• Journal of Biosystems Engineering
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• 제34권5호
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• pp.325-330
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• 2009

This study was performed to develop accelerated life test methods for agricultural tractor transmission receiving variable load. To acquire parameters for calculation of accelerated life test, endurance tests were performed under different torque conditions. Test results showed that the shape factor of Weibull distribution was 1.5 and fatigue damage exponent was 5.4. The calculated test time was 5,877 hours under the conditions of average life (MTBF) 3,000 hours and 90% reliability for one test sample. According to the linear cumulative damage rule, test time could be reduced using increased test load. Test time could be reduced by 252 hours when 1.2 times of the rated load compared with 0.67 times of the rated equivalent load calculated by load spectrum of the agricultural tractor. Calculated acceleration coefficient was 23.3.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.166-169
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• 2004

A fatigue test was used to evaluate the fatigue life of an actual structure. The loaded state and the constraint condition of an actual structure must be same as the specimen in order to apply the test results to an actual structure by the specimen. The loaded state and constraint conditions can't be same as the specimen in the actual structure which is complicated. In order to reduce these differences, an actual structure test with a lot of frequencies is need to get a fatigue life curve. Therefore, ten sets of accelerated test units which attached unbalanced mass were composed in this study. Acceleration history about the vibration of an actual structure was acquired. Rainflow counting was used on acceleration history, and the life curve return formula was assumed. The return formula that damage satisfied `1' was acquired in a feedback process by the Miner's rule, which was the linear cumulative damage theory. A conservative fatigue life curve was determined with a return formula to have been presumed by each set. The fatigue life of regular rpm condition was calculated by these conservative fatigue life curves.

• 한국해양공학회지
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• 제9권2호
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• pp.98-111
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• 1995

High temperature low cycle fatigue shows that cycle-dependent crack growth owing to cyclic plastic deformation occurred simultaneosly with time-dependent crack growth owing to intergranular deformation. Consequently, to estimate crack growth rate uniquely, many to investigators have proposed various kinds of parameters and theories but these could not produce satisfactory results. Therefore the goal of this study is focused on prediction of crack growth rate using predominant damage rule, linear cumulative damage rule and transitional parameter ${\Delta}J_c/{\Delta}J_f$. On the basis of these sinusoidal loading waveform at 600$^{\circ}C$ and 700$^{\circ}C$.

• 한국산학기술학회논문지
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• 제15권1호
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• pp.47-54
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• 2014

선체 내구성은 기존 선급 규격에 의하여 구조 치수를 결정한 후 이러한 치수의 선체구조에 대하여 스펙트랄과 결정론적 및 간이 방법에 의하여 평가되고 있다. 이러한 방법은 선체재료를 선급 규격에서 제안하고 있는 재료로 구성하는 경우에는 적용할 수 있으나 선체 재료를 신소재로 구성하는 경우에는 적용할 수 없다. 따라서 본 연구에서는 폴리에틸렌 보트 선체에 대한 피로 손상을 평가하기 위하여 선체에 부하되는 단기간 선체 가속도를 직접 측정하고 이러한 데이터를 기초로 구조설계와 피로수명평가방법이 확립되지 못한 소형 선박의 선체 내구성을 선형누적손상 법칙으로 평가하는 방법을 제안하였다. 개발된 폴리에틸렌 보트의 경우 최대 가속도 상태에서 보트에 부하되는 최대 Von-Mises 응력은 1.8MPa로서 $1{\times}10^9$ 사이클 피로강도 5.9MPa 아래에 있고 유한피로수명개념을 적용한 폴리에틸렌 보트의 내구수명은 415년으로 평가되어져 거의 무한수명을 가지고 있다.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.