• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.281-290
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• 2015

Numerical simulations of free surface flow over a broad-crested rectangular weir are conducted by using the volume of fraction (VOF) method and three different turbulence models, the k-${\varepsilon}$, RNG k-${\omega}$ and k-${\omega}$ SST models. The governing equations are solved by a second-order accurate finite volume method and the grid sensitivity study of solutions is carried out. The numerical results are evaluated by comparing the solutions with experimental and numerical results of Kirkgoz et al. (2008) and some non-dimensionalized experimental results obtained by Moss (1972) and Zachoval et al. (2012). The results show that the present numerical model can reasonably reproduce the experimental results, while three turbulent models yield different numerical predictions of two distinct zones of flow separation, the first zone is in front of the upstream edge of the weir and the second is created immediately behind the upstream edge of the weir where the flow is separated to form the separation bubble. The standard k-${\varepsilon}$ model appears to significantly underestimate the size of both separation zones and the k-${\omega}$ SST model slightly over-estimates the first separation zone in front of the weir. The RNG k-${\varepsilon}$ model predicts both separation zones in overall good agreement with the experimental measurement, while the k-${\omega}$ SST model yields the best numerical prediction of separation bubble at the upstream edge of the weir.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.143-154
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• 2012

As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.272-287
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• 2013

This paper describes the importance of selecting explanatory variables(e.g. land price determinants) in hedonic pricing models employed in predicting real estate price, and explores dynamics of the land price determinants over time. The City of Junju was chosen as the study area, and repeated measured price data of standard lots over 17 years were analyzed. We applied a three-level modeling approach to this data in consideration of its nested data structure and longitudinal characteristics. Main land price determinants we focused on are primarily based on items included in the standard comparison table of land price, which is an official hedonic pricing model used by Government to estimate land price for tax levy. Our result shows that the land price fluctuation over 17 years was not uniform over the whole study area with each neighborhood revealing different price trend, and as such warrants longitudinal model components. In addition, some of determinants previously recognized as important were proved insignificant. It was also found that significant determinants at a particular time point lost its power gradually over time and vice versa. It is expected that more accurate prediction of price would be possible when taken account for this dynamics of price determinants over time in applying hedonic pricing model method.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.11a
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• pp.109-113
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• 2007

This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.43-59
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• 2017

This study presents the prediction methodology of debris flow occurrence areas using the SINMAP model. Former studies used a single calibration region applying some of the soil test results to predict debris flow occurrence in SINMAP model, which couldn't subdivide the soil properties for the target areas. On the other hands, a multi-calibration region using a detailed soil map and soil strength parameters (c, ${\phi}$) for each soil series to make up for limitation of former studies is proposed. In this process, soils with soil erodibility factor (K) are classified into three types: 1) gravel and gravelly soil. 2) sand and sandy soil, and 3) silt and clay. In addition, T/R estimation method using mean elevation of target area instead of T/R method using actual occurrence time is suggested in this study. The suggested method is applied to Seobyeok-1 ri area, Bonghwa-gun where debris flow occurred. As a result of comparison between two T/R estimation method, both T/R estimations are almost equal. Therefore, the suggested methodologies in this study will contribute to set up the national-wide mitigation plan against debris flow occurrence.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.6
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• pp.64-72
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• 2017

The longitudinal dynamic instability which can occur in the fueling process of a space launch vehicle is called pogo. It is caused by coupling between the fuselage and propulsion system and they would be formed as a closed-loop system. so that the amplitude of the response may increase or decrease. In this paper, a mathematical model which is applicable to the systematic pogo analysis of a general launch vehicle is developed for an example of space shuttle. The formulations are composed of the linearized second-order differential equation for the propulsion system, and of the pressure, weight displacement, and generalized displacement. Those are important parameters for pogo analysis, are derived through eigenvalue analysis. By the formulation suggested in this paper, it is expected that mathematical modeling method of the pogo system can be obtained and systematic pogo stability analysis for any launch vehicle will be enabled.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.19-27
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• 2014

In order to estimate the life of 2,5 inch HDD which is adopted by PC environment, make the test plan which reflect the failure mode of market, make the test model of accelerated life test which reflect the stress of temperature. after an analysis of the environment of PC using, test procedure was decided that operation was write 50 % and read 50 %, and then access method was sequential 50 % and random 50%. The acceleration life test was executed on condition that temperature was $50^{\circ}C$ and $60^{\circ}C$, performance was 95 % in max performance, test time was 1000 hours. by the test of goodness of fit of anderson-darling of the failure data during test, it was confirmed that the distribution of failure fellow weibull. test for shape and scale was equal, and shape parameter was 0.7177, characteristic life was 429434 hours at normal user condition($30^{\circ}C$) by the analysis of weibull-arrhenius modeling. It made no difference about the statistics when equality test was executed. The activation energy was 0.2775eV. In analyzing between the failure samples of acceleration test and the samples of market return even though there is detail difference about the share of failure mode, the rank of share was almost same. This study suggest the test procedure of acceleration test of 2.5 inch HDD in PC using environment, and help the life estimation at manufacture and user.

• Journal of the Korea Concrete Institute
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• v.17 no.2 s.86
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• pp.281-290
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• 2005

This paper presents experimental and analytical studies on long-term behavior of square CFT columns under central axial loading. Two loading cases are considered; (1) the load applied only at the inner concrete of the column and (2) the load applied simultaneously on both the concrete and the steel tube. Four specimens of square CFT columns were tested under the two loading cases, and basic creep test for two concrete specimens was performed to find out the creep properties of the inner concrete. Three-dimensional finite element analysis models were established and verified with the experimental results. The verification shows that the prediction for the long-term behavior of actual square CFT columns is possible from the three dimensional finite element modeling considering the bond behavior between steel tube and inner concrete. Also, experimental results and numerical calculations revealed that the bond stress Induced by the confinement pressure as well as the slip between inner concrete and steel tube were increased with time In the first loading case. However, the confinement by the loading Plate was decreased with time while increasing confinement effect by the steel tube was observed over time. In contrast no confinement effects occur in the second loading case.

• Journal of the Korea Concrete Institute
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• v.14 no.1
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• pp.118-125
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• 2002

Hydration is the main reason for the growth of the material properties. An exact parameter to control the chemical and physical process is not the time, but the degree of hydration. Therefore, it is reasonable that development of all material properties and the formation of microstructure should be formulated in terms of degree of hydration. Mathematical formulation of degree of hydration is based on combination of reaction rate functions. The effect of moisture conditions as well as temperature on the rate of reaction is considered in the degree of hydration model. This effect is subdivided into two contributions: water shortage and water distribution. The former is associated with the effect of W/C ratio on the progress of hydration. The water needed for progress of hydration do not exist and there is not enough space for the reaction products to form. The tatter is associated with the effect of free capillary water distribution in the pore system. Physically absorption layer does not contribute to progress of hydration and only free water is available for further hydration. In this study, the effects of chemical composition of cement, W/C ratio, temperature, and moisture conditions on the degree of hydration are considered. Parameters that can be used to indicate or approximate the real degree of hydration are liberated heat of hydration, amount of chemically bound water, and chemical shrinkage, etc. Thus, the degree of heat liberation and adiabatic temperature rise could be determined by prediction of degree of hydration.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.9-14
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• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.