Fatigue Life Of Structures Research Articles

Fatigue Assessment of Inclined Film Cooling Holes in Nickel-Based Single-Crystal Superalloy

Fatigue tests of nickel-based single-crystal superalloys with inclined film cooling holes (FCHs) at 1000°C were conducted to investigate the effects of crystal orientation and to quantify the fatigue performance of the high-temperature structures. Fractographic analysis and computations of stress concentrations revealed competitive failure mechanisms between mode I crack nucleation and fatigue crack growth in crystallographic plastic slip systems, whereas crack nucleation around inclined FCHs can be characterized by the known fatigue criteria derived for smooth specimens. A life prediction model based on the crystal slip mechanism and the theory of critical distance was introduced to predict the fatigue life of FCH structures and provided reasonable accuracy for different FCH specimens.

Experimental and Numerical Investigation on Stress Concentration Factors of Offshore Steel Tubular Column-to-Steel Beam (STCSB) Connections

Steel tubular column-to-steel beam (STCSB) connections are critical parts in offshore structures, where complex component connections and the stress concentration are of significant concern. This study conducted stress concentration tests on welded STCSB connections and subsequently developed a finite element (FE) model for the connections, with the experimental results validating the accuracy of the model. The discussion focused on the influence of parameters such as the width-to-diameter ratio of the beam to the column, the diameter-to-thickness ratio of the column, the diameter-to-thickness ratio of the column to the beam, and the height-to-thickness ratio of the beam web on the fatigue performance. The study proposed optimization methods including the addition of stiffeners and outer flange plates. The findings indicate that optimized connection configurations can effectively mitigate stress concentration in the connected areas, thereby enhancing the structural stability and fatigue life. The width-to-diameter ratio of the beam to the column and the diameter-to-thickness ratio of the column significantly affect the fatigue performance of welded STCSB connections, with an increased width-to-diameter ratio of the beam to the column or a reduced diameter-to-thickness ratio of the column leading to a substantial decrease in the maximum stress concentration factors (SCFs). The addition of stiffeners and adjustment of the outer flange plate can improve stress concentration effects in the connection area.

Research on Advanced Prediction of Major Equipment Fatigue Load Based on Deep Learning

Abstract The fatigue life of complex service structures is predicted in real-time according to dynamic random loads. Real-time monitoring of stress/strain in structure key parts is important for practical engineering. Based on the deep learning theory, this paper proposes a long and short-term memory convolutional neural network (CNN- LSTM) prediction model with attention mechanism by using the actual workload data set of key components in major equipment. Firstly, convolutional neural networks (CNN) is used to extract the high-dimensional abstract representation from the preprocessed data, and attention mechanism is added to give each channel different attention scores. Then, long and short-term memory (LSTM) is used to process the time series data and output the final prediction results. In this study, data points in the future are predicted, and the final predicted results are root mean square error (RMSE) of 33.2626 and mean absolute percentage error (MAPE) of 15.3768, which can well fit the future load change trend. At the same time, the multi-condition identification module is added to the code, which can better adapt to the changing load of mechanical equipment in the actual service process. Finally, this paper also designed an ablation experiment, which proved the effectiveness of the overall structure of the prediction model designed in this study and the necessity of the three parts of CNN, ECA-Net and LSTM. It provides theoretical support and practical engineering application for real-time monitoring and predicting the fatigue life of important equipment.

Equations for efficient cycle-by-cycle computation of fatigue crack retardation and acceleration due to amplitude changes

The paper presents an efficient methodology for computation of the evolution of the fatigue crack retardation and acceleration effects due to crack closure during variable amplitude loading. The presented approach can lead to a very effective tool for estimation of residual fatigue life of engineering structures. Conventionally, consideration of variable-amplitude loading is either computationally too demanding, such as in finite element modelling, or challenging to unify the strip-yield model with another computational code. The simple analytical formulae available in literature are based on residual stress, which does not describe correctly the delayed retardation effect and in some cases it can be non-conservative. This work presents simple analytical equations describing the development of the crack closure based on the results of the strip-yield model for amplitude changes at the load ratio R = 0.1. The parabolic function enables simple computation of the maximum crack closure occurring after an overload without running any simulation. The equations also enable computation of crack closure behaviour following amplitude changes with the consideration of various cyclic material properties reflected in the tuneable ratio between the monotonic and cyclic plastic zone sizes.

A generative adversarial network for enhancing over-expansion flow field perception of nozzles with large expansion ratio

Over-expansion flow and separation phenomena exist inside the nozzle during the startup and shutdown of the rocket engine, and the transition between the separation modes is prone to cause significant side loads and jeopardize the safety of the engine. Accurate, comprehensive and prompt nozzle flow field state perception is of great significance to the stable operation of the engine. Here, a generative adversarial network is proposed to reconstruct the internal Mach number and temperature fields for different nozzle pressure ratios and flow separation modes based on the discrete pressure at the nozzle wall. The proposed generative adversarial network employs Wasserstein distance and gradient penalty to improve the problems of gradient vanishing and pattern collapse during discriminator network training. The large expansion ratio nozzle selected was the VOLVO S1 nozzle and numerical simulations were carried out under different nozzle pressure ratio conditions to obtain data for the training of data-driven model. The results indicate that generative adversarial networks can accurately reconstruct restricted shock separation and free shock separation modes under different nozzle pressure ratios based on discrete pressure and temperature measurement points on the nozzle wall, with a relative error of less than 1.2%, and accurately identify important flow field characteristics such as Mach disk, supersonic jet flow, and multiple recirculation regions. The advantages of the generative model in recognizing the strong normal shock Mach disk are compared with those of the supervised learning model. This study lays the foundation for the subsequent study of nozzle side load and structural fatigue life based on three-dimensional flow field.

Failure Analysis of a Suspended Inter-Array Power Cable between Two Spar-Type Floating Wind Turbines: Evaluating the Influence of Buoy Element Failure on the Cable

The suspended configuration of inter-array power cables between floating offshore wind turbines necessitates using various ancillary equipment, such as buoy elements and bend stiffeners, to maintain the desired cable geometry. The failure analysis is an important step in the design of an inter-array dynamic power cable layout. This study investigates the impact of buoy element failures on the structural integrity and fatigue life of inter-array power cable configurations in offshore environments, focusing on four environmental conditions representative of the North Sea. Utilizing numerical simulations and fatigue analysis in OrcaFlex, static and dynamic analyses are conducted to assess maximum tension, minimum bend radius (MBR), and fatigue life under single and two failure scenarios of buoy elements. The results indicate that single buoy failures significantly increase maximum tension at hang-off points. At the same time, MBR is found to be the smallest at the failure position, aiding in failure point identification. In addition, for the two buoy element failure scenarios, the maximum tension increase poses risks to structural integrity, while MBR and fatigue life have high sensitivity to the applied environmental conditions.

Empirical modeling of stress concentration factors using artificial neural networks for fatigue design of tubular T-joint under in-plane and out-of-Plane bending moments

PurposeStress concentration factors (SCFs) are commonly used to assess the fatigue life of tubular T-joints in offshore structures. SCFs are usually estimated from parametric equations derived from experimental data and finite element analysis (FEA). However, these equations provide the SCF at the crown and saddle points of tubular T-joints only, while peak SCF might occur anywhere along the brace. Using the SCF at the crown and saddle can lead to inaccurate hotspot stress and fatigue life estimates. There are no equations available for calculating the SCF along the T-joint's brace axis under in-plane and out-of-plane bending moments.Design/methodology/approachIn this work, parametric equations for estimating SCFs are developed based on the training weights and biases of an artificial neural network (ANN), as ANNs are capable of representing complex correlations. 1,250 finite element simulations for tubular T-joints with varying dimensions subjected to in-plane bending moments and out-of-plane bending moments were conducted to obtain the corresponding SCFs for training the ANN.FindingsThe ANN was subsequently used to obtain equations to calculate the SCFs based on dimensionless parameters (α, β, γ and τ). The equations can predict the SCF around the T-joint's brace axis with an error of less than 8% and a root mean square error (RMSE) of less than 0.05.Originality/valueAccurate SCF estimation for determining the fatigue life of offshore structures reduces the risks associated with fatigue failure while ensuring their durability and dependability. The current study provides a systematic approach for calculating the stress distribution at the weld toe and SCF in T-joints using FEA and ANN, as ANNs are better at approximating complex phenomena than typical data fitting techniques. Having a database of parametric equations enables fast estimation of SCFs, as opposed to costly testing and time-consuming FEA.

P-S-N surfaces of lifting lug structure based on extremely small samples

Given the susceptibility of lifting lug structures to fatigue failure under heavy loads and the high cost associated with fatigue testing time, determining the P-S-N model with a limited sample size holds significance in engineering. Assuming that the logarithmic fatigue life of the lifting lug structure followed a normal distribution, this study utilized the gray model and Gaussian process regression optimized by a genetic algorithm to predict fatigue lives at equidistant stress amplitudes. In addition, the improved bootstrap method was used to expand the experimental extremely small samples. The findings demonstrate that incorporating the mean stress into the S-N curve of the exponential function and utilizing a polynomial to account for the segmented behavior proved highly advantageous in attaining a more accurate S-N model. The mean and standard deviation of logarithmic life at each stress level were assessed by the expanded samples, resulting in P-S-N surface fitting outcomes. This study contributes to the fatigue reliability analysis in situations with limited sample sizes.

Crack propagation simulation and overload fatigue life prediction via enhanced physics-informed neural networks

The fatigue crack growth simulation and life prediction of structures are implemented in this paper based on the physics-informed neural networks (PINNs). Firstly, the enhanced PINNs are proposed by introducing the crack tip asymptotic displacement fields, so that the crack tip stress intensity factors can be calculated accurately even when the number of collocation points is small and the distribution grid is regular. The enhanced PINNs essentially transform the solution of elastic body containing crack into the optimization of minimizing the constructed loss functions, and can invert the fracture parameters. Then, an automatic crack propagation simulation method is developed based on the enhanced PINNs. The network architecture and the overall node distribution can be unchanged during the crack propagation process, and only new crack surfaces need to be processed and corresponding loss functions need to be modified. Because the nodal refinement around crack-tip is not required, this simulation method is convenient and can accurately predict the mixed-mode crack propagation path. Finally, the fatigue crack growth life algorithm considering overload is developed, where the effect of each overload can be captured by the cycle-by-cycle method. Based on this algorithm, the retardation behavior can be characterized and the fatigue life of structure under the load spectrum with periodic overloads can be accurately predicted. The sufficient examples are given to verify the feasibility and accuracy of the method proposed in this paper.

An artificial neural network model for determining stress concentration factors for fatigue design of tubular T-joint under compressive loads

PurposeThe stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.Design/methodology/approachA mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.FindingsUsing real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.Practical implicationsEngineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.Originality/valuePrecisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming.

Fatigue Analysis of a Jacket-Supported Offshore Wind Turbine at Block Island Wind Farm.

Offshore wind-turbine (OWT) support structures are subjected to cyclic dynamic loads with variations in loadings from wind and waves as well as the rotation of blades throughout their lifetime. The magnitude and extent of the cyclic loading can create a fatigue limit state controlling the design of support structures. In this paper, the remaining fatigue life of the support structure for a GE Haliade 6 MW fixed-bottom jacket offshore wind turbine within the Block Island Wind Farm (BIWF) is assessed. The fatigue damage to the tower and the jacket support structure using stress time histories at instrumented and non-instrumented locations are processed. Two validated finite-element models are utilized for assessing the stress cycles. The modal expansion method and a simplified approach using static calculations of the responses are employed to estimate the stress at the non-instrumented locations-known as virtual sensors. It is found that the hotspots at the base of the tower have longer service lives than the jacket. The fatigue damage to the jacket leg joints is less than 20% and 40% of its fatigue capacity during the 25-year design lifetime of the BIWF OWT, using the modal expansion method and the simplified static approach, respectively.

Effect of scour on the fatigue life of offshore wind turbines and its prevention through passive structural control

Abstract. Offshore wind turbine (OWT) support structures are exposed to the risk of fatigue damage and scour, and this risk can be effectively mitigated by installing structural control devices such as tuned mass dampers (TMDs). However, time-varying scour altering OWTs' dynamic characteristics has an impact on the TMD design and fatigue life, which has rarely been studied before. In this paper, a simplified modal model is used to investigate the influence of scour and a TMD on the fatigue life evaluation of a 5 MW OWT's support structure, and a traditional method and a newly developed optimization technique are both presented to obtain TMD parameters. This optimization technique aims at finding optimal parameters of the TMD which maximize the fatigue life of a hotspot at the mudline, and the effect of time-varying scour can be considered. This study assumes that the TMD operates in the fore–aft (FA) direction, while the vibration in the side–side (SS) direction is uncontrolled. Results show that scour can decrease the fatigue life by about 24.1 % and that the TMD can effectively suppress vibration and increase the fatigue life. When the scour depth reaches 1.3 times the pile diameter, the TMD with a mass ratio of 1 % can increase the fatigue life of an OWT's support structure by about 64.6 %. Further, it is found that the fatigue life can be extended by 25 % with the TMD optimized by the proposed optimization technique rather than using a traditional design method which does not take the change in dynamic characteristics into account.

Synchrotron diffraction residual stresses studies of electron beam welded high strength structural steels

In recent years, there's been a strong focus on enhancing high-strength structural steels (HSSSs), making them tougher, stronger, lighter, and more weldable. However, these steels face challenges like cold cracking sensitivity (CCS) and reduced toughness with higher heat input. Therefore, exploring HSSSs with advanced welding techniques like electron beam welding (EBW) is crucial. EBW known for its innovation and precision, is gaining popularity in HSSSs applications for vehicles, construction industries etc. offering advantages like narrow welds, reduced heat-affected zone (HAZ) and low distortion. It is essential to understand the influence of residual stresses (RS) in HSSSs which ultimately affect structural integrity and fatigue life. Using EBW on HSSSs, coupled with synchrotron XRD for residual stress studies, has great potential to advance this research significantly. In this work, a 15-mm-thick EB-welded joint of S960QL and S960 M steels was used to study the RS. At an energy level of 20 keV, RS data from the synchrotron XRD method and its result on the top of welded joints for both types of steel were compared. S960 M steel showed a longitudinal tensile stress of 250 MPa at the weld toe, approximately 1.8 times higher than the 138 MPa observed in S960QL steel under similar conditions. In transverse stress, S960QL exhibits a higher stress of 279 MPa compared to S960 M 46 MPa at the weld toe, approximately 83% lower. The synchrotron method measured 76% lower LRS for S960QL compared to conventional XRD, while S960 M exhibited 55% lower LRS using the same approach.

Mechanistic Study of Failure in CFRP Hybrid Bonded-Bolted Interference Connection Structures under Tensile Loading.

Hybrid bonded-bolted composite material interference connections significantly enhance the collaborative load-bearing capabilities of the adhesive layer and bolts, thus improving structural load-carrying capacity and fatigue life. So, these connections offer significant developmental potential and application prospects in aircraft structural assembly. However, interference causes damage to the adhesive layer and composite laminate around the holes, leading to issues with interface damage. In this study, we employed experimental and finite element methods. Initially, different interference-fit sizes were selected for bolt insertion to analyze the damage mechanism of the adhesive layer during interference-fit bolt installation. Subsequently, a finite element tensile model considering damage to the adhesive layer and composite laminate around the holes post-insertion was established. This study aimed to investigate damage in composite bonded-bolted hybrid joints, explore load-carrying rules and failure modes, and reveal the mechanisms of interference effects on structural damage and failure. The research results indicate that the finite element prediction model considering initial damage around the holes is more effective. As the interference-fit size increases, damage to the adhesive layer transitions from surface debonding to local cracking, while damage to the composite matrix shifts from slight compression failure to severe delamination and fiber-bending fracturing. The structural strength shows a trend of initially increasing and then decreasing, with the maximum strength observed at an interference-fit size of 1.1%.

Fatigue Life and Crack Initiation of K and N Type Jacket Structure Using 3D Fatigue FE Analysis

Jacket structures are widely used as foundation structures for offshore wind energy. The jacket structure as a truss shape structure is not deformed easily and has the advantage of keeping the structure stable under wind load. The offshore jacket structures are subjected to unstable repetitive loads such as wind, and wave loads in the deep sea. These harsh environments lead to the deterioration of material performance and fatigue failure with cracks in the structure. It is crucial to locate fatigue cracks since they might compromise a structure's overall stability.In this study, fatigue life and crack initiation for different braced jacket structures were investigated. First, 3D non-steady heat conduction analysis and thermal elastic-plastic analysis were performed to reproduce the initial state of the weld joint in the jacket structure. The heat history obtained from the 3D non-steady heat conduction analysis was enforced as an input in thermal elastic-plastic analysis to calculate welding deformation and residual stress. Next, the fatigue FE analysis of the jacket welding structure was carried out using the residual stress and welding deformation as initial values along with the external cyclic loadings. The 3D fatigue FE analysis employed cyclic hysteresis constitutive equations and fatigue damage theory to calculate the fatigue life and crack initiation. The 3D fatigue FE results were compared with the S-N curve by European code 3 and the hot spot stress (HSS) method. The results show that the 3D fatigue FE method effectively calculates the fatigue life and finds crack initiation.

Joint identification method for thermal–mechanical coupling loads

The crucial role in evaluating structural fatigue life, implementing health monitoring, and optimizing lightweight and reliable design is played by load identification technology. With the development of the aviation industry towards high-speed aircraft, the challenges under high temperature and high load conditions have been intensified. Unfortunately, in environments characterized by the coexistence of force and heat, difficulties are faced by existing load identification methods in achieving key decoupling and accurate identification of force and temperature fields. To address this gap, the Joint Identification Method (JIM), a new method that integrates force and thermal strain patterns, is introduced in this article. This method has been developed through in-depth research on “joint physical fields” and “joint basis functions.” Multiple physical fields for load identification are systematically decomposed by our method, each field is theoretically deduced, and they are seamlessly reassembled using the same structural spatial field. Through the method, mechanical strain and thermal strain are separated in high-precision temperature field reconstruction, and a basis function method for identifying the full field load distribution under a few measurement points is obtained. To verify the accuracy of our proposed Joint Identification Method (JIM), five experiments were designed, and the results consistently demonstrated the superiority of our method in accuracy (with an error always below 5%), efficiency (avoiding a large number of redundant calculations in traditional Duhamel methods), and reliability in static and dynamic load static heat identification. In the end, accurate, efficient, and reliable identification of the structural strain field, structural load field, and temperature field were achieved by our method.

Fatigue and post-fatigue behavior of FRCM-concrete specimens under direct shear and bending conditions

The combined effect of cyclic loading and steel rebar corrosion can determine the premature deterioration of reinforced concrete (RC) structures subjected to dynamic and environmental actions. The use of fabric-reinforced cementitious matrix composites (FRCM) is a promising solution to extend the fatigue life of RC structures. Externally bonded FRCMs are applied to the tension side of structural members to reduce the rebar stress level, thus delaying fatigue crack nucleation and/or propagation. A key aspect for the design of FRCM strengthening of these structures is the matrix-fiber bond behavior under fatigue loading. In this paper, a critical review of currently available studies on the fatigue behavior of FRCM-strengthened RC beams is presented. Then, the results of 25 bond tests on PBO FRCM-concrete specimens are provided and discussed. These tests include both single-lap direct shear and modified beam tests performed in quasi-static and cyclic mode. The results obtained show that the cyclic load may induce progressive debonding at the matrix-fiber interface with rupture of fiber filaments. Modified beam tests are more affected by these phenomena than direct shear tests. The rupture of fiber filaments is confirmed by the results of post-fatigue tests that show capacities lower than those of corresponding quasi-static tests.

Study of the kurtoses transmission of linear structures under stationary non-Gaussian random loadings

Recent research has discovered that the kurtoses of non-Gaussian stress loadings can significantly impact the fatigue life of in-service structures. To predict potential damage, a fatigue life estimation method based on Gaussian damage and a kurtosis-related corrective coefficient has been developed. However, the transmission of kurtoses from excitations to responses has not been well studied, particularly in multi-input cases. This hinders efforts to accelerate fatigue damage by controlling input kurtoses. Therefore, this paper aims to establish a kurtoses transmission model for a linear structure under multiple uncorrelated stationary non-Gaussian excitations generated by zero-memory non-linear method. Firstly, a single-input kurtosis transmission equation is proposed to establish the relationship between excitation kurtosis and response kurtosis. Using this equation, the response kurtosis is formulated with input kurtosis and the system parameters of a linear structure. Secondly, the response kurtosis of multi-input cases is deduced, and the study shows that the response kurtosis is the weighted sum of the kurtosis induced by each excitation. Finally, numerical validation and experimental studies are conducted to verify the accuracy of both the single-input and multi-input kurtoses transmission models. The validations demonstrate that the proposed models can predict the response kurtoses with satisfactory precision, regardless of the input spectral shape and the number of uncorrelated input forces.

An efficient/accurate multi-scale fatigue prediction method for Metal-Polymer hybrid (MPH) interface

Metal-polymer hybrid (MPH) structures, featuring a micro-structure interlocking design, combine the high strength of metal with the exceptional formability of polymer-based composites and have gained significant attention in automotive load-bearing components. Challenges persist in accurately predicting MPH structure fatigue life using small samples with diverse interlock parameters and swiftly generating static strength and fatigue life response surfaces for automated optimization. We introduce a simplified model for predicting fatigue at the interfaces of MPH structures. Our multi-fidelity prediction method integrates this model with limited high-fidelity data samples to assess both the static strength and fatigue life effectively. This method predicts the deviation with less than 3% error compared to FSR-FEM, achieving a reduction in prediction time of over 60%. Additionally, we elucidate the non-synergistic mechanisms of key interfacial locking parameters between static strength and fatigue life at the micro-scale. Finally, we propose and apply a multi-objective synergistic optimization strategy to the MPH thrust rods in vehicles. By utilizing our optimization method, we achieve a 27.9% weight reduction compared to steel counterparts, while enhancing overall tensile strength by 11.8% and significantly improving fatigue life by 46.7% compared to MPH torque rods lacking an interlock interface.

No-drilling method for the robust frequencies-based analysis of layer thickness backcalculation

A frequency-based backcalculation method has been introduced. It makes possible for a pavement backcalculations to be carried out without a known model layer thickness at the input. Presenting results for an asphalt concrete pavement, the authors set out the procedure, which lead to the determination of the total thickness of the pavement asphalt layers based solely on the results of deflection measurements under dynamic load. For field testing, ZiSPON technology equipped with the FWD module was applied. Compared to the methods classically used for determining the thickness of pavement layers, it has been demonstrated that the relative difference between the thicknesses identified by means of the proposed method and the geotechnical drilling or GPR methods lies in the range of 0 to 11%. By using load sequences of 50, 60, 70 kN, the proposed backcalculation procedure may be an element for a fully automated process of assessing the technical condition of the pavement. The procedure is performed automatically, non-invasively (without the participation of a laboratory technician/analyst) and does not require geotechnical drilling. It is assumed that the identified thicknesses can subsequently be used to assess the fatigue life of the pavement structures. A pavement model can be further created with already known total asphalt layers thickness.