents the nitrogen‐doped carbon) through defect engineering of metal‐organic frameworks (MOFs). The interatomic distance between metal sites can be increased by deliberately introducing structural defects within the MOF framework, which inhibits metal aggregation and consequently results in an approximately 70% increase in single metal atom yield. Additionally, the coordination structures of metal sites can also be facilely tuned. The optimized Co SAs/NC‐800 exhibits superior activity and excellent reusability for the selective hydrogenation of nitroarenes, surpassing several state‐of‐art non‐noble‐metal catalysts. This study provides a new avenue for the universal fabrication of transition metal SACs.
A general metal–organic framework defect engineering strategy is proposed to increase the yield of single‐atom catalysts. This strategy enlarges the distance between metal active sites, effectively hindering the aggregation of metal atoms and affording a 70% improved yield of metal single atoms. The optimized Co SAs/NC‐800 exhibits superior activity and reusability in nitroarene hydrogenation.
•Physical origin of cyclic softening discrepancy between stress and strain cycling are clarified.•A cyclic softening model is developed involving the special dislocation annihilation and storage ...events.•Various cyclic responses under different loading modes were predicted very well by the proposed model with a single parameter set.
Stress and strain controlled low cycle fatigue of the modified 9–12% Cr steel with the hierarchical arranged lath martensitic structure were conducted. We found that, apart from microstructure recovery in lath structure, an additional mechanism of reverse avalanche of low angle boundary, associated with the burst-like plastic deformation is responsible for the accelerated softening during stress cycling. These microstructural evolutions can be explicitly represented via deriving different dislocation evolution laws in terms of dislocation annihilation and storage events. Accordingly, a new model is proposed involving the microstructural evolution. Results indicate that the accelerated softening behavior under stress cycling can be reproduced very well by the present model with a very limited number of adjustable parameters. In addition, the model can capture the features of cyclic response and microstructural evolution under both the strain and stress cycling over a wide range of amplitudes.
It is known that fine granular area morphology is often formed around interior micro‐defect in the case of very high cycle fatigue failure of high strength steel. The mechanism of “fragmentation of ...martensitic laths and formation of dislocation cells” (Zhu's model), which revealed a microstructure‐dependent crack initiation and early growth for micro‐defect induced internal fatigue cracking, was discussed in several lathy martensitic or similar steels, verified under environmental fatigue, and applicable to white etching crack in rotating contact fatigue. A machine learning‐Z parameter integrated approach was developed for fatigue life, which is promising for design against fatigue of engineering structures for long life.
Highlights
The FGA model of martensitic steels in air (Zhu's model) was illustrated.
Zhu's model was confirmed in environmental media and similar steels.
Zhu's model was applicable to white etching crack in rotating contact fatigue.
Machine learning‐Z parameter was integrated for fatigue life prediction.
•Nonlinear Lamb wave imaging of micro-damage is achieved based on wavefield data.•A new approach is proposed for weak nonlinear feature enhancement.•Demonstrated capability of accurately imaging the ...fatigue crack tip.•Visualize the wave field of the harmonics.
The traditional nonlinear ultrasonic technique, as typified by the second-harmonic generation and the frequency mixing response, can be employed to identify and characterize the micro-damage. However, the research on micro-damage characterization using nonlinear Lamb wave imaging technique remains an ongoing challenge and is rarely reported. A method called standardized amplitude difference is proposed for nonlinear feature enhancement, and further for fatigue crack imaging based on the wavefield data. Wavefield data contain abundant information on the spatial and temporal variation of propagating waves in the damaged structure. The nonlinearity index β′ of the signal difference under the high and low incident wave amplitudes is calculated for fatigue crack imaging. Two scanning methods, including local scanning and global scanning, are introduced to image the fatigue crack tip and visualize the wave field of the harmonics respectively. The experimental validation, based on the imaging results of an aluminum alloy plate specimen with a barely visible fatigue crack and a steel plate with a blind hole, manifests that the proposed method can be used to enhance and extract the nonlinear features and suppress the fundamental frequency, so as to improve the signal-to-noise ratio (SNR) of the micro-damage imaging results.
The defect classification task is of great benefit to evaluating the safety performance of equipment and providing useful feedback information for discovering production process problems. In this ...article, we present a semisupervised learning (SSL) framework for transient thermography detection to employ the temporal and spatial information encoded into the three-dimensional transient thermal tensor data and provide pixel-level classification results for defect types. The time- and frequency-domain physical models for the transient thermal evolution of different kinds of defects are established to illustrate the theoretical foundation of defects classification based on transient thermography. The semisupervised multiclass Laplacian support vector machine is proposed to enable involving the abundant unlabeled data for enhancing learning performance in practical industrial applications where labeled samples are insufficient and labeling work is costly and laborious. A case study on silicone insulating materials with various types of artificial simulated internal defects validates the stronger generalized ability of the proposed method. This work, for the first time, proposes an SSL framework in transient thermography-based defect detection studies. It is believed that our proposed method is quite inspired for introducing SSL techniques to transient thermography for preferable performance in practical industrial applications.
In this paper, nonlinear Lamb waves with phase-velocity mismatching are proposed to detect accurately closed cracks by excluding the intrinsic material nonlinearity. Simulations and experimental ...studies were conducted to analyze double frequency Lamb waves (DFLWs) induced by the closed cracks and the intrinsic material nonlinearity. The results show that DFLWs induced by the material nonlinearity are negligible as compared with that caused by the contact acoustic nonlinearity (CAN) of the closed cracks. The closed cracks can be accurately detected using the proposed method, and the acoustic nonlinearity parameter increases monotonically with the crack evolution. The findings of this study provide a feasible method for detection and characterization of closed cracks.
•Closed cracks are effectively detected using phase-velocity mismatching method.•Material nonlinearity is excluded in the detection of closed cracks.•Acoustic nonlinearity parameter increases monotonously with crack length.