Mechanical Fatigue Research Articles

Utilization of coal bottom ash in zero-carbon footprint pavement quality geopolymer concrete

Worldwide demand for natural fine aggregates (NFA) in the construction sector has skyrocketed in recent decades, but NFA supply is becoming scarcer. At the same time, thermal power plants are producing massive quantities of coal bottom ash (CBA) which impacts the environment. As per the latest research, CBA can be used as NFA in concrete preparation. This study examines the fresh and mechanical properties, durability characteristics, and fatigue life of pavement quality geopolymer concrete (PQGPC) mixes prepared with the partial addition of CBA as NFA. Results found that after 28 days of curing, the basic properties like workability, compressive and flexural strength with the addition of 30% CBA-based PQGPC (GPC-30) mix are safe as per the requirement of rigid pavements. Furthermore, compared to the PQGPC mix, GPC-30 has a 2% lower endurance limit against fatigue at 2 million cycles at different stress levels of 0.55, 0.60, 0.65, and 0.70, respectively. Even though GPC-30 possesses 19% lower flexural strength than regular PQGPC, the fatigue life is comparable. So, incorporating CBA in the preparation of green PQGPC pavements not only lessens the reliance on NFA but also mitigates the need for landfills.

The effect of perceived organizational support and ego-resilience on the relationship between occupational stressors and compassion fatigue in COVID-19 frontline nurses: a cross-sectional study in Sichuan, China.

To investigate the level of compassion fatigue among frontline nurses during the COVID-19 pandemic and to explore the relationship between occupational stressors and compassion fatigue among frontline nurses based on structural equation modelling. Three years into the COVID-19 pandemic, nurses on the frontlines of the battle were overwhelmed by affective and emotional inputs while caring for patients, and they generally experienced varying degrees of psychological problems. High levels of compassion fatigue can affect nursing quality and patient safety and therefore should be taken seriously by nursing managers. A cross-sectional survey of 1432 frontline nurses in Sichuan Province, China, was conducted from January to March 2023 via convenience sampling methods. The General Information Questionnaire, the Nurses' Occupational Stressors Scale, the Ego-Resilience Scale, the Chinese version of the Compassion Fatigue Brief Scale, and the Perceived Organizational Support Scale were used to collect the data. Hypotheses were tested using structural equation models and bootstrapping methods. Nurse occupational stressors had a significant direct effect on compassion fatigue (B = 2.429, p < 0.001). Perceived organizational support exerted a mediating effect of 11.36% between occupational stressors and compassion fatigue. In addition, ego-resilience had a moderating role in the relationship between nurses' occupational stressors and compassion fatigue, between nurses' occupational stressors and perceived organizational support, and between perceived organizational support and compassion fatigue. Multiple linear regression analysis revealed that the most influential dimension of occupational stressors on compassion fatigue was work-family conflict (β = 0.253, p < 0.001), followed by organizational issues (β = 0.153, p < 0.001), work demands (β = 0.103, p < 0.001) and difficulty taking leave (β = 0.102, p < 0.001). Nurse occupational stressors are positively associated with compassion fatigue and influence nurse compassion fatigue through the mediating effect of perceived organizational support and the moderating mechanism of ego-resilience. Managers can reduce nurses' compassion fatigue levels by reducing occupational stressors, promoting nurses' perceived organizational support, and fostering ego-resilience. This study further integrated the external and internal factors affecting compassion fatigue and constructed a structural equation model of the mechanism of compassion fatigue in frontline nurses, which has implications for the early identification and intervention of compassion fatigue in nurses.

An Optimization Procedure to Convert Time‐Domain Complex Loadings to the Frequency Domain for Low‐Cost Fatigue Analysis

ABSTRACTThe time domain is the most widely chosen alternative in mechanical fatigue tests to completely represent random events. However, the main disadvantages of this approach are the long time required to complete the tests and the high cost of the complex equipment. On the other hand, fatigue test in the frequency domain is a potential alternative to overcome these disadvantages. That is, it requires less sophisticated equipment, because it uses only simple actuators instead of servo actuators. Moreover, the duration of the fatigue test is reduced, because the total length of the event is replaced by constant repetitions and constant damage. The objective of this work is to propose and develop a methodology that uses the results of structural fatigue as a starting point, and through an optimization problem solved by the genetic algorithm, it determines which loads/displacements caused them in the frequency domain. The purpose is to assist future developments in fatigue tests, supplanting tests in the time domain without losing the correlation in results.

How does turbulence intensity affect the fatigue life of composite airfoils based on existing CFD and experimental data?

This research investigates the effect of airflow turbulence intensity on the fatigue life of composite airfoil structures in aerospace engineering. Using advanced Computational Fluid Dynamics (CFD) simulations, this study provides a comprehensive analysis of how varying levels of turbulence intensity—ranging from mild (5%) to severe (30%)—impact the mechanical degradation and fatigue performance of carbon-fiber-reinforced polymers (CFRPs) used in airfoil designs. The research quantifies the relationship between turbulence levels and changes in stress distribution, highlighting critical points of fatigue crack initiation and subsequent propagation. The study includes detailed comparisons of CFD results to experimental data to validate the predictive models and discusses how localized stress fluctuations under high-intensity turbulence accelerate the onset of fatigue failure. We present significant findings that demonstrate a non-linear relationship between turbulence intensity and the reduction in fatigue life, suggesting optimal design modifications for enhanced durability. Furthermore, this paper explores current challenges in merging CFD data with real-world fatigue testing and proposes advanced techniques such as adaptive mesh refinement and hybrid simulation models to improve predictive accuracy and computational efficiency in future research.

Effect of ultrasonic vibration on fatigue life of Inconel 718 machined by high-speed milling: Physics-enhanced machine learning approach

Ultrasonic assisted high-speed machining (UAHSM) can be served as a thermomechanical surface sever plastic deformation (SSPD), because of the high-frequency impact load exerting to the sample together with thermomechanical loads due to shearing and plowing. Despite existing of few works which studied the impact of ultrasonic vibration on fatigue life assessment of difficult-to-cut material by experimental approach, they couldn’t provide an in-depth analysis to identify the underlying mechanisms of fatigue due time-consuming and costly fatigue life tests. Hence, elucidating the role of ultrasonic vibration in UAHSM on variation of fatigue life needs further studies. In order to do so, in the present work, a hybrid predictive approach based using ANFIS-based machine learning model and micromechanical Navaro-Rios (NR) fatigue crack propagation model has been introduced to directly correlates the UAHSM’s parameters to fatigue life. Here the former correlates feed rate, cutting velocity and vibration amplitude as process inputs, to surface integrity aspects (SIA) viz residual stress, roughness and grain size as output. Then, the modeled SIA are correlated to fatigue life using the former. The introduced hybrid model was then verified through series of UAHSM by examining the fatigue lives of milled Inconel 718 using four-point bending fatigue tests. Upon confirmation of the developed model, a comprehensive study was carried out to find how the process factors impact variation of SIA and subsequently fatigue. It was found from the results of developed models and confirmatory experiments that the role of ultrasonic vibration on improved fatigue life is mainly due to inducing compressive residual stress and more refined microstructure than the roughness.

Effects of Basalt Fibers with Different Volume Fractions on the Properties of Concrete

Basalt fiber is the most common inorganic non-metallic material in the field of construction at present, and the bending and cracking resistance is very excellent, has good mechanical and physical properties, is a new kind of green fiber. This paper discusses the effect of different volume content of basalt fiber on the mechanical properties, durability and fatigue properties of concrete, analyzes the research findings of different scholars at home and abroad, and draws corresponding conclusions.

Fatigue Behavior of Polymer Nanocomposites under Low-Strain Cyclic Loading: Insights from Molecular Dynamics Simulation.

Understanding the structural evolution and bond-breaking behavior under cyclic loading is crucial for designing polymer nanocomposites (PNCs) with superior fatigue resistance. Coarse-grained models of PNCs filled with spherical carbon black nanoparticles (NPs) at varying filling fractions of φ were successfully constructed using molecular dynamics simulations. Structural and dynamic simulation results reveal that higher φ leads to increased aggregation of NPs and markedly restricts the relaxation behavior of the polymer matrix. Subsequently, fatigue testing of PNCs was conducted under low-strain cyclic tensile deformation, and the real-time bond-breaking behavior was tracked. The decay behavior of the bond number autocorrelation function was found to be accurately described by the KWW equation, enabling precise determination of the characteristic lifetime τf. With increasing φ, the dominant factor influencing bond-breaking behavior gradually shifts from the polymer network, including entanglements and cross-linking networks, to the filler network. This suggests the presence of a critical filling fraction φc where τf is maximized. For low-strain failure mechanisms, temperature field observations at varying cycles reveal that localized temperature rise emerges as the predominant factor. Furthermore, the mobility of both polymers and NPs increases with cycles. Specifically, the diffusion coefficient of polymer monomers shows a clear power-law relationship with the bond-breaking rate, characterized by . Finally, the stiffness of polymer chains significantly influences the fatigue behavior, evidenced by an initial increase followed by a decrease in the τf with increasing bending energy k. This behavior is attributed to the competitive relationship between high entanglement density at low k and enhanced preorientation at high k. In summary, this study provides a general paradigm for describing failure behavior under cyclic deformation and offers insights into fatigue mechanisms at the molecular level, thereby guiding the development of improved fatigue-resistant PNCs.

The investigation on the bending fatigue properties of Ti-6Al-4V lattice sandwich structures fabricated EB-PBF

In this study, lattice sandwich structures of Ti-6Al-4V alloy with simple cubic (SC) and rhombic dodecahedron (RD) unit cells were prepared by electron beam powder bed fusion (EB-PBF) technique. Through a combination of finite element simulation and experimental investigation, the effect of lattice cell shape and heat treatment on the bending fatigue performance of these lattice sandwich structures was studied. The results show that the underlying fatigue mechanism of the RD lattice sandwich structure is primarily dominated by cyclic ratcheting of the lattice. In contrast, for the SC lattice sandwich structure, the fatigue mechanism involves an interaction of cyclic ratcheting and fatigue crack initiation and propagation of the lattice. During the cyclic deformation process, the struts of the lattice unit cells in the SC lattice sandwich structure mainly undergo buckling deformation. Under the same bending deformation strain, the struts experience much higher stress in the SC lattice sandwich structure, making them more susceptible to crack initiation and resulting in a quick fatigue failure. Therefore, the fatigue performance of the RD lattice sandwich structure is significantly superior to that of the SC lattice sandwich structure. Heat treatment result in the enhanced plasticity of parent materials of the lattice sandwich structure, leading to improved resistance to cyclic strain accumulation during fatigue processes and an increase in fatigue strength.

Mechanical Performance of Laser Powder Bed Fused Ti-6Al-4V: The Influence of Filter Condition and Part Location

Deteriorated filter condition in laser powder bed fusion (L-PBF) systems may negatively impact shield gas flow, causing inadequate spatter particle/plume removal, leading to laser beam attenuation and reduction in melt pool depth, and potentially causing more frequent formation of volumetric defects. This work investigated the effects of filter condition and part location on the micro-/defect-structure and mechanical behavior, including tensile and fatigue, of Ti-6Al-4V parts fabricated by L-PBF. Interestingly, within the manufacturer recommended service intervals, no specific effect of filter condition could be observed on the micro-/defect-structure or the mechanical behavior of the fabricated parts. However, the parts’ defect-structures were affected by their location, with ones located near the center of the build plate having less porosity than the ones located away. Although these defects did not affect the tensile properties, they frequently observed to initiate fatigue cracks; the critical defects sizes were often in the range of a few tens of micrometers. Therefore, their sensitivity to location resulted in the location dependence of the fatigue behavior.

Advanced piezoelectric fluid energy harvesters by monolithic fluid–structure–piezoelectric coupling: A full-scale finite element model

A full-scale finite element model is presented for monolithic fluid–structure interaction (FSI) simulations of thin-walled piezoelectric fluid energy harvesters (PFEHs). Unlike widely used beam/plate-based models, our model employs a solid finite element discretization to precisely represent the complex PFEH designs involving microstructured transducers and non-uniform cantilevers. These features, plus the local FSI effects, are often ignored by simplified models. We applied the Galerkin method to formulate the weak form of the mixed equation system, integrating the flow dynamics, the geometrically nonlinear cantilever, the piezoelectric components, the electrode, and the output circuit within a closed-circuit electro-mechanical coupled system. The coupling of the multiple domains is achieved through boundary-fitted discretization within a monolithic scheme, using shifted-Crank–Nicolson temporal integration. This work explored implementing piezoelectric FSI systems within the FEniCS-based TurtleFSI library, and experimented techniques such as employing penalty functions for achieving electrode components with uniform electric potentials. We investigated various advanced PFEH features, including the baseplate design, the arrangement and microstructure of the piezoelectric components, and their influence on the system's dynamic and energy output behavior. The results confirmed the model's key advantages: full-scale modeling allows the integration of complex base structures and transducer microstructures in PFEH design. Combined with monolithic FSI coupling, it offers greater versatility, supporting a wider range of fluid environments and configurations in both wind and hydropower harvesting. Additionally, the modeling strategy can be intended not only to enhance power output, but also to minimize material usage, reduce mechanical fatigue, and extend the operational lifespan of PFEH systems.

Evaluation of the Mechanical Properties and Fatigue Resistance of the ZrO2CeYAl2O3 Composite

This work aimed to evaluate the fatigue limit of the zirconia ceramic composite stabilized with yttria and ceria reinforced with alumina platelets (ZrO2CeYAl2O3) and characterize the mechanical properties of sintered specimens. Bar-shaped specimens were compacted by uniaxial pressing in a rigid die and sintered at 1500 °C-2 h. Subsequent characterizations included quantitative phase analysis by X-ray diffractometry, determination of density, modulus of elasticity, microhardness, fracture toughness, four-point flexural strength, and fatigue limit. Observations of fracture mechanisms were carried out using confocal and scanning electron microscopy (SEM). The sintered samples presented values above 98% of relative density. Complex microstructures with equiaxed, homogeneously distributed submicrometer grains and planar alumina platelets were observed by SEM. The composite samples showed high values of fracture toughness due to the transformation, during the test, from the tetragonal to monoclinic phase, causing an increase in volume and creating compression zones around the crack, making it difficult to propagate. The average flexural strength reached 445.55 MPa, with a Weibull modulus (m = 16.8), revealing low flexural rupture stress data dispersion. In the composite evaluated in this work, the occurrence of the tetragonal → monoclinic transformation that occurs in the Ce-TZP present at the triple points and grain boundaries during cyclic loading produces “crack tip shielding”, that is, a restricted elastic zone (zone shielding) that surrounds the crack tip. This phenomenon leads to a reduction in the stress intensity factor at the tip of the crack and slows down its growth, generating an increase in the fatigue resistance of the composite.

Comparative Study of High-Cycle Fatigue and Failure Mechanisms in Ultrahigh-Strength CrNiMoWMnV Low-Alloy Steels

This study provides a thorough analysis of the fatigue resistance of two low-alloy ultrahigh-strength steels (UHSSs): Steel A (fully martensitic) and Steel B (martensitic–bainitic). The investigation focused on the fatigue behaviour, damage mechanisms, and failure modes across different microstructures. Fatigue strength was determined through fully reversed tension–compression stress-controlled fatigue tests. Microstructural evolution, fracture surface characteristics, and crack-initiation mechanisms were investigated using laser scanning confocal microscopy and scanning electron microscopy. Microindentation hardness (HIT) tests were conducted to examine the cyclic hardening and softening of the steels. The experimental results revealed that Steel A exhibited superior fatigue resistance compared to Steel B, with fatigue limits of 550 and 500 MPa, respectively. Fracture surface analysis identified non-metallic inclusions (NMIs) comprising the complex MnO-SiO2 as critical sites for crack initiation during cyclic loading in both steels. The HIT results after fatigue indicated significant cyclic softening for Steel A, with HIT values decreasing from 7.7 ± 0.36 to 5.66 ± 0.26 GPa. In contrast, Steel B exhibited slight cyclic hardening, with HIT values increasing from 5.24 ± 0.23 to 5.41 ± 0.31 GPa. Furthermore, the martensitic steel demonstrated superior yield and tensile strengths of 1145 and 1870 MPa, respectively. Analysis of the fatigue behaviour revealed the superior fatigue resistance of martensitic steel. The complex morphology and shape of the NMIs, examined using the 3D microstructure characterisation technique, demonstrated their role as stress concentrators, leading to localised plastic deformation and crack initiation.

Prediction of Rubber Fatigue Life Using an Assimilation‐based Learning Approach and Incremental Crack Propagation Model

ABSTRACTAccurately and efficiently predicting the fatigue life of rubber materials has been a long‐standing challenge due to limited understanding of the fatigue mechanism. In this study, a variational assimilation‐based machine learning method assisted with incremental crack propagation model is proposed to predict the fatigue life of rubber materials. Firstly, according to the fracture mechanics theory, a new rubber fatigue life prediction model based on incremental crack propagation and sparse experimental data is established, which owns higher accuracy than the classical crack energy density model. Further, a rubber fatigue life solver coupled incremental crack propagation model and nonlinear finite element method is introduced to generate a dense fatigue life dataset of rubber materials with high accuracy. Finally, the artificial neural network model is trained, cross‐validated, and tested using the dense dataset, and the three‐dimensional variational assimilation model is employed to merge the predicted values of artificial neural network with experimental data. By comparing against the experimental data, the effectiveness of the proposed method was verified; thereby, we offer an accurate and efficient approach to predict the rubber fatigue life.

Investigation of Fatigue Mechanics and Crack Evolution Characteristics of Jointed Specimens Under Cyclic Uniaxial Compression

ABSTRACTNonpersistent joints are prevalent in engineering rock masses and are sensitive to cyclic loads induced by geological movements and engineering disturbances. Therefore, studying the fatigue mechanisms of rock masses with nonpersistent joints under cyclic compressive loads is crucial for ensuring the rational design and long‐term stability of rock engineering structures. Based on laboratory experiments, this study employed the discrete element method to create specimens with different nonpersistent joints, and uniaxial compressive cyclic loading tests were conducted on these specimens with different maximum cyclic stress levels. The results show that the joint inclination significantly affects the characteristics of jointed rock, such as deformation modulus, irreversible strain, energy evolution, and crack characteristics. Increasing the maximum stress in the stress path results in a rapid release of hysteretic energy in the jointed regions of the rock, which leads to an exponential decrease in fatigue life while an increase in initial irreversible strain, final irreversible strain, and hysteretic energy density. Additionally, the shear fracture zones on both sides of the model expand, and the propagation and merging of cracks between joints become more extensive and complex. The results are significant for studying rock fatigue instability and structure engineering design.

The impact of the filling technique with two sealers in bulk or associated with gutta-percha on the fatigue behavior and failure patterns of endodontically treated teeth.

The present in vitro study aimed to evaluate the fatigue behavior of teeth filled with a calcium silicate-based sealer (Bio-C Sealer, BC) or an epoxy resin-based sealer (AH Plus, AH), in bulk or associated with gutta-percha as main core material. Seventy-two sound human maxillary anterior teeth were initially selected. Sixty of them, were randomly chosen, and had their root canals prepared using nickel-titanium reciprocating instruments, being again randomly assigned to five experimental groups (n = 12): C+ (control + prepared but not filled); BC-B (BC in bulk); BC-GP (BC+ gutta-percha); AP-B (AH in bulk); AP-GP (AH+ gutta-percha). An additional negative control group (C-) was considered (n = 12), consisting only on sound teeth, without preparation and filling. The specimens were submitted to a survival analysis after the cyclic fatigue test. Sound teeth (C-) presented the best fatigue performance (P < 0.05), being similar only to the AP-GP group (P > 0.05). Despite that, all experimental groups showed similar fatigue behavior (P > 0.05) to C+ (BC-B = BC-GP = AP-B = AP-GP = C+). Based on that, it can be seen that the use of gutta-percha, as a main core material, associated with the AH Plus sealer, reestablished the mechanical fatigue performance of endodontically treated teeth comparable to sound teeth, still consisting on the most promising approach to rehabilitate such scenario. Teeth filled in bulk, had discreetly higher risk of premature failures and inferior fatigue performance.

Enhanced performance of flexible BiFeO3 ferroelectric memory with Mica substrate via SrTiO3 buffer layer

BiFeO3 (BFO) application in flexible wearable devices is garnering interest because of its unique ferroelectric and magnetic properties. However, the integration of high-quality BFO films onto flexible substrates presents significant technical challenges. Here, we successfully fabricated high-quality BFO films on mica substrates by using pulsed laser deposition, and report the fatigue characteristics of BFO films on flexible substrates for the first time. The results demonstrated that, after 108 bipolar switching cycles, the polarization only degraded by 0.28%, indicating superior fatigue characteristics compared to previously reported BFO films. Additionally, the device ferroelectric properties remained largely unchanged, with a bending radius of 3.5 mm. The fabricated flexible Pt/BFO/La0.65Sr0.35MnO3(LSMO)/SrTiO3(STO)/mica non-volatile memory devices exhibited mechanical flexibility and fatigue resistance. These findings not only highlight the potential of flexible BFO films for wearable electronic devices and flexible memory devices, they also provide valuable insight for the future development of high-performance flexible ferroelectric materials.

Mechanical Properties and Fatigue Life Evaluation under High Temperature and Shot Peening Application using AA7001

In some applications, AA7001 may be subjected to high temperature and fatigue. This interaction leads to varying the mechanical and fatigue properties of the above alloy. This work deals with the effects of tensile properties and constant fatigue amplitude performance. Aluminum alloys have a low specific strength, are simple to produce, and are lightweight, which has made them popular in the construction, automotive, marine, and aviation industries. The history of stress and temperature applied to the component has a significant impact on the time-dependent process of creep and strain damage. The purpose of this research is to investigate the behavior of AA7001-T6 when two phenomena, high temperatures creep and fatigue, are combined. Compared to the fatigue life interaction employing shot peening thereby, the fatigue lifetimes were The influence of shot peening on the mechanical and fatigue characteristics of AA7001-T6 was investigated utilizing four different temperatures, including RT, SP+RT, 330°C, and SP+330°C. It has been observed The application of 330°C to the tensile process lowered the ultimate tensile strength of UTS and YS by 21.9 % and 22.3 %, respectively. Shot peening improved the aforesaid percentage, lowering it to 19.2 % and 19.7%, respectively. At a stress level of 400MPa, fatigue life was lowered by 18.18 % owing to an increased temperature of 330°C, and this percentage was reduced to 10.16 % due to creating the compressive residual stresses (CRS) (SP). At (RT), the fatigue strength (endurance fatigue limit) was 229 MPa, but after Shot Peening, it improved to 237 MPa. At 330°C, shot peening increased the improved fatigue limit from 217MPa to 229MPa, resulting in a 5.24 % improvement.

Flammability and Mechanical Testing of Sandwich Composite for Rolling Stock Structural Applications

Components made of composite materials are being increasingly used in the construction of rolling stock. Currently, the use of components made of composite materials as train structural elements is increasingly being considered. Non-structural components made of composites are most often found inside rail vehicles (e.g., the interior lining), while structural components made of sandwich composite materials can be used for the roof, sidewalls, and underframe constructions. This article provides a description of an innovative sandwich composite developed for a metro’s underframe, as well as the production process and preparation of the composite specimens. The main parts of the work are flammability and mechanical (static and fatigue) tests of the innovative sandwich composite. The scope of the flammability tests included the testing of the fire properties using the radial plate method, the optical density of smoke, and the content of toxic gases. The mechanical strength of the sandwich composite was examined during a flexural (three-point bending) test and a fatigue strength under a given dynamic load. The results presented in the article are very significant, both in terms of flammability and the mechanical strength tests. In order to produce large-size train components, appropriately large patches of component layers of the composite are required; this may pose production problems.

Optimizing energy density in dielectric elastomer generators: a reliability-dependent metric

Abstract Dielectric elastomer generators (DEGs) are soft transducers capable of converting mechanical energy into electrostatic energy. Increasing the mechanical stretch amplitude and the electric field imposed to the DEG leads to higher energy conversion at the cost of a reduced lifetime. Here, mechanical fatigue and electrical degradation were assessed on a silicone-based DEG, and the outcome was used to build an electro-mechanical reliability model. A novel metric, termed levelized energy density, has been introduced to carefully balance the conflicting objectives of high energy output and long-term reliability. Through a multi-dimensional anaylsis of this index, the optimal operating parameters (stretch amplitude and electric field) that maximize energy conversion can be derived. Energy densities reported in literature are generally obtained after pushing the DEG close to their intrinsic limits for a limited number of cycles. In our approach, more realistic values in the endurance domain are presented, which typically leads to a 9-fold decrease in energy density for a design life of 1 million cycles. This article not only addresses the challenge of optimizing DEG performance but also emphasizes the importance of considering realistic operational conditions to enhance reliability, ultimately contributing to the practical and sustainable deployment of these soft transducers in various applications.

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.