• Computers and Concrete
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• v.25 no.1
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• pp.67-73
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• 2020

Traditionally used analytical approach to predict the fatigue failure of reinforced concrete (RC) structure is generally conservative and has certain limitations. The nonlinear finite element method (FEM) offers less expensive solution for fatigue analysis with sufficient accuracy. However, the conventional implicit dynamic analysis is very expensive for high level computation. Whereas, an explicit dynamic analysis approach offers a computationally operative modelling to predict true responses of a structural element under periodic loading and might be perfectly matched to accomplish long life fatigue computations. Hence, this study simulates the fatigue behaviour of RC beams with finite element (FE) assemblage presenting a simplified explicit dynamic numerical solution to show computer aided fatigue behaviour of RC beam. A commercial FEM package, ABAQUS has been chosen for this complex modelling. The concrete has been modelled as a 8-node solid element providing competent compression hardening and tension stiffening. The steel reinforcements are simulated as two-node truss elements comprising elasto-plastic stress-strain behaviour. All the possible nonlinearities are duly incorporated. Time domain analysis has been adopted through an automatic Newmark-β time incremental technique. The program consists of twelve RC beams to visualize the real behaviour during fatigue process and to obtain the reliability of the study. Both the numerical and experimental results indicate a redistribution of stresses along the time and damage accumulation of beam which severely affect the serviceability and ultimate capacity of RC beam. The output of the FEM analysis demonstrates good match with the experimental consequences which affirm the efficacy of the computer aided model. The controlled fatigue damage evolution at service fatigue load limits makes the FE model an efficient tool in predicting high cycle fatigue behaviour of RC structures.

• Journal of Ocean Engineering and Technology
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• v.27 no.5
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• pp.63-69
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• 2013

The mooring lines of a floating type offshore plant are known to show wide banded and bimodal responses. These phenomena come from a combination of low and high frequency random load components, which are derived from the drift-restoring motion characteristic and wind- sea, respectively. In this study, fatigue models were applied to predict the fatigue damage of mooring lines under those loads, and the result were compared. For this purpose, seven different fatigue damage prediction models were reviewed, including mathematical formula. A FPSO (floating, production, storage, and offloading) with a $4{\times}4$ spread catenary mooring system was selected as a numerical model, which was already installed at an offshore area of West Africa. Four load cases with different combinations of wave and wind spectra were considered, and the fatigue damage to each mooring line was estimated. The rain flow fatigue damage for the time process of the mooring tension response was compared with the results estimated by all the fatigue damage prediction models. The results showed that both Benasciutti-Tovo and JB models could most accurately predict wide banded bimodal fatigue damage to a mooring system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.140-145
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• 1997

In case of spot-welded joints, the fatigue cracks generally originate from the weld interfaces of the neighborhood nugget tips, and propagate toward the outer surfaces of the sheets. Generally, because fatigue crack was observed in nugget around, strain gage was attached at nugget zone. Accordingly, it was very difficult to detect the generation time of fatigue crack in spot-welded joints and to measure the propagation speed of fatigue crack. We developed the non-destructive method, according to which th fatigue crack propagation rate can be quantitatively estimated by utilizing information obtained from strain gages bonded on the electrode indentations of spot welds. The results measured by real crack were compared with the data which was measured by strain gauge method in fatigue testing. And so fatigue strength was evaluated by stress intensity factor. In this study behavior of fatigue crack propagation under repeated load were considered.

• Journal of Korean Society for Quality Management
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• v.31 no.2
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• pp.165-182
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• 2003

The fatigue has been considered to the most important failure mode where optimal design or reliability prediction of the machinery in aircraft, atomic reactors, and structure systems, etc., is required. When the statistical analysis of fatigue life data is performed, some difficulties are present because of the following facts : nonlinear relationship, heteroscedastic data, large scatter in the data, censored data (runouts), and existence of fatigue limit. To find the S-N curve models that characterize fatigue strength better, this research compares existing fatigue curve models developed recently in terms of the residual mean square and the estimate of fatigue limit, etc. for various fatigue data sets.

• Smart Structures and Systems
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• v.22 no.2
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• pp.193-200
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• 2018

From the viewpoint of engineering applications, the prediction of the failure of bogies plays an important role in preventing the occurrence of fatigue. Fatigue is a complex phenomenon affected by many uncertainties (such as load, environment, geometrical and material properties, and so on). The key to predict fatigue damage accurately is how to quantify these uncertainties. A Bayesian model is used to account for the uncertainty of various sources when predicting fatigue damage of structural components. In spite of improvements in the design of fatigue-sensitive structures, periodic non-destructive inspections are required for components. With the help of modern nondestructive inspection techniques, the fatigue flaws can be detected for bogie structures, and fatigue reliability can be updated by using Bayesian theorem with inspection data. A practical fatigue analysis of welded bogies is utilized to testify the effectiveness of the proposed methods.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.2
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• pp.116-121
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• 2011

The Spectral Fatigue Analysis is representative fatigue life assessment method for vessels. This Analysis is performed generally for the whole vessel and many assessment sites. The spectral fatigue analysis is performed through the process of hydrodynamic response analysis, global structural analysis, local structural analysis and calculation of fatigue damage. In these processes, fatigue damage is affected by many variables. The representative variables are S-N curve data, wave scatter data, wave spectrum, bandwidth effect and etc. In this paper, the effects of these variables to the fatigue damage are analyzed through the spectral fatigue analysis for 170k LNGC.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.225-230
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• 2000

This paper presents the fatigue behavior of composite materials with impact-induced damage. The impact damage parameter is proposed to evaluate the effect of impact damage on fatigue life. Subsequently, a new model is developed to predict the fatigue life of impacted composite materials. Also, a stochastic model is proposed to describe the variation of fatigue life due to the material nonhomogeneity. For these models, the fatigue tests were performed on the unimpacted and impacted composite materials. The effect of impact damage on fatigue life can be characterized by the impact damage parameter. Additionally, the results by the present fatigue life prediction model agree well with experimental results regardless of applied impact energy. Also, the variation of fatigue life can be described by the present stochastic model and is reduced with applied impact energy.

• Composites Research
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• v.12 no.2
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• pp.62-69
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• 1999

During fatigue loading of composite materials, damage accumulation can be monitored by measuring their material properties. In this study, fatigue modulus is used as the damage index. Fatigue life of composite materials may be predicted analytically using damage models which are based on fatigue modulus and resultant strain. Damage models are propesed as funtions of applied stress level, number of fatigue cycle and fatigue life. The predicted life was comparable to the experimental result obtained using E-glass fiber reinforced epoxy resin materials and pultruded glass fiber reinforce polyester composites under two-stress level fatigue loading.

• Journal of the Korean Society of Industry Convergence
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• v.10 no.3
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• pp.143-147
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• 2007

In recents years, the statistical properties has become an important quantity for reliability based design of a component. The effects of the materials and test conditions for parameter estimation in residual strength degradation model are studied in carbon/epoxy laminate. It is shown that the correlation between the experimental results and the theoretical prediction on the fatigue life distribution using the life distribution convergence method is very reasonable.

• International Journal of Highway Engineering
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• v.4 no.2 s.12
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• pp.9-18
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• 2002

The main distresses that influence pavement performance are rutting, fatigue cracking, and longitudinal roughness. Thus, it is important to analyze the factors that affect these three distresses, and to develop prediction models. In this paper, three distress prediction models were developed using DataPave program which stores data from a wide variety of pavement sections In the United States. Also, sensitivity studies were conducted to evaluate how the input variables impact on the distresses. The result of sensitivity study for the prediction model of rutting showed that asphalt content, air void, and optimum moisture content of subgrade were the major factors that affect rutting. The output of sensitivity study for the prediction model of fatigue cracking revealed that asphalt consistency, asphalt content, and air void were the most influential variables. The prediction model of longitudinal roughness indicated asphalt consistency, #200 passing percent of subgrade aggregate, and asphalt content were the factors that affect longitudinal roughness.