• 소성∙가공
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• 제26권3호
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• pp.162-167
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• 2017

The tensile surface residual stress in the multi-pass drawn wire deteriorates the mechanical properties of the wire. Therefore, the evaluation of the residual stress is very important. Especially, the axial residual stress on the wire surface is the highest. Therefore, the objective of this study was to propose an axial surface residual stress prediction model of the multi-pass drawn steel wire. In order to achieve this objective, an elastoplastic finite element (FE) analysis was carried out to investigate the effect of semi-die angle and reduction ratio of the axial surface residual stress. By using the results of the FE analysis, a surface residual stress prediction model was proposed. In order to verify the effectiveness of the prediction model, the predicted residual stress was compared to that of a wire drawing experiment.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권6호
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• pp.661-669
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• 2018

Engineering system problems consist of multi-objective optimisation and the performance analysis is generally time consuming. To optimise the system concerning its performance, many researchers perform the optimisation using an approximation model. The Response Surface Method (RSM) is usually used to predict the system performance in many research fields, but it shows prediction errors for highly nonlinear problems. To create an appropriate metamodel for marine systems, Lee (2015) compares the prediction accuracy of the approximation model, and multi-objective optimal design framework is proposed based on a confirmed approximation model. The proposed framework is composed of three parts: definition of geometry, generation of approximation model, and optimisation. The major objective of this paper is to confirm the applicability/usability of the proposed optimal design framework and evaluate the prediction accuracy based on sensitivity analysis. We have evaluated the proposed framework applicability in derrick structure optimisation considering its structural performance.

• 한국수자원학회논문집
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• 제43권12호
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• pp.1011-1027
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• 2010

모형의 구조, 모델링에 사용되는 자료, 매개변수 등에 포함된 다양한 불확실성 원인들은 수문모의 및 예측결과에 있어 불확실성을 야기한다. 본 연구에서는 강우-유출 및 강우-유사유출 모의가 가능한 분포형 강우-유사-유출 모형을 용담댐 상류유역인 천천유역에 적용하여 수문곡선 및 유사량곡선의 재현성을 평가하고, 다중최적화기법인 MOSCEM을 이용하여 강우-유출 모듈, 강우-유사유출 모듈의 매개변수를 독립적으로 보정한 경우(Case I과 II), 그리고 두 모듈이 결합된 강우-유사-유출 모형의 매개변수를 동시에 보정한 경우(Case III)에 대하여 Pareto 최적해를 추정하고, 이에 따른 수문 예측결과의 불확실성을 평가한다. 매개변수 불확실성의 전이에 따른 수문곡선의 불확실성 평가 결과(Case I), 모의기간 동안 고유량보다는 저유량 부분에서 불확실성 범위가 두드러졌으며, 이에 반해, 유사량곡선의 경우(Case II) 저농도보다는 고농도 부분에서 불확실성 범위가 넓게 분포하였다. 강우-유사-유출 모형의 매개변수의 불확실성을 동시에 추정한 경우 수문곡선 및 유사량곡선 모두 Case I과 II에 비해 모의기간 전반에 걸쳐 불확실성 범위가 넓게 분포되었으며, 매개 변수의 불확실성으로 인해 대상유역내 격자별 침식 및 퇴적 공간분포 양상이 상이하게 나타났다.

• 한국재난정보학회 논문집
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• 제13권4호
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• pp.491-498
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• 2017

본 연구의 주 목적은 연성 도로포장의 소성변형 예측모델을 개발하는 것이다. 목적을 수행하기 위하여 다양한 실험실 시험이 수행되었다. 소성변형 량을 측정하기 위하여 측면 구속압을 제공하는 새로운 반복 일축압축시험이 채택되었으며 소성변형 예측모델은 층별-변형률 이론이 적용되었다. 예측모델의 소성계수는 아스팔트 콘크리트 재료의 소성변형시험을 통하여 결정되었다. 본 연구가 수행된 범위내에서 반복 일축압축시험을 통한 연성포장의 소성변형 예측모델이 제안되었다. 제안된 소성변형 예측모델은 연성포장 층 재료의 거동을 적절하게 모사하는 것으로 나타났다.

• Fibers and Polymers
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• 제6권3호
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• pp.269-276
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• 2005

In this study, cross-cultural comparison of sound sensation for Korean traditional silk fabrics between Korea and America was performed and prediction models for sound sensation by objective measurements including sound parameters such as level pressure of total sound (LPT), Zwicker's psychoacoustic characteristics, and mechanical properties by Kawabata Evaluation System were established for each nation to explore the objective parameters explaining sound sensation of the Korean traditional silk. As results, Koreans felt the silk fabric sounds soft and smooth while Americans were revealed as perceiving them hard and rough. Both Koreans and Americans were pleasant with sounds of Gongdan and Newttong and especially Newttong was preferred more by Americans in terms of sound sensation. In prediction models, some of subjective sensation were found as being related mainly with mechanical properties of traditional silk fabrics such as surface and compressional characteristics.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1187-1192
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• 2008

In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• International Journal of Air-Conditioning and Refrigeration
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• 제10권2호
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• pp.65-71
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• 2002

The objective of this study is to evaluate the design parameters and to develop the cooling and heating load prediction equations of office buildings. The building load calculation simulation was carried out using the DOE-2.1E program. The results of the simulation were used as data for multiple regression analysis which could develop the load prediction equations.

• 설비공학논문집
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• 제13권9호
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• pp.914-921
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• 2001

The objective of this study is to evaluate the design parameters and to develop the cooling and heating load prediction equations of office buildings. The building load calculation simulation was carried out using the DOE-2.1E program. The results of the simulation was used as a data for ANOVA and multiple regression analysis which could develop the load prediction equations.

• Asia-Pacific Journal of Atmospheric Sciences
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• 제54권4호
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• Asia pacific journal of information systems
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• 제15권2호
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• pp.51-63
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• 2005

There has been substantial research into the bankruptcy prediction. Many researchers used the statistical method in the problem until the early 1980s. Since the late 1980s, Artificial Intelligence(AI) has been employed in bankruptcy prediction. And many studies have shown that artificial neural network(ANN) achieved better performance than traditional statistical methods. However, despite ANN's superior performance, it has some problems such as overfitting and poor explanatory power. To overcome these limitations, this paper suggests a relatively new machine learning technique, support vector machine(SVM), to bankruptcy prediction. SVM is simple enough to be analyzed mathematically, and leads to high performances in practical applications. The objective of this paper is to examine the feasibility of SVM in bankruptcy prediction by comparing it with ANN, logistic regression, and multivariate discriminant analysis. The experimental results show that SVM provides a promising alternative to bankruptcy prediction.