Influence of dynamic characteristics of monopile supported offshore wind structures on fatigue loading

Mechanism of Crack Initiation / Propagation for Ultra-high Strength Stainless Steel under Corrosion Environment - Fatigue Load Coupling

• A dCESO-based ADRC strategy is proposed for collective pitch control of floating offshore wind turbines. • A Red-Tailed Hawk (RTH) optimization algorithm is employed to tune the controller parameters. • The proposed controller improves power regulation and rotor speed stability under turbulent wind and wave conditions. • Comparative results demonstrate enhanced overall performance relative to GSPI, ROSCO, and ESO-ADRC controllers. • The control strategy provides favorable trends in damage equivalent load (DEL) mitigation for key structural components. This paper introduces a model-free control strategy for floating offshore wind turbines (FOWTs), which utilizes a double cascade, two extended state observer (dCESO)-based active disturbance rejection controller (ADRC) to regulate the collective pitch angle of the turbine. The primary objectives are stabilizing the generated power and rotor speed at their rated values while mitigating damage equivalent loads (DELs) on the tower and mooring lines. A data-driven approach employs the red-tailed hawk (RTH) optimization algorithm to fine-tune the controller parameters for optimal performance. The proposed controller is applied to the 5 MW NREL FOWT mounted on a semi-submersible floating platform and evaluated under various operational conditions, including above-rated wind and wave scenarios. Simulation results demonstrate that the dCESO-based ADRC maintains power output and rotor speed at their rated levels, even in challenging environments. A comparison with the standard ADRC, reference open-source controller (ROSCO), and the gain scheduling PI (GSPI) controllers also shows that the optimized controller is better at improving control performance while lowering DELs by a large amount. The ultimate finding reveals that the proposed controller has provided an excellent balance between the performance indicators including the power and the speed errors and the DEL of the tower and the blades, where the power error has been reduced by 48.3% compared to the GSPI, contributing to enhancing the power quality, validating the reliability and effectiveness of the proposed control strategy, establishing it as a robust solution for FOWT applications.

Tubular composite joints offer a non-welded alternative for offshore structures by bonding a composite wrap to steel Circular Hollow Section (CHS) members, eliminating weld-induced stress concentrations and significantly improving fatigue life. This enables steel weight and cost reductions and faster fabrication for jacket structures supporting large off-shore wind turbines. In service, these joints experience complex cyclic loads combining axial forces and bending moments, which can lead to interfacial debonding and delamination, necessitating damage-tolerant design. This paper presents one of the first experimental campaigns applying combined axial and bending loads on composite X-joints using a Hexapod system, enabling realistic offshore load simulation. Fatigue tests on 1/4-scale X90 specimens cover pure axial tension, out-of-plane bending, and combined cases. Two primary failure modes were observed: interfacial debonding under compressive strain and delamination under tensile in-plane strain. A numerical methodology based on the Virtual Crack Closure Technique (VCCT) and a stepwise crack-growth model incorporating non-linear crack retardation effects, rarely considered in composite joint fatigue modelling, was developed. Calibration of the Paris-law constant C revealed variations up to two orders of magnitude due to interface quality and manufacturing variability. Despite this, results demonstrate fatigue life extensions of up to 2000 times compared to welded joints. This work introduces a design philosophy leveraging crack retardation and interface friction effects to predict fatigue life, moving beyond conservative stress-based criteria towards damage-tolerant offshore design. • Hexapod tests of 1/4-scale tubular composite X-joints under multi-axial fatigue. • VCCT stepwise model with specimen-specific Paris-law calibration (C). • Two failure modes: interface debonding and delamination. • Optical-fibre sensing tracked crack fronts. • Fatigue life ⩾ 8 × ; projected 600–2000 × vs welded joints at design loads.

Degradation and service life prediction of reinforced concrete beams under coupled fatigue loading and chloride ingress: A review

The filler-to-binder ratio plays a critical role in determining the rheological performance and fatigue behavior of emulsified asphalt mastics; however, its influence on viscoelastic response and failure characteristics remains insufficiently understood. In this study, emulsified asphalt mastics with different filler-to-binder ratios were prepared using conventional emulsified asphalt and SBS-modified emulsified asphalt. Their rheological and mechanical behaviors were evaluated using dynamic shear rheometer (DSR), multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), and bending beam rheometer (BBR) tests. The results showed that increasing the filler-to-binder ratio enhanced the stiffness and high-temperature deformation resistance of emulsified asphalt mastics, as reflected by increases in complex modulus, rutting factor, and yield stress. However, excessive filler content reduced fatigue tolerance and low-temperature flexibility, as indicated by decreases in yield strain, failure strain, and m-value, together with an increase in low-temperature creep stiffness. The MSCR results further showed that higher filler contents changed the nonrecoverable creep response of the mastics, and negative Jnr-diff values at high filler-to-binder ratios suggested a transition in the rheological response of the highly filled mastic system. For SBS-modified emulsified asphalt mastics, a distinct phase angle inflection point was observed during fatigue loading, which may serve as a rheological indicator for characterizing the transition of fatigue damage behavior. These findings clarify the effect of filler-to-binder ratio on the rheological evolution, deformation resistance, fatigue behavior, and low-temperature performance of emulsified asphalt mastics. The results provide practical guidance for optimizing filler-to-binder ratio design in pavement engineering applications.

Introduction: The cognitive and mental demands placed on football players are considerable. Athletes must consistently maintain vigilance, execute swift decision-making, process incoming information efficiently, and regulate emotional responses effectively. Objective: This study investigated the weekly fluctuations in Countermovement Jump (CMJ) performance, Rating of Perceived Exertion (RPE), mental fatigue (MF), and mental load (ML) in elite U19 football players across microcycles featuring single or double match weeks. Methodology: Eighteen elite male U19 football players from Spain participated during the 2024–2025 season. CMJ performance was assessed 30 minutes before and 20 minutes after each training session, while RPE, MF, and ML were evaluated following each session. Results: Findings revealed an inverse relationship between players’ RPE and pre-competition jump performance. Critically, during M2-Opt sessions, scheduled 48 hours prior to a match and often associated with double competition weeks, players reported significantly higher RPE and MF scores. This indicated elevated physical and mental demands on match day minus two (MD-2), coinciding with diminished jump performance. These fatigue levels were consistent with observed weekly microcycle fluctuations, highlighting MD-2. Discussion: The significant influence of pre-match demands on physical and mental fatigue, culminating in impaired performance, underscores the necessity for coaches to meticulously manage training loads. Conclusion: Prioritizing athlete recovery and strategically minimizing strenuous physical and mental stimuli in the days leading up to competition are crucial to optimize performance, mitigate injury risk, and ensure competitive readiness in elite youth football.

This study presents an AI-based methodology for the quantitative evaluation of crack propagation in cyclically loaded thick-layer silicone adhesive joints used in structural glazing systems. Experimental shear tests under low cycle fatigue loading were recorded with a DSLR and analyzed using a convolutional neural network for crack detection and segmentation. A dedicated dataset was generated from video frames and annotated to capture varying crack geometries and substrate positions. Real-time object detection-based segmentation models were trained and systematically optimized through hyperparameter tuning. To address deformation-induced crack distortion, a linear back-calculation was implemented to transform detected crack geometries into an undeformed reference state. This enables the extraction of normalized crack metrics independent of instantaneous deformation. The automated measurements were validated against manual reference evaluations, showing reproducible accuracy across multiple specimens. Increasing input resolution was associated with improved geometric agreement, while training stability depended on an appropriate balance of model complexity. The proposed approach extends conventional experimental evaluation by enabling continuous, image-based crack assessment throughout cyclic loading. This provides a basis for the future evaluation of adhesive joint performance under low-cycle fatigue conditions while accounting for the actual crack propagation behavior.

To evaluate and compare the fatigue performance of veneers fabricated from lithium disilicate, 3D-printed resin composite, and injection-molded direct resin composite under standardized cyclic loading. Thirty extracted human maxillary central incisors (n = 10 per group) received standardized veneer preparations. Veneers were fabricated using CAD/CAM milling (lithium disilicate), additive manufacturing (3D-printed resin composite), or injection molding (direct composite). Specimens were adhesively bonded following manufacturer protocols, thermocycled (10,000 cycles) and subjected to cyclic fatigue loading (200 N, 1.6 Hz) for up to 1,000,000 cycles. Fatigue survival was analyzed using Kaplan-Meier and log-rank tests. Significant differences in survival distributions were observed (p < 0.001). Lithium disilicate showed the highest fatigue performance, with 80% survival at 1,000,000 cycles and a mean survival of 954,060 cycles. 3D-printed resin composite showed the lowest survival (mean: 134,878 cycles), while direct resin composite exhibited intermediate performance (mean: 460,453 cycles). Failure modes varied by material, with lithium disilicate demonstrating debonding, 3D-printed resin presenting multiple failure types, and direct composite limited to incisal fractures. Lithium disilicate demonstrated superior fatigue performance compared with resin-based materials. Injection molded direct composite performed better than 3D-printed resin composite with more repairable fractures. Although lithium disilicate restorations remain the most durable material choice for anterior veneers, injection molded direct composites offer an economical option with possibly repairable fractures.

The use of the stress intensity factor K to characterize the severity of crack tip stress fields is widespread throughout engineering. The relationship between K and the crack growth rate is then usually represented empirically by a straight line Paris law relationship on logarithmic axes. This study develops an analytical relationship between the two by linking crack growth to the accumulation of fatigue damage ahead of the moving crack tip. A stress-based fatigue model was used, with inputs from plastic 2D plane stress FE analyses representing an edge crack by a sharp semi-circular notch. Stress–distance profiles ahead of the crack tip were extracted at the maximum and minimum points of a range of fatigue loading cycles. These were then used with data from smooth specimen LCF tests to predict the build-up of fatigue damage at regularly spaced locations ahead of the crack tip and hence crack growth rates. Full da/dN–ΔK curves were generated for the nickel-based superalloy RR1000 at 20 °C with loading R-ratios of 0, −1 and 0.5. The R = 0 and R = −1 crack growth rate predictions agreed well with experimental data, as did the steeper growth rate slope calculated at R = 0.5. The method was then extended to predict overload behaviour.

Sacroiliac joint fixation with a posterior intra-articular implant versus a posterolateral transiliac implant: A biomechanical comparison.

Tendon is critical for musculoskeletal function as it transfers forces generated by muscle to bone and stores energy during movement. Impaired mechanical function in tendon limits mobility and results from fatigue-induced damage progression that outpaces the restorative processes maintaining tissue health, a phenomenon we term mechanopathology. Early and non-invasive detection of tendon mechanopathologies is vital to prevent further damage but is lacking in the clinical space. Here, we evaluate the ability of diffusion tensor magnetic resonance imaging (DT-MRI) to detect mechanical fatigue damage in tendon and validate our findings using histologic assessments of collagen fiber microstructure and molecular structure. We found that fatigue-induced changes in DT-MRI metrics of tendon are spatially heterogeneous and correspond to regions with damaged collagen fiber microstructure. While secondary structures of collagen molecules were damaged by fatigue loading, they do not spatially correspond to fatigue-induced changes in DT-MRI metrics. Fatigue-induced changes in DT-MRI metrics can be partially explained by quantitative metrics of post-fatigue collagen fiber microstructure, estimating the limit of detection of DT-MRI metrics to fatigue-induced damage in tendon. Our findings indicate that DT-MRI metrics are sensitive to fatigue-induced local damage in tendon, supporting the use of DT-MRI as a non-invasive tool to detect tendon mechanopathologies and motivating future work toward clinical translation. STATEMENT OF SIGNIFICANCE: Non-invasive imaging techniques capable of detecting fatigue-induced damage in tendon are lacking in the clinical practice. Diffusion Tensor MRI (DT-MRI) is a non-invasive imaging technique that is sensitive to tissue microstructure, but its sensitivity to detect fatigue-induced damage in tendon - and other connective soft tissues - has not been evaluated. Here, we show that DT-MRI can identify local damage to the collagen fiber microstructure of tendon and establish the detection limits of 9.4 tesla DT-MRI metrics to such damage. Collectively, our findings support DT-MRI as a noninvasive tool for detecting fatigue-induced damage in tendon, and potentially other soft connective tissues, warranting further development to facilitate clinical translation.

Fatigue lifetime and microbial inhibition at the implant-abutment interface of 5Y-PSZ zirconia abutments coated with experimental glass.

Fluid–structure interaction in downstream wind turbine: Spacing-dependent structural loads and responses to upstream wake

Straight skewed I-girder bridges exhibit three-dimensional (3D) behavior due to deformation compatibility considerations. Most pertinent is the development of a stiff transverse load path between the obtuse corners of skewed bridge spans, which results in undesirable 3D effects causing large cross-frame (CF) forces and girder flange lateral bending stresses. Recent research has demonstrated that the CF framing arrangement significantly impacts the stiff transverse load path and the overall 3D behavior of these structures. Limited studies have found that the subway tile stagger framing arrangement, derived from a contiguous framing arrangement by eliminating every other intermediate CF from interior girder bays, is highly effective in mitigating the stiffness of the transverse load path and reducing undesirable 3D effects. The reduction of undesirable 3D effects improves the applicability of line girder analysis methods, thereby simplifying the bridge design. This paper evaluates the impact of CF framing arrangements on the 3D behavior of straight skewed bridges under dead, live, and fatigue loads based on the 10th edition of the AASHTO LRFD Specifications. A 3D finite-element analysis parametric study was conducted, encompassing a wide range of geometric variables and CF framing arrangements. Three framing arrangements, consisting of contiguous, parallel stagger, and subway tile stagger patterns, are studied for highly skewed steel I-girder bridge geometries. The influence of the framing arrangement on the bridge’s 3D behavior is assessed, and guidelines are provided for developing effective framing arrangements that significantly mitigate transverse load path effects in straight skewed bridges. A framework is established for simplified design, selection of framing arrangements, and sizing of CFs.

Adhesive joints are widely used in structural applications. However, they are susceptible to degradation under service loads and adverse environmental conditions, leading to eventual catastrophic failure. Thus, the advancement of monitoring tools that can deliver real-time data on the deterioration of adhesive joints is crucial for enhancing the reliability of structures. This study investigated the feasibility of using electrical impedance responses to monitor integrity degradation under tensile and fatigue loading in single-lap adhesive joints in aluminum alloy and carbon fiber-reinforced polymer (CFRP) specimens. Previous works on electrical impedance monitoring of adhesive joint integrity invariably employed conductive adhesives. Theoretical considerations based on the concept of a capacitive system indicate that electrical impedance monitoring may still be feasible even if the joint is non-conductive. This has important implications as it suggests that the structural health of many existing ordinary adhesive joints may be amenable to impedance-based monitoring. To test this possibility, neat epoxy adhesive joints without the addition of conductive constituents were fabricated with aluminum and composite adherends. The specimens were subjected to tensile and fatigue degradation while the impedance responses under different excitation frequencies were monitored. The results showed that impedance monitoring is insensitive for detecting damage during tensile failure because the onset of debonding that produces a detectable impedance change occurs too close to the unstable final failure. For fatigue cycling, debonding developed at an early stage and evolved in a stable manner, and the impedance gradually increased with the number of fatigue cycles, reflecting the development of fatigue damage. These findings indicate that impedance-based monitoring on non-conductive adhesive joints has strong potential for tracking structural integrity degradation, particularly for fatigue loading.

The paradigm shift from mass production to mass customization has empowered users to actively participate in the product design process. Consequently, interactive product customization has emerged as a critical link connecting user preferences with intelligent manufacturing. However, this system faces two major challenges: the increased cognitive load and decision fatigue caused by explicit feedback (e.g., Rating products), and the difficulty in discerning users’ implicit preferences from the vast amount of procedural information generated during interaction. To address these challenges, this study proposes a novel preference analysis method based on multi-graph that incorporates the user’s selective attention process. This method first achieves a unified representation of gaze and selection behaviors through a graph network, thereby establishing a unified representation for analyzing user cognitive patterns. By integrating global and local information from the graph network, we then propose a selective attention centrality metric to effectively quantify the prominence of different design options within the user’s cognitive process. To demonstrate its practical application, we integrated this metric with an interactive genetic algorithm to develop a customization system for Chinese vases. A controlled experiment was then conducted to compare our method against two traditional approaches. Experimental results show that our proposed method offers significant advantages in multiple metrics, including interaction efficiency, algorithm convergence, and user satisfaction. Specifically, the total evaluation time was reduced by 65.45% and 32.09% compared to the traditional interactive genetic algorithm and eye-tracking analysis methods, respectively. This research combines cognitive science theory with graph network analysis methods. It demonstrates the potential of graph networks in decoding complex human behavior information and building efficient human-AI collaboration systems.

HighlightsStatic weak magnetic signals agree well with deformation evolution.Fatigue magnetic signals show a clear three-stage evolution.Magnetic hysteresis loops reveal richer damage information than deformation loops.Post-fracture magnetic anomalies coincide with the crack location.Weak magnetic signals can indicate local fatigue damage in Fe-SMA.The normal component is more suitable for damage localization and evaluation.Combined magnetic monitoring and scanning enable time-space damage assessment.Iron-based shape memory alloys (Fe-SMAs) have considerable potential for the active strengthening of concrete structures, yet convenient externally applicable non-destructive methods for identifying local fatigue damage under cyclic loading remain limited. To investigate the weak magnetic response of notched Fe-SMA and its correspondence with local damage evolution, static tensile tests and constant-amplitude fatigue tests were conducted on Fe-SMA specimens with a semi-circular notch. Weak magnetic signals were continuously monitored at a fixed point throughout loading, and surface magnetic-field scanning was performed after fracture. Under static loading, the magnetic signal evolved consistently with the deformation response. Under fatigue loading, the fixed-point magnetic signal exhibited a clear three-stage evolution corresponding to the development of residual deformation. Compared with deformation hysteresis loops, magnetic hysteresis loops contained richer information on local damage evolution. After fracture, abrupt changes in the scanned magnetic field coincided with the actual fracture location, and the magnetic anomaly gradually attenuated as the scanning path moved away from the notch. These results indicate that weak magnetic signals can effectively characterise the evolution of local fatigue damage in notched Fe-SMA, with the normal magnetic component showing greater sensitivity to damage localisation and state assessment.

Implantation of a femoral stem in total hip arthroplasty alters physiological load transfer within the proximal femur. Short-stem designs aim to preserve bone stock and maintain proximal load sharing, yet the influence of femoral neck resection height and its interaction with femoral morphology on primary stability remain insufficiently understood. This in vitro biomechanical study investigated these effects using 33 human femora classified as Dorr B or C. In a paired design, a cemented calcar-guided short stem was implanted with either a low (standard) or +5 mm higher femoral neck resection. Specimens underwent cyclic fatigue loading to assess reversible and irreversible micromotion and interface strain, followed by ultimate compression to quantify global fixation strength. Primary stability was assessed by reversible and irreversible translation of the prosthetic head center of rotation and by cortical interface strain measurements using digital image correlation. Overall fixation strength and irreversible deformation remained comparable across resection heights and Dorr types. In contrast, resection height and femoral morphology influenced reversible micromotion and interface strain, with higher resection reducing reversible micromotion, particularly in Dorr C femora and shifting lateral interface strain toward compression. These findings suggest that surgical technique and femoral morphology mainly affect local, reversible bone-cement-implant mechanics rather than global fixation strength.

This study analyses finite elements in the structural calculation of a drone propeller in carbon fiber with loads that represent live use. The output of this study evaluates the effect of load variations on deformation, stress distribution, and safety factors as key indicators of structural performance. A three-dimensional propeller model is developed based on the actual geometric configuration and analysed using the Finite Element Method (FEM). Several loadings are considered: a base load with a total mass of 3.6 kg, and two additional loading conditions with increasing masses of 0.5kg and 0.75kg. The applied loads are converted into equivalent forces distributed along the propeller blades to simulate realistic operating conditions. Simulations show that increasing the applied load causes a proportional increase in the maximum deformation and a significant reduction in the minimum safety factor. The maximum deformation increases from 14.933mm at the base load to 18.044mm at the highest load. The blade tip is consistently identified as a critical region, where the highest deformation and stress concentration occur due to bending-dominated behaviour. The safety factor ranges from 0.51341 to 0.42489 as the load increases, indicating a decrease in structural safety. Fatigue loading is mentioned, this study addresses fatigue qualitatively based on stress concentration and safety factor trends, as explicit S–N curve data, load cycle definitions, and mean stress corrections are not included. The results emphasize the importance of structural optimization and accurate material modelling to improve the reliability and durability of carbon fiber drone propellers under various load conditions.