• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.11
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• pp.1315-1321
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• 2013

This study presents a prognostic technique for the damage state of a ball bearing. A stochastic bearing fatigue defect-propagation model is applied to estimate the damage progression rate. The damage state and the time to failure are computed by using RMS data from noisy acceleration signals. The parameters of the stochastic defect-propagation model are identified by conducting a series of run-to-failure tests for ball bearings. A regularized particle filter is applied to predict the damage progression rate and update the degradation state based on the acceleration RMS data. The future damage state is predicted based on the most recently measured data and the previously predicted damage state. The developed method was validated by comparing the prognostic results and the test data.

• Journal of the Korea Concrete Institute
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• v.13 no.4
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• pp.389-396
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• 2001

This paper presents an analytical prediction of the fatigue behavior of reinforced concrete bridge piers under earthquake. Material nonlinearity is taken into account by comprising tensile, compressive and shear models of cracked concrete and a model of reinforcing steel. The smeared crack approach is incorporated. In boundary plane at which each member with different thickness is connected, local discontinuous deformation due to the abrupt change in their stiffness can be taken into account by introducing interface element. The effect of number of load reversals with the same displacement amplitude has been also taken into account to model the reinforcing steel. The proposed numerical method for fatigue behavior of reinforced concrete bridge piers under earthquake will be verified by comparison with reliable experimental results.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.74-82
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• 1998

To evaluate the reliability against fatigue failure of offshore structures, a fatigue reliability analysis model based on the probabilistic approach has been developed. In this model, the simplified method is adopted as a fatigue analysis method. The uncertainties included in the fatigue analysis are considered as random variables and their statistical properties are evaluated as quantitatively as possible using existing data. As an example, the developed fatigue reliability model is applied to the jacket. And then the relative significance of each uncertainty on the probability of fatigue failure is surveyed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.6
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• pp.757-762
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• 2010

Owing to the high specific strength and stiffness of composite materials, they are extensively used in mechanical systems and in vehicle industries. However, most mechanical structures experience repeated load and fatigue. Therefore, it is important to perform fatigue analysis of fiber-reinforced composites. The properties of composite laminates vary depending upon the stacking sequence and stacking direction. Fatigue damage of composite laminates occurs according to the following sequence: matrix cracking, delamination, and fiber breakage. In this study, fatigue tests were performed for damage analysis. Fatigue damages, which have to be considered in fatigue analysis, are determined by using the stiffness values calculated from hysteresis loops, and the obtained fatigue damage curve is examined using Mao's equation and Abdelal's equation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2828-2835
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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 will 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1452-1460
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• 2001

A new method of parameter determination in the fatigue residual strength degradation model is proposed. The new method and minimization technique is compared experimentally to account for the effect of tension-compression fatigue loading of spheroidal graphite cast iron and graphite/epoxy laminate. It is shown that the correlation between the experimental results and the theoretical prediction on the fatigue life and residual strength distribution using the proposed method is very reasonable. Therefore, the proposed method is more adjustable in the determination of the parameter than minimization technique for the prediction of the fatigue characteristics.

• Journal of Aerospace System Engineering
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• v.3 no.4
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• pp.27-34
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• 2009

This paper deals with the lifetime prediction of Aircraft Flaperon Joint made of AISI 4130 steel. Reviews are performed on the published damage models at first. And three different damage models are used for predicting the fatigue life of the structure subjected to variable amplitude fatigue loading. These models require no increase in complexity of use, nor do they require additional material property or mission loading information to achieve the improved accuracy. Finally a comparison among the fatigue results is performed. It is observed that the Miner's rule could predict longer life than other cumulative damage models which take into account loads below the endurance limit.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.611-617
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• 2010

A complex system involves a large number of design variables, and its operation is non-linear. To explore the characteristics in its design space, a Kriging meta-model can be utilized; this model has replaced expensive computational analysis that was performed in traditional parametric design optimization. In this study, a Kriging meta-model with a computational orthogonal array for the design of experiments was developed to optimize the fatigue life of a turbine blade whose behavior under cyclic rotational loads is significantly non-linear. The results not only show that the maximum fatigue life is improved but also indicate that the accuracy of computational analysis is achieved. In addition, the robustness of the results obtained by six-sigma optimization can be verified by comparison with the results obtained by performing Monte Carlo simulations.

• Journal of Technology Innovation
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• v.20 no.2
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• pp.49-74
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• 2012

In this study we analyzed factors affecting the life cycle of technology, quantified the evaluation criteria that will affect the life of the individual technologies, and finally proposed the improvements to calculate technology life cycle that the properties of individual technologies are reflected based on cited-patent life time(CLT). It is expected that the methodology proposed improves the limits of the existing standard model, presents more reasonable criteria and ease of persuasion on the results derived by appraisers, and finally gives a lot of the feasibility and the usability of technology life cycle derived by the improved method to appraisers.

• Ecology and Resilient Infrastructure
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• v.3 no.3
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• pp.189-200
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• 2016

The species distribution model would be a useful tool for understanding how invasive alien species spread over the country and what environmental variables contribute to their distributions. This study is focused on the potential distribution of two invasive alien species, the common ragweed (Ambrosia artemisiifolia) and knotgrass (Paspalum distichum) in the Korean Peninsula. The maximum entropy (Maxent) model was used for the prediction of their distribution by inferring their climatic environmental requirements from localities where they are currently known to occur. We obtained their presence data from the Global Biodiversity Information Facility and the Korean plant species databases and bioclimatic data from the WorldClim dataset. As a results of the modelling, the potential distribution predicted by global occurrence data was more accurate than that by native occurrence data. The variables determining the common ragweed distribution were precipitation of the driest month and annual mean temperature. Both annual and the coldest quarter mean temperatures were critical factors in determining the knotgrass distribution. The Maxent model could be a useful tool for the prediction of alien species invasion and the management of their expansion.