Browse Topic: Fatigue
To address the detection and monitoring needs of fatigue damage in ferromagnetic materials, this paper proposes a nondestructive testing method based on the evolution of magnetic hysteresis characteristics. By constructing a hysteresis loop measurement system, the variation patterns of coercivity (Hc) in Q235 steel specimens under cyclic loading were investigated, revealing three-phase characteristics of fatigue damage: the initial linear growth phase (N ≤ 8,000), the rapid rise phase (8,000 < N ≤ 12,000), and the stable oscillation phase (N > 12,000). Experimental results demonstrate that the relationship between coercivity and damage degree (D) can effectively characterize the processes of crack initiation, propagation, and instability, with significant inflection points observed at D = 0.6 and D = 0.8. The quantitative model based on coercivity provides a novel method for early warning and condition assessment of fatigue damage, offering advantages such as non-contact operation and high sensitivity. This study provides theoretical foundations and technical support for the health monitoring of engineering structures.
Qualification of new aerospace alloys requires extensive mechanical testing to capture anisotropy and ensure reliable performance under complex loading conditions. This process is costly and time-consuming, particularly with emerging manufacturing routes such as additive manufacturing. Advanced yield surface prediction offers a route to reduce test campaigns by linking microstructural features to macroscopic constitutive models. In this work, Digimat is employed as a multi-scale material modeling platform to generate yield surfaces of polycrystalline metals using computational homogenization. Representative volume elements (RVEs) are constructed from experimental texture and grain morphology data, and their response under multiaxial loading is simulated using a crystal plasticity framework. The computed yield loci are then fitted with phenomenological functions (e.g. Yld2000-2D), enabling calibration of anisotropic yield models from virtual testing. As a case study, an AA6016-T4 sheet with strong cube texture is modeled and validated against experimental data, including yield stresses and Lankford coefficients in multiple directions. The predictive capability of the approach is further assessed through a cup drawing simulation in Simufact, where earing behavior is accurately reproduced. These results demonstrate that digital yield surface prediction can capture anisotropic plasticity and provide reliable input to forming simulations while significantly reducing experimental requirements. This capability lays the foundation for more efficient alloy qualification, with direct impact on fatigue and damage tolerance modeling in aerospace applications.
This paper presents a high-fidelity fatigue damage modeling framework for composite structures with ply drops, incorporating several key advancements to capture localized fatigue behavior. The approach includes: (1) computation of local stress ratios at each fatigue cycle; (2) an R-ratio-dependent fatigue damage accumulation model; (3) implementation of a constant load diagram to construct S–N curves at arbitrary R-ratios; and (4) a cycle-jumping technique to account for the evolving rate of fatigue damage accumulation due to progressive stiffness redistribution. A combined experimental and numerical study was conducted on tapered composite beams subjected to mixed axial tension and vertical bending. A custom-designed fatigue test fixture was developed to capture displacement at the loading end, which was then used as a boundary condition in the fatigue life prediction model. To guide the selection of fatigue test peak loads, static failure analyses were first performed on representative tapered beams under constant axial tension and monotonic bending. Subsequent fatigue tests, conducted under constant axial tension and cyclic bending at two peak load levels, showed strong agreement between predicted and measured load–deflection responses, fatigue lives, and failure patterns, thereby demonstrating the accuracy and robustness of the developed framework.
Rolling-element bearings in rotorcraft dynamic systems are critical components susceptible to rolling contact fatigue (RCF), a dominant degradation mechanism manifesting through subsurface-initiated spalling, surface micropitting, and fatigue fractures. Robust inspection strategies compliant with EASA and FAA requirements are therefore essential. Traditional methods are often invasive, requiring disassembly, and are susceptible to human-factor errors. Smart Duplex introduces a design-for-monitoring architecture integrating in-situ videoscopic and coherence scanning interferometry (CSI) for high-resolution 3D surface mapping, including under partial grease coverage. This paper details a repeatability and reproducibility (R&R) framework ensuring metric consistency; a maintainability assessment projecting significant man-hour reductions and high availability; certification rationale emphasizing airworthiness improvements via enhanced detectability, workload reduction, and digitized inspection records; and an airworthiness mapping supporting threat assessments, Airworthiness Limitations Section (ALS) entries, and usage-based maintenance credits. By embedding sensing capability and digitizing inspection records, Smart Duplex minimizes downtime, mitigates human-factor errors, and facilitates predictive maintenance, optimizing cost, enhancing performance, and ultimately improving safety.
This work presents the development and application of a methodology for predicting fatigue life, implemented within the modern progressive failure analysis software tool CDMat, developed at the Advanced Materials and Structures Laboratory of the University of Texas at Arlington. CDMat is designed as an extension to the general-purpose finite element analysis program ABAQUS/Explicit. The set of user-defined subroutines for describing material behavior can be expanded by adding new subroutines. A recent development in CDMat is a computational model capable of predicting delamination crack growth under quasi-static and fatigue loading, based on a fracture mechanics approach using the J-integral. The J-integral is calculated by integrating stresses and displacements along a line defined by the negative gradient of displacements in the cohesive interface. Due to the large integration path, the J-integral allows for a highly accurate estimation of the energy release rate, which makes it possible to reasonably estimate the crack growth rate using Paris's law. A comprehensive verification of the J-integral-based fatigue prediction methodology was performed using a tapered structural element with internal ply drops. Experimental determination of the static and fatigue properties of the materials, static and fatigue tests of a tapered structural element, and numerical simulation of fatigue crack growth were performed. The predicted fatigue crack growth showed good agreement with experimental results.
Traditional safe-life methodologies for rotorcraft structural components rely on deterministic safety factors to account for uncertainty in loads, material properties, and operational usage. While effective for ensuring safety, these approaches lead to early retirement lives and reduced aircraft availability. This paper presents an updated digital twin-based probabilistic framework for rotorcraft component fatigue life assessment that integrates a probabilistic stress–life (S-N) material model, machine learning-based load estimation from flight data, and Monte Carlo uncertainty propagation. The approach is demonstrated for a critical location on the CH-146 Griffon main rotor yoke. Compared with earlier work, the present study advances the framework through independent validation of the load-estimation model and application to available in-service flight data from multiple mission categories. A probabilistic sensitivity analysis is used to examine the separate and combined effects of material variability and load-estimation uncertainty on fatigue life, cumulative probability of failure, and hazard rate. For the CH-146 demonstration case, the results indicate that the material fatigue strength uncertainty has a major impact on the lower tail of the life distribution and the corresponding reliability-based life, whereas load-estimation accuracy uncertainty has a secondary influence on risk metrics. The application of the digital twin framework to operational, search and rescue, and training mission data further shows that mission-specific usage variability plays an important role in the evolution of fatigue damage accumulation and structural risk. Overall, the proposed framework provides a more informative basis for risk-based rotorcraft life assessment by explicitly quantifying uncertainty and incorporating aircraft-specific operational data. The study is intended as a step toward validation of the framework rather than a completed operational deployment.
This work evaluates the long-term fatigue life and structural compatibility of integrated optical fiber sensors (OFS) within an H145 (or BK117 D-3) helicopter flexbeam. Utilizing fiber Bragg grating (FBG) arrays, the study compares different deployment techniques under a 100,000-cycle fatigue test: embedded, surface-integrated, and surface-applied. A validated three-dimensional (3D) finite element model (FEM) was developed to reconstruct cross-sectional loads and correlate experimental strain data. Validation against conventional electrical strain gauges (SG) confirms that embedded FBGs significantly outperform SGs in durability, maintaining functionality beyond the operational limit of traditional sensors. Furthermore, the methodology successfully tracks global stiffness evolution and degradation throughout the fatigue life. Micro-computed tomography (µCT) scans verify that the integrated fibers do not compromise structural integrity. These findings demonstrate the potential of embedded OFS for continuous, in-service load monitoring and condition-based maintenance (CBM) of flight-critical rotorcraft components.
This presentation focuses on evaluating the fatigue life of the TAV-8B aircraft using a more realistic, data-driven structural assessment approach. Flight-by-flight data recorded from individual TAV-8B aircraft were then combined with the regression models and FEA-based load-to-stress transfer functions to generate aircraft-specific stress spectra and fatigue damage predictions using the CI89 fatigue analysis program. The results showed a 95% probability that the aircraft would exceed the projected SLAP fatigue life of 9,500 flight hours.
Due to the spot weld and mechanical fastener share the similar characteristics to join sheets together with differences in deformation behavior around joint region, a novel spot joint element (user-defined element) consists of regular Mindlin shell elements and equations for different kinematic constraints is proposed to simplify the spot joint representation in lightweight automotive structures. The novel spot joint element can not only provide accurate deformation behavior around joint region but also output mesh-insensitive structural stresses at virtual nodes with the use of traction-based structural stress method for fatigue failure analysis. In this investigation, the structural stress distributions around joint circumference in the lap-shear specimens with spot weld or fastener are first calculated to validate the accuracy of the novel spot joint element. Then, the structural stresses along different cross-sections emanating from joint are also calculated for the specimens with fasteners to investigate the potential different failure modes. Finally, the fatigue data correlation based on the novel spot joint element and traction-based structural stress method using available literature data are presented and served as example applications.
In recent years, computer-aided engineering (CAE) has become an essential practice in design and durability analysis of industrial components such as weldments. The current analytical trend for CAE-based fatigue life prediction of weldments includes procedures based on design guidelines, mesh-sensitive methods (e.g., local strain-life approach) and mesh insensitive methods (e.g., Volvo and Verity methods). As an inherent characteristic of weldments, the geometry of the weld is often simplified in failure analysis and important hotspots such as start/stop of the weld beads are not considered in the design process. However, such critical locations cannot be avoided in complex welded structures. Therefore, incorporating main geometrical details of the weld can improve the accuracy of critical regions identification and damage calculation using mesh-sensitive CAE-based methodologies. Herein, a framework for life prediction of welded components including the weld geometry is discussed and evaluated by its application to a coupled torsion beam axle. The weldment was simulated in finite element (FE) environment as a shell model with local mesh refinement and improved weld geometry. The FE model was validated by strain gage measurements of the actual component under single-channel constant amplitude load and critical locations in the component were accurately identified. Local stress-life and critical plane approaches were employed to predict fatigue life to failure resulting in reasonable accuracy within a factor of two. Despite the close results by the uniaxial and multiaxial fatigue damage criteria in this work, advanced life prediction approaches such as the critical plane concept are recommended due to their robustness for more complex and realistic loading conditions during service.
Carbon fiber-reinforced polymers (CFRPs) have become essential in modern aerospace structures, from fuselage skins and wing components to nacelles, interior structures, and a growing range of primary load-bearing parts. Their high strength-to-weight ratio delivers major benefits in fuel efficiency, payload capacity, and fatigue performance. Yet achieving reliable adhesive bonds on CFRP surfaces remains a persistent engineering challenge. The low intrinsic surface energy of composites - particularly under thermal cycling, vibration, and moisture exposure - limits bond durability unless surfaces are properly prepared. Plasma surface treatment has emerged as a pivotal solution, offering a fast, controllable, and non-destructive way to increase surface energy, improve wettability, and enhance adhesion across complex geometries. This is especially important as the aerospace industry transitions from thermoset to thermoplastic composites (TPCs), which enable faster processing, lower production costs, and better recyclability.
Items per page:
50
1 – 50 of 3357