• 대한조선학회지
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• 제23권3호
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• pp.10-16
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• 1986

This paper deals with a simple, approximate formula to predict the natural frequencies of the sagged cable structures. Assuming that the propagation velocity of the lateral wave is dependent only on the local mass per unit length and local tension, the explicit simple formula to predict the fundamental period is newly derived. The modified form of these formula is also presented for the prediction of the fundamental period of general shaped cable structures. The results of comparison shows fairly good agreements with experimental results and with theoretical ones. This formula is also used to predict the natural frequencies of a long vertical cable and the derived approximate formula in that case, becomes identical to the exact solution.

• Structural Engineering and Mechanics
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• 제34권2호
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• pp.159-174
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• 2010

Elastic buckling load of perforated steel plates is typically predicted using the finite element or conjugate load/displacement methods. In this paper an artificial neural network (ANN)-based formula is presented for the prediction of the elastic buckling load of rectangular plates having a circular cutout. By using this formula, the elastic buckling load of perforated plates can be calculated easily without setting up an ANN platform. In this study, the center of a circular cutout was chosen at different locations along the longitudinal x-axis of plates subjected to linearly varying loading. The results of the finite element method (FEM) produced by the commercial software package ANSYS are used to train and test the network. The accuracy of the proposed formula based on the trained ANN model is evaluated by comparing with the results of different researchers. The results show that the presented ANN-based formula is practical in predicting the elastic buckling load of perforated plates without the need of an ANN platform.

• Steel and Composite Structures
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• 제33권2호
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• pp.181-194
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• 2019

This paper presents an efficient approach to generate a new empirical formula to predict the axial compression capacity (ACC) of circular concrete-filled tube (CCFT) columns using the artificial neural network (ANN). A total of 258 test results extracted from the literature were used to develop the ANN models. The ANN model having the highest correlation coefficient (R) and the lowest mean square error (MSE) was determined as the best model. Stability analysis, sensitivity analysis, and a parametric study were carried out to estimate the stability of the ANN model and to investigate the main contributing factors on the ACC of CCFT columns. Stability analysis revealed that the ANN model was more stable than several existing formulae. Whereas, the sensitivity analysis and parametric study showed that the outer diameter of the steel tube was the most sensitive parameter. Additionally, using the validated ANN model, a new empirical formula was derived for predicting the ACC of CCFT columns. Obviously, a higher accuracy of the proposed empirical formula was achieved compared to the existing formulae.

• 한국소음진동공학회논문집
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• 제15권6호
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• pp.635-644
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• 2005

This paper is. a study on relation between road traffic noise(RTN) and sound power level(PWL). At present, many experimental formulae and prediction formulae are used for prediction of RTN. But these formulae are difficult to appiy to the metropolitan area because these formulae are inaccurate in the different condition from reference condition. This paper calculate RTN and PWL of each prediction formula, choose the best one and make a noise map of the subject area. Procedure is as follows. First, calculate $L_{eq}$ of RTN using experimental formulae and prediction formulae. Second, calculate PWL using $L_{eq}$ of RTN and distance attenuation for point source at semi-free field. Third, choose the most accurate formula. And finally, make a noise map of the subject area at present and future. The result using noise map will be able to apply to application field. Noise mapping tool used on this paper is Raynoise program using Ray Tracing Method(RTM), Mirror Image Source Method(MISM) and Hybrid Method(HM).

• 대한기계학회논문집A
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• 제38권5호
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• pp.505-511
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• 2014

내연기관의 냉각기 고무호스에 사용되는 EPDM 고무는 열과 기계적 하중을 받는 동시에 국부적으로 형성된 전기적 스트레스를 받아 복합적인 노화가 발생한다. 본 연구에서는 EPDM 고무의 전기화학적 복합노화 시험을 하고, 아레니우스 관계식을 이용하여 노화온도($60^{\circ}C$, $80^{\circ}C$, $100^{\circ}C$)에 따른 가속수명 예측식을 구하였다. 수명에 영향을 미치는 인장변형률(5%, 10%)을 반영하여 예측식의 기울기($E_a/R$) 및 아레니우스 상수(C)를 고려한 수정된 수명예측 식을 제안하였다. 이를 통해 노화온도와 인장변형률에 영향을 받은 EPDM 고무의 수명을 예측하였고, 수정된 수명예측 시간이 실제 실험결과의 편차 범위 이내에서 일치함을 확인하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2010년도 춘계학술대회 논문집
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• pp.477-478
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• 2010

It was in the mid-1980s when the shipboard noise analysis was introduced to the Korean shipbuilding industry. Since then through the continued efforts of the industries in the last decades, native computational codes dedicated to the shipboard noise prediction have been developed based on empirical formula and/or sophisticated theories such as SEA and PFM. This paper addresses some problems in dealing with predicting shipboard noise and the way how to overcome the uncertainties in the prediction.

• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.717-726
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• 2006

This study is to investigate the MAE of prediction value by collaborative filtering algorithm originated by GroupLens and improved algorithm. To decrease the MAE on the collaborative recommender system on user based, this research proposes the improved algorithm, which reduces the possibility of over estimation of active user's preference mean collaboratively using other user’s preference mean. The result shows the MAE of prediction by improved algorithm is better than original algorithm, so the active user's preference mean used in prediction formula is possibly over estimated.

• 한국대기환경학회지
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• 제15권5호
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• pp.545-554
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• 1999

We would like to develop a short-term model to predict the time-related concentration of ozone whose reaction mechanism is complex. The paper targets Seoul where an ozone alert system has recently been employed. In order to develop a short-term prediction model for ozone, we suggested the Ozone Peak Indicator(OPI), an equivalent of the potential daily maximum ozone concentration, with precursors being the only limiting factor, and we calculated the Ozone Peak Indicarot as OPI={$rac{(O_3)_{max}cdot(H_{eH})_{max}(Rad)_{max}$ to preclude the influence of mixing height and solar radiation on the daily maximum ozone concentration. The OPI on the day of the prediction is to be calcultated by using the relation between OPI and the initial value of precursors. The basic prediction formula for time-related ozone concentration was established as $O_3(1)={(OPI)cdot Rad(t-2)H_{eH}}$, using the OPI, solar radiation two hours before prediction and mixing height. We developed, along with the basic formula for predicting photochemical oxidants, "SEOM"(Seoul Empirical Oxidants Model), a Fortran program that helps predict solar radiation and mixing height needed in the prediction of ozone pollution. When this model was applied to Seoul and an analysis of the correlation between the observed and the predicted ozone concentrations was made through SEOM, there appeared a very high correlation, with a coefficient of 0.815. SEOM can be described as a short-term prediction model for ozone concentration in large cities that takes into account the initial values of precursors, and changes in solar radiation and mixing height. SEOM can reflect the local characteristics of a particular and region can yield relatively good prediction results by a simple data input process.t process.

• 대한토목학회논문집
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• 제5권4호
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• pp.103-111
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• 1985

본(本) 논문(論文)에서는 철근콘크리트 휨부재의 균열폭과 균열간격 결정에 관한 연구(硏究)가 이루어 졌다. 철근콘크리트 휨부재의 균열폭 및 균열간격의 유도는 최근에 진전된 균열이론에 의거하였으며, 설계(設計) 및 해석시(解析時)에 실제적으로 사용할 수 있는 균열폭 및 균열간격 예측 공식을 제안하였다. 제안된 공식과의 비교를 위하여 철근콘크리트보에 대한 균열거동 실험이 수행되었다. 본(本) 예측 공식(公式)을 본(本) 연구(硏究)의 실험결과 및 타연구자(他硏究者)의 실험자료와 비교한 결과 만족스런 결과를 얻었다. 본(本) 연구(硏究)에서 제안된 공식을 현재 ACI 시방서(示方書)에서 채택하고 있는 Gergely & Lutz 공식(公式)과도 비교한 결과, 본(本) 공식(公式)이 거의 모든 경우, 더 정확한 예측을 하고 있음을 알 수 있었으며, 실제 설계 및 해석시에 지침이 될 수 있을 것으로 사료된다.

• 환경영향평가
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• 제14권1호
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• pp.25-36
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• 2005

Actually, prediction formula of road traffic noise for EIA(Environmental Impact Assessment) has been used that proposed by National Institute of Environmental Research in 1999. The prediction formula, however, was calculated predicted noise level according to noise level producing on first floor, then needs to correct noise level at each floor in the case of apartment building. The investigation was carried out to calculate the correction coefficient for commonly using in EIA of large scaled apartment development areas. The noised level at each floor were measured from August 2001 to March 2002 at 31 investigation points of large scaled apartment development area in national wide. Measured data were divided and treated with 4 types as 3th floor, 5th floor, 7th floor and 10th floor and then the correction coefficients of each floor were calculated using by correlation formula according to each floor.