• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 추계학술대회 논문집
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• pp.1203-1208
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• 2005

This study is the evaluation of rating of railway prestressed concrete beam bridges by prediction of residual effective prestress force. Therefore, developed prediction method is based on the center camber of prestressed concrete beam, structural design report of various PSC beams, construction reference materials of PSC beams. Both rating evaluation and residual effective prestress force by developed method is compared with evaluation by structural design. This comparison results shows that this developed method is very effective method. Therefore evaluation of rating by prediction of residual effective prestress force will be used for evaluation of the rating of railway PSC beam bridges.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 가을 학술발표회 논문집
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• pp.377-384
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• 2000

The characteristics and prediction model of the shear strength for unsaturated residual soils was studied. In order to investigate the influence of the initial water content on the shear strength, unsaturated triaxial tests were carried out varying the initial water content, and the applicability of existing prediction models for the unsaturated shear strength was testified. It was shown that the soil - water characteristic curve and the shear strength of the unsaturated soil varied with the change of the initial water content. A sample compacted in the lower initial water content needs a higher suction to get the same degree of saturation while the shear strength of a sample with the lower initial water content displays a lower value. In order to apply the existing prediction models of the unsaturated shear strength to granite residual soils, a correction coefficient, α, on the internal friction angle, ø'was added.

• 대한기계학회논문집A
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• 제33권1호
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• pp.72-81
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• 2009

This paper provides simulational round robin test results for welding residual stress prediction of safety/relief nozzle. To quantify the welding variables and define the recommendation for prediction and determination of welding residual stress, 6 partners in 5 institutes participated in round robin test. It is concluded that compressive axial and hoop residual stress occurs in dissimilar metal weld and pre-existing residual stress distribution in dissimilar metal weld was affected by similar metal weld due to short length of safe end. Although the reason for the deviation among the results was not pursued further, the effect of several key elements of FE analyses on welding residual stress was investigated in this paper.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.79-82
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• 2008

In this paper, results of simulational round robin test on residual stress prediction was provided. Welding residual stress is one of the reasons for primary water stress corrosion cracking in PWR. Therefore, quantifying the welding variables and defining the recommendation for prediction welding residual stress is important. Through the round robin test, it is known that compressive axial and hoop residual stress occurs in dissimilar metal weld and pre-existing residual stress distribution in dissimilar metal weld was affected by similar metal weld due to short length of safe end.

• IEIE Transactions on Smart Processing and Computing
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• 제2권6호
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• pp.345-349
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• 2013

This paper proposes a simplified generalized residual prediction (GRP) that reduces the computational complexity of spatial scalability in scalable high efficiency video coding (SHVC). GRP is a coding tool to improve the inter prediction by adding a residual signal to the inter predictor. The residual signal was created by carrying out motion compensation (MC) of both the enhancement layer (EL) and up-sampled reference layer (RL) with the motion vector (MV) of the EL. In the MC process, interpolation of the EL and the up-sampled RL are required when the MV of the EL has sub-pel accuracy. Because the up-sampled RL has few high frequency components, interpolation of the up-sampled RL does not give significantly new information. Therefore, the proposed method reduces the computational complexity of the GRP by skipping the interpolation of the up-sampled RL. The experiment on SHVC software (SHM-2.0) showed that the proposed method reduces the decoding time by 10 % compared to conventional GRP. The BD-rate loss of the proposed method was as low as 1.0% on the top of SHM-2.0.

• 한국지반환경공학회 논문집
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• 제9권3호
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• pp.17-28
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• 2008

본 연구에서는 상수도 금속관의 공식특성에 따른 잔존 인장강도 예측모델을 제안하였다. 이들 모델중 회주철관에 대해서는 지수함수형 모델이 실측값에 대한 예측값의 상관성($R^2$)이 높게 나타났으며, 닥타일주철관과 강관 등은 선형함수인 공식특성에 따른 강도손실 모델이 더 예측력이 높은 것으로 나타났다. 국내에서 과거에 제조된 상수도 금속관의 파괴인성은 평균적으로 회주철관이 $40.46kgf/mm^2{\sqrt{mm}}$, 닥타일주철관이 $85.27kgf/mm^2{\sqrt{mm}}$, 그리고 강관이 $97.27kgf/mm^2{\sqrt{mm}}$로 나타났으며, 파괴인성을 이용한 잔존 인장강도 예측모델의 실측값에 대한 예측값의 상관성은 관종에 따라 다르나 0.44에서 0.86로 나타났다. 특히 이들 제안된 모델들을 새로운 지역에 매설된 상수관로에 대하여 적용한 결과, 결정계수가 0.76~0.78로 나타나 향후 노후 상수도 금속관의 잔존 강도를 예측하는데 활용됨으로서 합리적인 개대체 의사결정에도 도움을 줄 수 있을 것으로 판단된다.

• Structural Engineering and Mechanics
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• 제56권2호
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• pp.201-221
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• 2015

The fatigue damage problems are frequently encountered in the design of civil engineering structures. A realistic and accurate fatigue life prediction is quite essential to ensure the safety of engineering design. However, constructing a reliable fatigue life prediction model can be quite challenging. The use of traditional deterministic approach in predicting the fatigue life is sometimes too dangerous in the real practical designs as the method itself contains a wide range of uncertain factors. In this paper, a new fatigue life prediction method is going to be proposed where the residual strength is been utilized. Several cumulative damage models, capable of predicting the fatigue life of a structural element, are considered. Based on Miner's rule, a randomized approach is developed from a deterministic equation. The residual strength is used in a one to one transformation methodology which is used for the derivation of the fatigue life. To arrive at more robust results, fuzzy sets are introduced to model the parameter uncertainties. This leads to a convoluted fuzzy based fatigue life prediction model. The developed model is illustrated in an example analysis. The calculated results are compared with real experimental data. The applicability of this approach for a required reliability level is also discussed.

• 소성∙가공
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• 제25권1호
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• pp.61-66
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• 2016

In the current study, we present a new model for the prediction of the strip profile and the residual stresses. This new approach is an analytical model that predicts the residual stresses from the effect of post-deformation. Since the residual stress cannot exceed the yield strength of the material, post-yielding may possibly occur in the post-deformation zone prior to the strip reaching the steady-state zone. The prediction accuracy of the proposed model is examined through comparison with the predictions from 3-D finite element (FE) simulations.

• 한국음향학회지
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• 제21권6호
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• pp.522-530
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• 2002

본 논문에서는 선형 예측 후에 얻어지는 잔차 신호 (residual signal)를 신경 회로망에 바탕을 둔 비선형 예측기로 예측하는 방법을 제안하였다. 신경 회로망을 이용한 예측 방법의 타당성을 입증하기 위해, 먼저 선형 장구간 예측기와 신경 회로망이 도입된 비선형 장구간 예측기의 성능을 서로 비교하였다. 그리고 비선형 예측 후의 잔차 신호를 양자화 하는 과정에서 발생하는 양자화 오차의 영향에 대해 분석하였다. 제안된 신경망 예측기는 예측 오차뿐만 아니라 양자화의 영향을 함께 고려하였으며, 양자화오차에 대한강인성을 갖게 하기 위하여 쿤-터커 (Kuhn-Tucker) 부등식 조건을 만족하는 제한조건 역전파 알고리즘을 새로이 제안하였다. 실험 결과, 제안된 신경망 예측기는 제한조건을 갖는 학습 알고리즘을 사용했음에도 불구하고, 예측 이득이 크게 뒤떨어지지 않는 성능을 나타내었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.482-487
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• 1993

A prediction method for determining the welding residual stress by artificial neural network is proposed. A three-dimensional transient thermomechanical analysis has been performed for the CO $_{2}$ Arc Welding using the finite element method. The validity of the above results is demonstrated by experimental elastic stress relief method which is called Holl Drilling Method. The first part of numarical analysis performs a three-dimensional transient heat transfer anslysis, and the second part then uses results of the first part and performs a three-dimensional transient thermo-clasto-plastic analysis to compute transient and residual stresses in the weld. Data from the finite element method were used to train a backpropagation neural network to predict residual stress. Architecturally, the finite element method were used to train a backpropagation voltage and the current, a hidden layer to accommodate failure mechanism mapping, and an output layer for residual stress. The trained network was then applied to the prediction of residual stress in the four specimens. The results of predicted residual stress have been very encouraging.