• 제목/요약/키워드: Artificial propagation

검색결과 533건 처리시간 0.026초

TIG 용접된 Al6013-T4 알루미늄 합금에서 피로균열전파저항의 변동성에서의 PWHT의 영향 (Effect of PWHT on Variability of fatigue Crack Propagation Resitance in TIG Welded Al 6013-T4 Aluminum Alloy)

  • 구나완;이상열;김선진
    • 동력기계공학회지
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    • 제15권6호
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    • pp.73-80
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    • 2011
  • The experimental investigation focuses on an influence of artificial aging time in longitudinal butt welded Al 6013-T4 aluminum alloy on the fatigue crack growth resistance. The preferred welding processes for this alloy are frequently tungsten inert gas welding (TIG) process due to its comparatively easier applicability and better weldability than other gas metal arc welding. Fatigue crack growth tests were carried out on compact tension specimens (CT) in longitudinal butt TIG welded after T82 heat treatment was varied in three artificial aging times of 6 hours, 18 hours and 24 hours. Of the three artificial aging times, 24 hours of artificial aging time are offering better resistance against the growing fatigue cracks. The superior fatigue crack growth resistance preferred spatial variation of materials within each specimen in the Paris equation based on reliability theory and fatigue crack growth rate by crack length are found to be the reasons for superior fatigue resistance of 24 hours of artificial aging time was compared to other joints. The highest of crack propagation resistance occurs in artificial aging times of 24 hours due to the increase in grain size (fine grained microstructures).

표면파의 수치해석을 위한 인공지능 엔진 개발 (Artificial Intelligence Engine for Numerical Analysis of Surface Waves)

  • 곽효경;김재홍
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2006년도 정기 학술대회 논문집
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    • pp.89-96
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    • 2006
  • Nondestructive evaluation using surface waves needs an analytical solution for the reference value to compare with experimental data. Finite element analysis is very powerful tool to simulate the wave propagation, but has some defects. It is very expensive and high time-complexity for the required high resolution. For those reasons, it is hard to implement an optimization problem in the actual situation. The developed engine in this paper can substitute for the finite element analysis of surface waves propagation, and it accomplishes the fast analysis possible to be used in optimization. Including this artificial intelligence engine, most of soft computing algorithms can be applied on the special database. The database of surface waves propagation is easily constructed with the results of finite element analysis after reducing the dimensions of data. The principal wavelet-component analysis is an efficient method to simplify the transient wave signal into some representative peaks. At the end, artificial neural network based on the database make it possible to invent the artificial intelligence engine.

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한국산 자생 상사화(Lycoris squamigera MAX.)의 효과적인 번식방법 (Effective and Economical Propagation Method of Lycoris squamigera Native to Korea)

  • 박윤점;허북구;정소영;정재호;안민실
    • 원예과학기술지
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    • 제16권2호
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    • pp.242-243
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    • 1998
  • 상사화에 chipping, half-chipping, twin-scaling, coring, scooping 및 notching을 실시하여 번식능력과 1인1일구근처리량을 조사하여 가장 경제적인 인공번식법을 구명하고자 본 실험을 실시하였다. 번식능력의 경우 twin-scaling에 의해 1구당 42.19개의 가장 많은 자구를 얻었고 다음은 half-chipping (23.2개) > chipping(18.2개) > notching(14.3개) 순이었으며, coring과 scooping에 의해서는 평균 1개의 자구를 얻어 전혀 효과적인 인공번식법이 아님이 확인되었다. 이상의 결과에서 twin-scaling의 경우 일시에 많은 개체를 얻을 수 있었으나 하루에 200구 정도 작업이 가능하여 번식작업에 가장 많은 시간이 소요되었고 형성된 자구도 매우 작았다. 그러나 chipping의 경우는 하루에 480구 정도로 다른 인공번식법에 비해 가장 많은량을 작업할 수 있었고 또 자구도 비교적 큰 것을 얻을 수 있었으며, 유일하게 기계화가 가능하므로 가장 경제적인 인공번식법으로 판단되었다.

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ARIMA 모형과 인공신경망모형의 BOD예측력 비교 (Comparison of the BOD Forecasting Ability of the ARIMA model and the Artificial Neural Network Model)

  • 정효준;이홍근
    • 한국환경보건학회지
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    • 제28권3호
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    • pp.19-25
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    • 2002
  • In this paper, the water quality forecast was performed on the BOD of the Chungju Dam using the ARIMA model, which is a nonlinear statistics model, and the artificial neural network model. The monthly data of water quality were collected from 1991 to 2000. The most appropriate ARIMA model for Chungju dam was found to be the multiplicative seasonal ARIMA(1,0,1)(1,0,1)$_{12}$, model. While the artificial neural network model, which is used relatively often in recent days, forecasts new data by the strength of a learned matrix like human neurons. The BOD values were forecasted using the back-propagation algorithm of multi-layer perceptrons in this paper. Artificial neural network model was com- posed of two hidden layers and the node number of each hidden layer was designed fifteen. It was demonstrated that the ARIMA model was more appropriate in terms of changes around the overall average, but the artificial neural net-work model was more appropriate in terms of reflecting the minimum and the maximum values.s.

Levenberg-Marquardt 알고리즘의 지반공학 적용성 평가 (Evaluation for Applications of the Levenberg-Marquardt Algorithm in Geotechnical Engineering)

  • 김영수;김대만
    • 한국지반환경공학회 논문집
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    • 제10권5호
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    • pp.49-57
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    • 2009
  • 본 연구에서는 Levenberg-Marquardt(LM) 알고리즘 인공신경망을 통하여 지반공학 문제 중의 하나인 압축지수를 예측하였고, 예측된 결과는 현재 지반공학에 널리 사용되고 있는 Back Propagation(BP) 알고리즘 인공신경망의 예측 결과와 비교하여 LM 알고리즘의 지반공학 적용성을 평가하였다. 또한 두 알고리즘에 의한 예측치는 기존에 제안된 압축지수의 경험식들에 의하여 산정된 결과들과 비교를 통하여 예측결과의 정확성을 확인하였다. 경험식에 의한 압축지수의 산정치는 전반적으로 BP 알고리즘과 LM 알고리즘 인공신경망에 의한 예측치에 비하여 더 큰 오차를 나타냈다. LM 알고리즘에 의한 압축지수의 예측치는 BP 알고리즘의 예측치와 비교할 때 정확도는 비슷하나 수렴속도에서 더 좋은 결과를 보여 LM 알고리즘의 지반공학 적용성은 우수한 것으로 나타났다.

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오류역전파 알고리즘을 이용한 최적 사출설형 냉각시스템 설계 (Optimum Cooling System Design of Injection Mold using Back-Propagation Algorithm)

  • 태준성;최재형;이병옥
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 2009년도 춘계학술대회 논문집
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    • pp.357-360
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    • 2009
  • The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. In this research, we tried the back-propagation algorithm of artificial neural network to find an optimum solution in the cooling system design of injection mold. The cooling system optimization problem that was once solved by a response surface method with 4 design variables was solved by applying the back-propagation algorithm, resulting in a solution with a sufficient accuracy. Furthermore the number of training points was much reduced by applying the fractional factorial design without losing solution accuracy.

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인공슬롯을 고려한 수압파쇄 균열의 발전양상에 관한 연구 (The Analysis of Fracture Propagation in Hydraulic Fracturing using Artificial Slot Model)

  • 최성웅;이희근
    • 터널과지하공간
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    • 제5권3호
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    • pp.251-265
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    • 1995
  • One of the most important matters in stress measurement by hydraulic fracturing technique is the determination of the breakdown pressure, reopening pressure, and shut-in pressure, since these values are the basic input data for the calculation of the in-situ stress. The control of the fracture propagation is also important when the hydraulic fracturing technique is applied to the development of groundwater system, geothermal energy, oil, and natural gas. In this study, a laboratory scale hydraulic fracturing device was built and a series of model tests were conducted with cube blocks of Machon gabbro. A new method called 'flatjack method' was adopted to determine shut-in pressure. The initial stress calculated from the shut-in pressure measured by flatjack method showed much higher accuracy than the stress determined by the conventional method. The dependency of the direction of fracture propagation on the state of the initial stresses was measured by introducin g artificial slots in the borehole made by water jet system. Numerical modeling by BEM was also performed to simulate the fracture propagation process. Both results form numerical and laboratory tests showed good agreement. From this study which provides the extensive results on the determination of shut-in pressure and the control of fracture propagation which are the critical issue in the recent hydraulic fracturing, it is conclued that in-situ stress measurement and the control of fracture propagation could be achived more accurately.

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인공신경망을 이용한 평면파괴 안정성 예측 (A Prediction of the Plane Failure Stability Using Artificial Neural Networks)

  • 김방식;이성기;서재영;김광명
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2002년도 가을 학술발표회 논문집
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    • pp.513-520
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    • 2002
  • The stability analysis of rock slope can be predicted using a suitable field data but it cannot be predicted unless suitable field data was taken. In this study, artificial neural networks theory is applied to predict plane failure that has a few data. It is well known that human brain has the advantage of handling disperse and parallel distributed data efficiently. On the basis of this fact, artificial neural networks theory was developed and has been applied to various fields of science successfully In this study, error back-propagation algorithm that is one of the teaching techniques of artificial neural networks is applied to predict plane failure. In order to verify the applicability of this model, a total of 30 field data results are used. These data are used for training the artificial neural network model and compared between the predicted and the measured. The simulation results show the potentiality of utilizing the neural networks for effective safety factor prediction of plane failure. In conclusion, the well-trained artificial neural network model could be applied to predict the plane failure stability of rock slope.

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오류역전파 알고리즘을 이용한 사출성형 금형 냉각회로 최적화 (Injection Mold Cooling Circuit Optimization by Back-Propagation Algorithm)

  • 이병옥;태준성;최재혁
    • 한국생산제조학회지
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    • 제18권4호
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    • pp.430-435
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    • 2009
  • The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. The cooling circuit optimization problem that was once solved by a response surface method with 4 design variables. It took too much time for the optimization as an industrial design tool. It is desirable to reduce the optimization time. Therefore, we tried the back-propagation algorithm of artificial neural network(BPN) to find an optimum solution in the cooling circuit design in this research. We tried various ways to select training points for the BPN. The same optimum solution was obtained by applying the BPN with reduced number of training points by the fractional factorial design.

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인공추간판의 피로하중 모드에 따른 슬라이딩 코어의 피로균열전파 거동 (Fatigue Crack Propagation of Sliding Core in Artificial Intervertebral Disc due to the Fatigue Loading Mode)

  • 김철웅;강봉수
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2006년도 춘계학술대회 논문집
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    • pp.367-368
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    • 2006
  • Today, the Artificial Intervertebral Disc (AID) is being developed by increasing the oblique of the endplate gradually. In other words, Ultra-high Molecular Weight Polyethylene (UHMWPE) which is apply to the sliding core of the AID, does not change the shape but alters the oblique of endplate. However, the unreasonable increase of degree of freedom (DOF) can result in the aggravation of the bone fusion and the initial stability and it can also lead to the increase of the concentrated force in core. For these reasons, it is necessary to develop the advanced techniques, which choose the most adequate DOF. In this study, the new optimized modeling of the sliding core and the endplate, the fatigue characteristics, the crack propagation and the formation mechanism of wearing debris was studied and the minimizing technique will be derived from this research.

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