• 대한기계학회논문집A
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• 제28권11호
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• pp.1813-1821
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• 2004

Until now, the 40% of wall thickness criterion, which is generally used for the plugging of steam generator tubes, has been applied only to a single cracked geometry. In the previous study by the authors, a total number of 9 local failure prediction models were introduced to estimate the coalescence load of two collinear through-wall cracks and, then, the reaction force model and plastic zone contact model were selected as the optimum ones. The objective of this study is to estimate the coalescence load of two collinear through-wall cracks in steam generator tube by using the optimum local failure prediction models. In order to investigate the applicability of the optimum local failure prediction models, a series of plastic collapse tests and corresponding finite element analyses for two collinear through-wall cracks in steam generator tube were carried out. Thereby, the applicability of the optimum local failure prediction models was verified and, finally, a coalescence evaluation diagram which can be used to determine whether the adjacent cracks detected by NDE coalesce or not has been developed.

• 대한전기학회논문지:전력기술부문A
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• 제49권3호
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• pp.107-117
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• 2000

This paper proposes a systematic method to develop short-term electrical load forecasting systems using neuro-fuzzy models. The primary goal of the proposed method is to improve the performance of the prediction model in terms of accuracy and reliability. For this, the proposed method explores the advantages of the structure learning of the neuro-fuzzy model. The proposed load forecasting system first builds an initial structure off-line for each hour of four day types and then stores the resultant initial structures in the initial structure bank. Whenever a prediction needs to be made, the proposed system initializes the neuro-fuzzy model with the appropriate initial structure stored and trains the initialized model. In order to demonstrate the viability of the proposed method, we develop an one hour ahead load forecasting system by using the real load data collected during 1993 and 1994 at KEPCO. Simulation results reveal that the prediction system developed in this paper can achieve a remarkable improvement on both accuracy and reliability compared with the prediction systems based on multilayer perceptrons, radial basis function networks, and neuro-fuzzy models without the structure learning.

• 전기학회논문지
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• 제63권11호
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• pp.1608-1614
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• 2014

Power demand forecasting is an important factor of the peak management. This paper deals with the 15 minutes ahead load forecasting problem in a DC urban railway system. Since supplied power lines to trains are connected with parallel, the load characteristics are too complex and highly non-linear. The main idea of the proposed method for the 15 minutes ahead prediction is to use the daily load similarity accounting for the load nonlinearity. An Euclidean norm with weighted factors including loads of the neighbor substation is used for the similar load selection. The prediction value is determinated by the sum of the similar load and the correction value. The correction has applied the neural network model. The feasibility of the proposed method is exemplified through some simulations applied to the actual load data of Incheon subway system.

• Smart Structures and Systems
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• 제24권4호
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• pp.507-524
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• 2019

A Bayesian dynamic linear model (BDLM) is presented for a data-driven analysis for response prediction and load effect separation of a revolving auditorium structure, where the main loads are self-weight and dead loads, temperature load, and audience load. Analyses are carried out based on the long-term monitoring data for static strains on several key members of the structure. Three improvements are introduced to the ordinary regression BDLM, which are a classificatory regression term to address the temporary audience load effect, improved inference for the variance of observation noise to be updated continuously, and component discount factors for effective load effect separation. The effects of those improvements are evaluated regarding the root mean square errors, standard deviations, and 95% confidence intervals of the predictions. Bayes factors are used for evaluating the probability distributions of the predictions, which are essential to structural condition assessments, such as outlier identification and reliability analysis. The performance of the present BDLM has been successfully verified based on the simulated data and the real data obtained from the structural health monitoring system installed on the revolving structure.

• 한국지능시스템학회논문지
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• 제14권5호
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• pp.533-538
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• 2004

본 논문은 뉴로-퍼지 모델의 구조 학습을 이용하여 단기 전력 수요 예측시스템을 개발하기 위한 체계적인 방법을 제안한다. 제안된 단기 수요 예측시스템은 1시간, 24시간, 168시간의 예측 리드 타임을 갖고 예측을 수행하기 위해서 요일 유형과 시간 별로 총 96개의 초기 구조를 미리 생성하고, 이를 초기 구조 뱅크에 저장한다. 예측이 수행되는 시점에 해당하는 초기구조를 선택하여 뉴로-퍼지 모델을 초기화하고, 학습하고, 예측을 수행한다. 제안된 예측시스템은 단지 2개의 입력 변수만을 이용하기 때문에 간단한 모델 구조를 가질 뿐 아니라 학습된 퍼지 규칙을 해석하는 것이 매우 용이하다는 장점을 갖는다. 제안된 방법의 실효성을 검증하기 위해 1996년과 1997년의 한극전력의 실제 전력 수요 데이터를 이용하여 1시간, 24시간, 168시간 앞의 전력 수요를 예측하는 모의 실험을 수행한다. 실험 결과 제안된 방법은 단지 2개의 입력 변수를 사용함에도 불구하고, 기존의 예측 방법과 비교하여 예측의 정확도와 신뢰도 측면에서 우수한 성능을 얻는다.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 춘계학술발표대회 논문집
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• pp.304-310
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• 2008

Currently energy use planning council system is mandatory especially for the urban development project planned on a specified scale or more. The goal of existing demand prediction was to calculate the maximum load by multiplying energy load per unit area by building size. The result of this method may be exaggerated and has a limit in the information of period load. The paper suggests a new forecasting process based on standard unit household in order to upgrade the limit in demand prediction method of multi-family housing complex. The new process was verified by comparing actual using amount of multi-family housing complex to forecasting value of energy use plan.

• 소성∙가공
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• 제18권4호
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• pp.323-328
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• 2009

The prediction of drawing load is very important in the drawing process. However, it is not easy to calculate the drawing load for the shape drawing process through a theoretical model because of a complex arbitrary final cross section shape. The purpose of this study is to predict drawing load in shape drawing process. The cross section of product is divided with small angle as much as similar with fan-shape. The drawing load of each section was calculated by theoretical model of round to round drawing process. And the shape drawing load was determined by summation of drawing load of each section. The effectiveness of the proposed method was verified through the FE analysis and shape drawing experiment. It had a good agreement between proposed method, FE analysis and experiment within about 3% errors.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.2049-2056
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• 2011

The reinforced-roadbed materials composed of crushed stones are used for preventing vertical deformation and reducing impact load caused by highspeed train. Repeated load application can induce deformation in the reinforced-roadbed layer so that it causes irregularity of track. Thus it is important to understand characteristics of permanent deformation in the reinforced-subbase materials. The characteristics of permanent deformation can be simulated by prediction model that can be obtained by performing repetitive triaxial test. The prediction model of permanent deformation is a key-role in construction of design method of track. The prediction model of permanent deformation is represented in usual as the hyperbolic function with increase of number of load repetition. The prediction model is sensitive to many factors including stress level etc. so that it is important to define parameters of the model as clearly as possible. Various data obtained from repetitive triaxial test and resonant column test using the reinforced-roadbed of crushed stone are utilized to develop a new prediction model based on concept of shear-stress ratio and elastic modulus. The new prediction model of permanent deformation can be adapted for developing design method of track in the future.

• 한국음향학회지
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• 제33권3호
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• pp.153-162
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• 2014

경험적 음향하중 예측 방법은 우주 발사체 상단 페어링에 가해지는 음향하중을 예측하는 방법으로 상사성 원리를 기반으로 한 제트 실험 데이터를 기반으로 한다. 대표적인 경험적 예측기법인 DSM-II(Distributed Source Method-II)는 제트 화염 축을 따라 소음원을 배치하는 방법이다. 그러나 이러한 경험적 예측 모델은 자유제트 실험 결과를 기반으로 하였기 때문에 실제 상황에 존재하는 충돌 소음원을 고려하기 어렵다는 한계가 있다. 따라서 본 논문에서는 기존 예측 방법에 충돌 소음원을 추가 배치함으로써 충돌 제트 효과를 반영하는 예측 방법을 제안하였다. 이를 위하여 소음원의 위치, 스펙트럼, 세기, 방향성 특징을 고려하였으며 KSR-III(Korean Sounding Rocket-III) 로켓에 대한 음향 하중 예측 결과를 기존 예측 방법 및 실험 결과와 비교하였다.

• 한국농공학회지
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• 제42권
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• pp.68-77
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• 2000

Analyses, in which load was regarded as instant load and gradual step load, respectively, were performed with data measured on a gradually loaded field, and the results were inspected to find the effect of load conditions, and the final settlements which were predicted by Hyperbolic, Tan's, Asaoka's, and Monden's methods were compared with each other. Settlement curves in which load was regarded as instant load and gradual step load being to coincide at twice the time of duration of embankment. On the ground installed vertical drain, from the results of Hyperbolic, Tan's, Asaoka's, Monden's, Curve fitting I, and Curve fitting II (simple, carrillo) methods it was concluded that Asaoka, Curve fitting I, and Curve fitting II methods are reliable for prediction final settlement with back analysis.