Modeling of Short Fiber Reinforced Polymer Composites Subjected to Multi‐block Loading

RETRACTED: Fatigue property study and life assessment of composite girders with two corrugated steel webs

Lightweight-structural durability design by consideration of variable amplitude loading

Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

9 - Fatigue life prediction of composite materials under realistic loading conditions (variable amplitude loading)

A phenomenological stress–strain model for wrought magnesium alloys under elastoplastic strain-controlled variable amplitude loading

Fatigue assessment of naval welded assemblies

PurposeEngineering components/structures are usually subjected to complex and variable loads, which result in random multiaxial stress/strain states. However, fatigue analysis methods under constant loads cannot be directly applied to fatigue life prediction analysis under random loads. Therefore, the purpose of this study is how to effectively evaluate fatigue life under multiaxial random loading.Design/methodology/approachFirst, the average phase difference is characterized as the ratio of the number of shear strain cycles to the number of normal strain cycles, and the new non-proportional additional hardening factor is proposed. Then, the determined random typical load spectrum is processed into a simple variable amplitude load spectrum, and the damage in each plane is calculated according to the multiaxial fatigue life prediction model and Miner theory. Meanwhile, the cumulative damage can be calculated separately by projection method. Finally, the maximum projected cumulative damage plane is defined as the critical plane of multiaxial random fatigue.FindingsThe fatigue life prediction capability of the method is verified based on test data of TC4 titanium alloy under random multiaxial loading. Most of the predicting results are within double scatter bands.Originality/valueThe objective of this study is to provide a reference for the determination of critical plane and non-proportional additional hardening factor under multiaxial random loading, and to promote the development of multiaxial fatigue from experimental studies to practical engineering applications.

Fatigue behaviour of additive manufactured Ti6Al4V, with as-built surfaces, exposed to variable amplitude loading

Investigation of the fatigue behaviour of the welded joints treated by TIG dressing and ultrasonic peening under variable-amplitude load

The aim of this study is to deal with the simulation of intralaminar fatigue damage in unidirectional composite under multi-axial and variable amplitude loadings. The variable amplitude and multi-axial loading is accounted for by using the damage hysteresis operator based on Brokate method [6]. The proposed damage model for fatigue is based on stiffness degradation laws from Van Paepegem combined with the ‘damage’ cycle jump approach extended to deal with unidirectional carbon fibres. The parameter identification method is here presented and parameter sensitivities are discussed. The initial static damage of the material is accounted for by using the Ladevèze damage model and the permanent shear strain accumulation based on Van Paepegem’s formulation. This approach is implemented into commercial software (Siemens PLM). The validation case is run on a bending test coupon (with arbitrary stacking sequence and load level) in order to minimise the risk of inter-laminar damages. This intra-laminar fatigue damage model combined efficient methods with a low number of tests to identify the parameters of the stiffness degradation law, this overall procedure for fatigue life prediction is demonstrated to be cost efficient at industrial level. This work concludes on the next challenges to be addressed (validation tests, multiple-loadings validation, failure criteria, inter-laminar damages…).

Fatigue life prediction of parabolic leaf spring under various road conditions

In this paper, a probabilistic double linear damage accumulation model is proposed to characterize the uncertainty of damage accumulation using the statistics of material fatigue life. The probabilistic modeling framework is performed under normal distribution assumption of fatigue life. By applying a one‐to‐one probability density function transformation method, the probability distribution of critical damage and cumulative damage can be extracted and derived. The proposed probabilistic damage accumulation model is then used for fatigue reliability analysis by building the reliability formulas with respect to the cumulative damage and the critical damage under both constant and variable amplitude loadings. It treats the mean and variance of cumulative damage as time‐dependent values that dynamically vary with increase in usage life. The reliability can be easily calculated by limited data necessary from fatigue life samples. The applicability of the proposed method is demonstrated using the experimental data of two metallic materials under constant amplitude and two‐block loadings. The results show that the model predictions are in good agreement with the experimental observations under constant amplitude loading and L‐H loading sequence. In addition, the proposed method provides better predictive ability than the Miner rule under constant amplitude loading and H‐L loading sequence. Moreover, the predicted reliability plots can typically present a two‐stage fatigue characteristic during crack initiation and crack propagation periods.

Fatigue life prediction based on equivalent initial flaw size for Al-Li alloy 2297 under spectrum loading

Fatigue assessment methods for variable amplitude loading of welded structures

It has been shown in several studies that methods to improve the fatigue strength of welded structures, such as high-frequency impact treatment (HFMI), can increase the fatigue life of welded joints [1–6]. The results of these investigations led to current guidelines and recommendations for the fatigue assessment of HFMI-treated welded joints. Nevertheless, in practice, there are reservations regarding the efficiency of HFMI-treated welded steel joints under variable amplitude loading. Recent results [7] from studies on transverse attachments of the material S355 and S700 under variable amplitude loading show that the fatigue strength increasing effect of the HFMI-treatment is maintained compared to the as-welded state. The aim of this study is to analyse the sequence effect on the fatigue strength of HFMI-treated transverse attachments and to validate the applicability of linear damage accumulation hypotheses for the design of as-welded and HFMI-treated welded details. In this paper, fatigue test results with random variable amplitude loading (VAL) and high-low VAL and low–high VAL with linear spectrum for the two states as-welded (AW) and HFMI-treated joints will be presented.