Local Strain Research Articles

Local and global mechanical properties of orbital friction stir welding on API X65 PSL2 steel / Inconel 625 clad pipes

Orbital friction stir welding (FSW) is a promising approach to joining clad pipes. In this work, the influence of individual process parameters on the material flow even as, mechanical properties in orbital friction stir welded clad pipes is investigated. Due to the local heterogeneous microstructures within the weld, joints were evaluated by optical and scanning electron microscopy (SEM), microhardness, and digital image correlation (DIC). A microhardness increase was observed, with a maximum of 380 HV0.5 within the Inconel 625 and 265 HV0.5 within the X65 steel stir zones. Sound joints had an average ultimate tensile strength (UTS) exceeding up to 13% of the calculated theoretical tensile strength, which is obtained considering the minimum tensile strength of both materials. Additionally, failure occurred in the base material during the tensile testing, where the local strain in the stir zones of the X65 steel and Inconel 625 were only 3.3% and 10%, respectively. In summary, this investigation shows friction stir welded joints of API X65 steel and Inconel 625 clad pipes with high mechanical properties.

Neural network-based recognition of multiple nanobubbles in graphene

We present a machine learning method for swiftly identifying nanobubbles in graphene, crucial for understanding electronic transport in graphene-based devices. Nanobubbles cause local strain, impacting graphene's transport properties. Traditional techniques like optical imaging are slow and limited for characterizing multiple nanobubbles. Our approach uses neural networks to analyze graphene's density of states, enabling rapid detection and characterization of nanobubbles from electronic transport data. This method swiftly enumerates nanobubbles and surpasses conventional imaging methods in efficiency and speed. It enhances quality assessment and optimization of graphene nanodevices, marking a significant advance in condensed matter physics and materials science. Our technique offers an efficient solution for probing the interplay between nanoscale features and electronic properties in two-dimensional materials.

Damage Detection and Localization Methodology Based on Strain Measurements and Finite Element Analysis: Structural Health Monitoring in the Context of Industry 4.0

This paper investigates the integration of Structural Health Monitoring (SHM) within the frame of Industry 4.0 (I4.0) technologies, highlighting the potential for intelligent infrastructure management through the utilization of big data analytics, machine learning (ML), and the Internet of Things (IoT). This study presents a success case focused on a novel SHM methodology for detecting and locating damages in metallic aircraft structures, employing dimensional reduction techniques such as Principal Component Analysis (PCA). By analyzing strain data collected from a network of sensors and comparing it to a baseline pristine condition, the methodology aims to identify subtle changes in local strain distribution indicative of damage. Through extensive Finite Element Analysis (FEA) simulations and a PCA contribution analysis, the research explores the influence of various factors on damage detection, including sensor placement, noise levels, and damage size and type. The findings demonstrate the effectiveness of the proposed methodology in detecting cracks and holes as small as 2 mm in length, showcasing the potential for early damage identification and targeted interventions in diverse sectors such as aerospace, civil engineering, and manufacturing. Ultimately, this paper underscores the synergistic relationship between SHM and I4.0, paving the way for a future of intelligent, resilient, and sustainable infrastructure.

Oligo-cyclic loading-induced evolution of stress distribution and apparent amorphous modulus in lamellar stacks of high-density polyethylene

Assessing the resistance of high-density polyethylene (HDPE) against earthquake-like loads involves understanding the changes in structure and properties induced by oligo-cyclic loading at various length scales. To study the evolution of stress distribution and intrinsic properties within lamellar stacks from pristine to oligo-cyclic loading pre-conditioned materials, simultaneous in-situ SAXS/WAXS measurements were performed. During the elastic deformation of each pristine and preconditioned sample, crystal strain was tracked using the in-situ WAXS technique. Based on the established elastic tensor of the crystalline structure in polyethylene, we calculated the microscopic stress values within crystalline lamellae. In the pristine sample, lamellar stacks exhibit closely series-like coupling in the equatorial region and parallel-like coupling in the polar region of the spherulite. In the pre-conditioned sample, stress is primarily concentrated in the intra-fibrillar region, where the crystalline and amorphous phases are series-coupled, and strong strain concentration occurs in the inter-fibrillar region. By combining the local strain in the amorphous layer within the lamellar stacks in the equatorial region of the spherulite and the intra-fibrillar region with series-coupled lamellar stacks, measured by in-situ SAXS tests, the apparent amorphous modulus at the lamellar stack scale can be determined. This modulus changes from 71 to 106 MPa in the equatorial region of pristine spherulites to a notable 2000–7000 MPa in the intra-fibrillar region under the influence of oligo-cyclic pre-loading. Importantly, this apparent modulus is affected by both crystallization conditions and molecular structure, with molecular parameters exerting the primary influence.

Microstructural strain localisation phenomena in fibre-reinforced polymer composites: Insights from nanoscale digital image correlation and finite element modelling

Multiscale models for fibre-reinforced polymer composites currently lack experimentally validated microscale damage descriptors as input parameters. This work demonstrates the occurrence of strain localisation phenomena at the fibre/matrix level using nanoscale digital image correlation. Unidirectional carbon-fibre reinforced epoxy and glass-fibre reinforced PMMA composites were loaded in transverse compression in a scanning electron microscope. Radial and shear strain maps were extracted and compared with finite element simulations based on a conventional elastoplastic model. Near the interface, an interphase layer is present in the matrix, presumably due to locally different polymerisation conditions. A skin-core structure was found in carbon fibres, corresponding to an increased transverse modulus towards the interface.

Strain localisation and grain boundary-mediated deformation in pure titanium at low and high temperatures: In-situ optical microscopy and digital image correlation

Heterogeneous deformation occurs between grains in polycrystalline α-titanium. Understanding the role of temperature in local deformation is essential for its applications in extreme environments such as cryo- or high-temperature, but the underlying mechanism still remains elusive. Here we report a study of grain-scale deformation behaviour in CP-Ti plate at the temperature range from −60 °C to 280 °C. The full-field strain measurements were conducted on the tensile samples loaded parallel (RD) and transverse (TD) to the rolling direction, using in-situ optical microscopy and digital image correlation (OM-DIC). The DIC local strain maps were coupled with scanning electron microscopy and electron backscatter diffraction analysis. The grain boundary sliding and slip transfer occurred depending on the geometric relationship (i.e., deformation compatibility) between adjacent grains at 20 °C, and a micro-crack was observed at the {101‾1} twist boundary. The strain was recovered in the grains in the RD sample favourable for slip, whilst more accumulated in the grains in TD sample unfavourable for slip at 280 °C. The plasticity of grains differs with decreasing temperature to −40 °C, resulting in the presence of soft/hard grain pairs. The strong strain localisation between the soft and hard grains led to the cracking along the GBs (RD) and cross the grains (TD). Interestingly, the cracking was significantly reduced with decreasing temperature to −60 °C due probably to the temperature dependence of the plasticity of grains. The strain-hardening behaviour of α-Ti polycrystals was significantly affected by the temperature and crystal orientation dependence of grain-scale deformation mechanism.

Local Health Equity Action Teams (LHEATS) as a Novel and Emerging Practice of the Communities Organizing to Promote Equity (COPE) Project in Kansas.

The Communities Organizing to Promote Equity (COPE) Project was implemented in 20 counties across Kansas to build capacity to address health equity by forming local health equity action teams (LHEATS), hiring and training community health workers, facilitating state-wide learning collaboratives, and tailoring communication strategies. We conducted interviews and focus groups with project stakeholders who identified pragmatic recommendations related to LHEAT formation and leadership, establishing trust, nurturing autonomy, and optimizing impact. Insights can improve future community-based health equity efforts. (Am J Public Health. 2024;114(S7):S570-S574. https://doi.org/10.2105/AJPH.2024.307802).

Multiferroicity in plastically deformed SrTiO3

Quantum materials have a fascinating tendency to manifest novel and unexpected electronic states upon proper manipulation. Ideally, such manipulation should induce strong and irreversible changes and lead to new relevant length scales. Plastic deformation introduces large numbers of dislocations into a material, which can organize into extended structures and give rise to qualitatively new physics as a result of the huge localized strains. However, this approach is largely unexplored in the context of quantum materials, which are traditionally grown to be as pristine and clean as possible. Here we show that plastic deformation induces robust magnetism in the quantum paraelectric SrTiO3, a property that is completely absent in the pristine material. We combine scanning magnetic measurements and near-field optical microscopy to find that the magnetic order is localized along dislocation walls and coexists with ferroelectric order along the walls. The magnetic signals can be switched on and off via external stress and altered by external electric fields, which demonstrates that plastically deformed SrTiO3 is a quantum multiferroic. These results establish plastic deformation as a versatile knob for the manipulation of the electronic properties of quantum materials.

Precise Image-level Localization of Intracranial Hemorrhage on Head CT Scans with Deep Learning Models Trained on Study-level Labels.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop a highly generalizable weakly supervised model to automatically detect and localize image- level intracranial hemorrhage (ICH) using study-level labels. Materials and Methods In this retrospective study, the proposed model was pretrained on the image-level RSNA dataset and fine-tuned on a local dataset using attention-based bidirectional long-short-term memory networks. This local training dataset included 10,699 noncontrast head CT scans from 7469 patients with ICH study-level labels extracted from radiology reports. Model performance was compared with that of two senior neuroradiologists on 100 random test scans using the McNemar test, and its generalizability was evaluated on an external independent dataset. Results The model achieved a positive predictive value (PPV) of 85.7% (95% CI: [84.0%, 87.4%]) and an AUC of 0.96 (95% CI: [0.96, 0.97]) on the held-out local test set (n = 7243, 3721 female) and 89.3% (95% CI: [87.8%, 90.7%]) and 0.96 (95% CI: [0.96, 0.97]), respectively, on the external test set (n = 491, 178 female). For 100 randomly selected samples, the model achieved performance on par with two neuroradiologists, but with a significantly faster (P < .05) diagnostic time of 5.04 seconds per scan (versus 86 seconds and 22.2 seconds for the two neuroradiologists, respectively). The model's attention weights and heatmaps visually aligned with neuroradiologists' interpretations. Conclusion The proposed model demonstrated high generalizability and high PPVs, offering a valuable tool for expedited ICH detection and prioritization while reducing false-positive interruptions in radiologists' workflows. ©RSNA, 2024.

Dynamic mechanical properties of sandstone with two circular inclusions under impact loading

Inclusions are often present in rock defects, which can compensate for some of the problems of low rock strength and poor stability caused by hole defects. Specimens containing inclusions exhibit different mechanical properties under dynamic loading, and the strength change, energy evolution law and fracture mechanism deserve to be clearly discussed. In this work, a dynamic impact test of sandstone with circular inclusions was carried out. The failure process of each sample was recorded by a high-speed camera, and the influences of the inclusion strength and strain rate on the dynamic impact performance of the sandstone were analysed. Increasing the strain rate and inclusion strength can significantly improve the dynamic compressive strength of a sample. The dissipated energy density and impact toughness index are positively correlated with the strain rate. The dissipated energy density increased the most when the sample type was FA, at 10.6%. When the sample type was FD, the impact toughness index increased the most, which was 49.1%. In the early stage of loading, the localized strain is mainly concentrated inside the filler and gradually evolves into deformation of the filler and extension of shear cracks in the late stage of loading. The failure modes of a sample are not the result of a single factor but are influenced by both the strain rate and the filler. The types of cracks in the samples are mainly shear cracks and shear–tension composite cracks.

Studying the effect of Cr content on microstructure and deformation behavior of (NiCo)88-xCrxAl10Ta2 medium-entropy alloy through L-DED gradient material

Optimization of Cr content is crucial for γ'-strengthened NiCoCr-based medium entropy alloys, influencing the stacking fault energy, deformation behavior and the precipitation of brittle σ phase. In this study, (NiCo)88-xCrxAl10Ta2 gradient materials were prepared by L-DED, and the influence of Cr content on the phase precipitation and tensile deformation behavior was investigated. As the Cr content decreases from 24.1 at% to 13.9 at%, the aging time for σ phase precipitation at the grain boundaries at 750°C increases from 100 hours to 215 hours. Meanwhile, the coarsening rate of γ' phase at 750°C are found to be 7.84×10−28 m3/s and 13.6×10−28 m3/s for the Cr content of 24.1 at% and 18.7 at%, respectively. It suggests that the reduction in Cr content notably suppresses the precipitation of σ phase, and accelerates the coarsening rate of γ' phase. Tensile testing of the gradient material reveals that the lower Cr content region exhibits fewer and shorter stacking faults during tensile deformation due to its higher stacking fault energy, leading to the rapid development of local strain, subsequent necking, and eventual fracture. Taking into account the evolution of microstructure, hardness, and deformation substructure with varying Cr content, the appropriate Cr content in (NiCo)88-xCrxAl10Ta2 medium entropy alloy is 17–24 at%.

Two-dimensional speckle tracking echocardiography and stress computed tomography myocardial perfusion: potential for early imaging of asymptomatic patients with myocardial bridges

Aim. To evaluate the effectiveness of left ventricular (LV) peak global longitudinal strain and potential of computed tomography myocardial perfusion (CT perfusion) for the early diagnosis of asymptomatic patients with myocardial bridges (MBs).Material and methods. Forty patients were examined (20 with asymptomatic MBs in the area of the left anterior descending (LAD) artery and 20 without MBs) at the S. M. Kirov Military Medical Academy in the period from 2021 to 2023. The patients were divided into 2 equal groups consisting of 20 people (10 with MBs — the main group; 10 without MBs — the comparison group), one of which underwent speckle tracking echocardiography (STE), and the other — stress CT perfusion performed (adenosine triphosphate 160 mg/kg). The results were assessed in accordance with the 17-segment classification of LV proposed by the American Heart Association (2002).Results. When performing STE, 5 (50%) patients with MBs showed a decrease in LV local strain in the segments, the blood supply of which comes from the LAD artery and its branches, while in the comparison group — 1 (10%) (x2=5; p=0,025). When assessing the global longitudinal peak strain (GLPS), a significant difference was revealed among the study groups, amounting to -20,9±1,5% in patients with MBs and -22,1±0,9% in those without MBs (p=0,04). Using ROC analysis, the effectiveness of GLPS in prediction of asymptomatic MBs was calculated as follows: AUC=0,93 (95% confidence interval: 0,819-1,0; p=0,001), the cut-off point — -20,55% (sensitivity 80%, specificity 100%). According to CT perfusion data, impaired myocardial blood supply in the group of asymptomatic patients with MBs was noted in 6 (60%) cases, and in the comparison group — 2 (20%) (x2=9,8; p=0,002).Conclusion. Imaging of initial LV changes according to two-dimensional STE and detection of coronary circulatory disorders according to CT myocardial perfusion in asymptomatic patients with MBs makes it possible to timely suspect intramyocardial course of the coronary artery, as well as to consider further management tactics and carry out early prevention of possible cardiovascular events.

Building sustainable local training capacity for maternal and newborn health within the public health system: A training intervention in Palghar District, India

Continuing professional development for the health workforce is of paramount importance and can be implemented using locally available, competent trainers. However, guidelines for the selection, development, and mentorship of such trainers are lacking. Training intervention research conducted in Western Maharashtra, India, aimed to address these gaps by focusing on skills for maternal and newborn health (MNH). In this study, selected trainers from a pilot project in the Pune district received advanced training to become core trainers (CTs) for a scale-up project in Palghar district (2019 &amp;ndash; 2022). The CTs trained master trainers (MTs) in Palghar (n = 32) with support from the United Kingdom-based technical partners, following a six-step approach: selection of trainers, training of trainers (ToT) (including knowledge and skills assessment), staggered induction as trainers, continuous support, regular quality assessment, and virtual refresher training. The process and outcomes of this six-step approach were evaluated using mixed-methods research. The skills of local trainers were augmented through hands-on training and further supported by long-term mentorship to develop training excellence. The CTs&amp;rsquo; competency as mentors improved due to appreciative feedback. Regular assessments conducted by the expert team also contributed to maintaining quality control. Online learning has emerged as an effective method for refresher training. There was considerable improvement in the clinical knowledge and skills of the health providers from Palghar (n = 505), which attests to the quality of the training delivered by the Palghar MTs. This intervention enhanced both clinical competency and confidence. The approach demonstrated the importance of recruiting suitable participants who could consciously shift their teaching style to become more adult-learner-centric facilitators. However, there is a need for a systematic, long-term evaluation of this model, its application to MNH care, and its institutionalization within the public health system.

Hydrogen-enhanced microbanding in an austenitic FeMnAlC low-density steel: Effect on hydrogen embrittlement resistance

We have investigated the influence of 101 mass ppm hydrogen content on the room temperature deformation structure and mechanical behavior of an austenitic Fe30Mn6.5Al0.3C (wt.%) low-density steel by several electron microscopy techniques, such as electron channeling contrast imaging (ECCI), electron backscatter diffraction (EBSD), and scanning transmission electron microscopy (STEM). The steel exhibits a high hydrogen embrittlement resistance associated with a moderated increase in strength (yield stress increase of 10%) and ductility (increase in the elongation to fracture of ∼ 8%). Analysis of the deformation structure reveals that hydrogen influences the deformation behavior by promoting deformation mechanisms associated with inhomogeneous plasticity (hydrogen-enhanced deformation banding (HEDB)) and strain localization (hydrogen-enhanced microbanding (HEMB)). These deformation mechanisms are ascribed to hydrogen-induced effects on dislocation plasticity, resulting in macroscopic kink bands, sub-micron localized strain gradients, and localized shear at cell blocks. We find that HEMB plays a relevant role in the deformation behavior of sub-micron localized strain gradients by promoting plastic relaxation and the enhanced storage of geometrically necessary dislocations within them. These effects mitigate the activation of damage mechanisms and enhance the strain-hardening capacity, contributing to the high HE resistance of the steel, comparable to that of high HE-resistant fcc alloys and steels.

Aging behavior, microstructure and mechanical properties of Al-Cu-Mg alloy matrix composites reinforced with carbon nanotubes

High-strength Al-Cu-Mg alloys are good matrix candidates for fabricating strong and tough Al matrix composites reinforced with carbon nanotubes (CNTs). In this study, an element mechanical alloying method was used to achieve homogeneous CNT dispersion in hard Al-Cu-Mg matrix. A comprehensive transmission electron microscopy study was applied on peak-aged CNTs/Al-Cu-Mg composites and referential Al-Cu-Mg alloy. It was found that the ex-situ CNTs increased the dislocation density and hindered the recrystallization of the Al-Cu-Mg matrix. Thus, larger local stress and strain were detected in CNTs/Al-Cu-Mg composites. The precipitation in CNTs/Al-Cu-Mg composites was accelerated, which brought extra 12 % improvement to tensile yield strength of the composite. The distribution of precipitates in CNTs/Al-Cu-Mg composites were nonuniform due to the element mechanical alloying process, which was probably beneficial to the high ductility of the CNTs/Al-Cu-Mg composite. With the synergetic strengthening effect of CNTs and fine precipitates, CNTs/Al-Cu-Mg composites exhibited well-balanced strength and ductility.

Stretch-steering of highly aligned discontinuous fiber tape with automated fiber placement

Highly aligned discontinuous fiber (ADF) composites have been developed with mechanical properties comparable to continuous fiber composites. These materials can be stretched in the fiber direction during processing enabling the production of complex geometries. This study utilizes 57% fiber volume fraction ADF tape comprised of a thermoplastic Polyetherimide (PEI) matrix with 3 mm long IM7 carbon fibers. The Laser-Assisted Automated Fiber Placement (LA-AFP) process is used to study the limits of stretch-steering of ADF tape at small radii. An experimental technique based on photogrammetry was developed to quantify the effect of stretch parameters on the tape strain fields and path placement accuracy. The measurements captured the local in-plane strain tensor (longitudinal, transverse, and shear) across the width and along the length of steered tapes. The results demonstrate that placement path accuracy can be achieved when the tool center point (center of rotation) of the AFP head is located at the nip-point versus the roller centerline, which is typically used for steering continuous fiber tapes at large steering radii. Accuracy of the in-situ tape stretching was demonstrated up to 60% applied stretch strain. The measurements also confirm that when stretch-steering ADF tape, the resulting strain across the tape width is on average the superposition of the in-situ applied tensile strain and in-plane bending computed from the tape width and steering radius. A statistical-based methodology is presented to select the average tensile stretch levels to minimize the probability of defects forming during steering on the inner radius of the tape. The experiments show that a 12.5 mm wide tape can be accurately placed on a 50 mm radius of curvature without defects. This represents a two order of magnitude improvement in steerability over continuous fiber tapes of the same tape width found in peer-reviewed literature.

Generalized Federated Learning via Gradient Norm-Aware Minimization and Control Variables

Federated Learning (FL) is a promising distributed machine learning framework that emphasizes privacy protection. However, inconsistencies between local optimization objectives and the global objective, commonly referred to as client drift, primarily arise due to non-independently and identically distributed (Non-IID) data, multiple local training steps, and partial client participation in training. The majority of current research tackling this challenge is mainly based on the empirical risk minimization (ERM) principle, while giving little consideration to the connection between the global loss landscape and generalization capability. This study proposes FedGAM, an innovative FL algorithm that incorporates Gradient Norm-Aware Minimization (GAM) to efficiently search for a local flat landscape. FedGAM specifically modifies the client model training objective to simultaneously minimize the loss value and first-order flatness, thereby seeking flat minima. To directly smooth the global flatness, we propose the more significant FedGAM-CV, which employs control variables to correct local updates, guiding each client to train models in a globally flat direction. Experiments on three datasets (CIFAR-10, MNIST, and FashionMNIST) demonstrate that our proposed algorithms outperform existing FL baselines, effectively finding flat minima and addressing the client drift problem.

Degradation of lubricating molecules in synovial fluid alters chondrocyte sensitivity to shear strain.

Articular joints facilitate motion and transfer loads to underlying bone through a combination of cartilage tissue and synovial fluid, which together generate a low-friction contact surface. Traumatic injury delivered to cartilage and the surrounding joint capsule causes secretion of proinflammatory cytokines by chondrocytes and the synovium, triggering cartilage matrix breakdown and impairing the ability of synovial fluid to lubricate the joint. Once these inflammatory processes become chronic, posttraumatic osteoarthritis (PTOA) development begins. However, the exact mechanism by which negative alterations to synovial fluid leads to PTOA pathogenesis is not fully understood. We hypothesize that removing the lubricating macromolecules from synovial fluid alters the relationship between mechanical loads and subsequent chondrocyte behavior in injured cartilage. To test this hypothesis, we utilized an ex vivo model of PTOA that involves subjecting cartilage explants to a single rapid impact followed by continuous articulation within a lubricating bath of either healthy synovial fluid, phosphate-buffered saline (PBS), synovial fluid treated with hyaluronidase, or synovial fluid treated with trypsin. These treatments degrade the main macromolecules attributed with providing synovial fluid with its lubricating properties; hyaluronic acid and lubricin. Explants were then bisected and fluorescently stained to assess global and depth-dependent cell death, caspase activity, and mitochondrial depolarization. Explants were tested via confocal elastography to determine the local shear strain profile generated in each lubricant. These results show that degrading hyaluronic acid or lubricin in synovial fluid significantly increases middle zone chondrocyte damage and shear strain loading magnitudes, while also altering chondrocyte sensitivity to loading.

A personalized federated meta-learning method for intelligent and privacy-preserving fault diagnosis

Intelligent fault diagnosis methods have made significant progress during the past decade, often following a centralized training paradigm that gathers data from multiple industrial users, which results in high acquisition costs and raise data privacy concerns. Federated Learning (FL) provides a promising solution to intrinsically protect data privacy by jointly training a shared global model without sharing individual data, but the varying data distributions among clients pose challenges for diagnostic performance. To address these problems, a novel FL framework called federated meta-learning based on fine-grained classifier reconstruction (FedFGCR) is presented in this paper. First, an adaptive interpolation strategy based on meta-learning is designed to compute the optimal combination of global and local feature extractors as the initialization of the local training. Additionally, we introduce a new regularization term that allows the local model to leverage global data, enhancing model generalization by incorporating global semantic feature information. Furthermore, a fine-grained classifier reconstruction method is proposed to improve the personalized diagnosis ability for local samples. Comparative experiments with mainstream FL-based fault diagnosis methods have been conducted, demonstrating FedFGCR’s superiority with accuracy gains ranging from 0.96% to 5.41% on the CWRU dataset and from 5.01% to 9.95% on the KAIST dataset.

Evaluation of the fatigue life of AISI 347 specimens with small notches based on local strain considerations

The use of materials data for cyclic loading determined on unnotched specimens to predict the fatigue life of notched components has a long tradition, specifically when it comes to nuclear engineering. The basic principle is that the material behaviour of the unnotched specimens can be transferred to what the material is exposed to be in a notch root. This principle has been proven for large notches. However, what happens when the notch is relatively small? Can the fatigue life still be predicted on the grounds of what has been considered as the local strain or Neuber approach? A key reference in that regard is the Neuber equation or generally the load versus notch stress, notch strain – or any combination of those – relationship. In a larger study, unnotched and notched specimens from the metastable austenitic steel AISI 347 have been tested and characterized providing a database that may give some answers to the question raised above.The unnotched specimens considered here had a cross-section diameter of 10 mm while the notch radii of the notched components were only 0.5 and 0.35 mm, respectively. Notch radii of such dimensions will easily reach a fully plastic condition once the material has exceeded the yield limit, because the difference in load between yield start in the notch and full plastification is relatively small. This fully plastic state exceeds the validity of the Neuber equation and requires respective corrections. In this paper it is shown how such corrections can be obtained through a finite element analysis and how this applies to the cases mentioned above.