• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.6
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• pp.556-565
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• 2004

We have experimented an actual solar water heating system acquiring real data for one year period. On the basis of the operation data, it is necessary to predict the system performance such as collector efficiency and solar fraction, and to analyze the economical efficiency for system optimal design. To estimate the performance of actual systems through simulation, valid modelling for components consisting of the system should be accompanied. The present study is focused on the modelling for load patterns and operating control conditions. We proposed two load models: concentration model which gathers real loads as a meaningful group and distribution model which disperses real loads with time. If grouping of the load distribution is suitable, the predicted values by the concentration model approaches to those by the distribution model close to actual load pattern apparently. As a result, both of them are in good agreement with those by experiment.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.445-459
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• 2014

This paper investigates the dependence structure of Korean financial markets (stock, foreign exchange (FX) rates and bond) using copula-GARCH and dynamic conditional correlation (DCC) models. We examine GJR-GARCH with skewed elliptical distributions and four copulas (Gaussian, Student's t, Clayton and Gumbel) to model dependence among returns, and then employ DCC model to describe system-wide correlation dynamics. We analyze the daily returns of KOSPI, FX (WON/USD) and KRX bond index (Gross Price Index) from $2^{nd}$ May 2006 to $30^{th}$ June 2014 with 2,063 observations. Empirical result shows that there is significant asymmetry and fat-tail of individual return, and strong tail-dependence among returns, especially between KOSPI and FX returns, during the 2008 Global Financial Crisis period. Focused only on recent 30 months, we find that the correlation between stock and bond markets shows dramatic increase, and system-wide correlation wanders around zero, which possibly indicates market tranquility from a systemic perspective.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.1
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• pp.98-106
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• 1996

An irrigation scheduling model, IRIS developed to evaluate irrigation demand and irrigation time for upland crops. For IRlS modeling the soil moisture simulation model, SWATRER was adopted and modified. The developed model, IRIS operated under 5 different soil moisture level that is 20%, 40%, 60%, 80% of available soil moisture and optimum soil moisture level, OSML, which is different about the growing stage and no rainfall condition during growing period. As a result for IRIS simulation, irrigation demand for 5 different soil moisture level was 332.3, 409.8, 569.3, 732.2, 539.3mm, irrigation number was 5, 8, 18, 54, 16 times and irrigation interval during peak time of consumptive use was 20, 13, 6, 2, 6 days respectively. It is appeared that the higher soil moisture level the more irrigation demand and irrigation number and the higher soil moisture level the less irrigation interval.

• Asian Journal of Innovation and Policy
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• v.6 no.2
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• pp.225-244
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• 2017

When evaluating the economic value of technology or business project, we need to consider the period and cost for commercialization. Since the discounted cash flow (DCF) method has limitations in that it can not consider consecutive investment or does not reflect the probabilistic property of commercialization cost, we often take it desirable to apply the concept of real options with key metrics of underlying asset value, commercialization cost, and volatility, while regarding the value of technology and investment as the opportunity value. We at this moment provide more elaborated real options model with the effective region of volatility, which reflects the uncertainty in the option pricing model (OPM).

• Korean Journal of Computational Design and Engineering
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• v.14 no.2
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• pp.96-104
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• 2009

It gradually becomes important to study on how to efficiently integrate and manage plant lifecycle data such as 2D schematic and 3D solid data, logical configuration data, and equipment specifications data. From this point of view, converting plant design data from various systems into neutral data independent from any commercial systems is one of important technologies for the operation and management of plants which usually have a very long period of life. In order to achieve this goal, a neutral model for efficient integration and management of plant data was defined. After schema mapping between one of specification-driven plant design systems and the neutral model was performed, a plant data translator is also implemented according to the mapping result. Finally, by experiments with nuclear power plant design, the feasibility of the translator was demonstrated.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.4
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• pp.277-293
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• 2016

We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-dimensional Geometric Brownian Motion (GBM) as the model of two equities and a no-arbitrage interest model (One-factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.

• East Asian Economic Review
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• v.22 no.2
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• pp.141-176
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• 2018

The paper analyzes and compares the effects of domestic monetary policy using DSGE, DSGE-VAR, and VAR based on a two-country open economy model of Korea and the U.S. According to impulse response analysis, a domestic interest rate hike raises won value in the case of DSGE and DSGE-VAR models, while in the case of the unrestricted VAR model, it lowers won value. In the marginal data density standard, DSGE-VAR (${\mu}=1$) is superior to DSGE or Bayesian VAR over the sample period. Conversely, in the in-sample RMSE criterion, especially for the won/dollar exchange rate, VARs are superior to DSGE or DSGE-VAR. It is necessary to study further if these differences are caused by model misspecification or omitted variable bias.

• Korea Trade Review
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• v.44 no.2
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• pp.51-62
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• 2019

This study predicts the future world seaborne trade volume with econometrics methods using 23-year time series data provided by Clarksons. For this purpose, this study uses simple regression analysis, exponential smoothing method and seemingly unrelated regression model (SUR Model). This study is meaningful in that it predicts worldwide total seaborne trade volume and seaborne traffic in four major items (container, bulk, crude oil, and LNG) from 2019 to 2023 as there are few prior studies that predict future seaborne traffic using recent data. It is expected that more useful references can be provided to trade related workers if the analysis period was increased and additional variables could be included in future studies.

• Ocean and Polar Research
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• v.31 no.2
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• pp.167-176
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• 2009

Cobalt-rich manganese crusts on seamounts have received an increasing amount of attention as future resources for Co, Ni, Cu, and Mn. A dearth of detailed information regarding the relevant distribution characteristics, mining technologies, and ore processing technologies, however, has precluded potential evaluations of the technical and economic advantages of these crusts. In the past 4 years, Korea has undertaken a survey of the cobalt-rich manganese crusts in and around the Magellan Seamount and Mid-Pacific Mountains. This paper introduces the preliminary feasibility study of the distribution features and R&D results centered around the development of the cobalt-rich manganese crusts. The evaluation model was developed by modifying the model for the manganese nodules. In addition to considering the geological and geophysical differences between the manganese nodules and the cobalt-rich manganese crusts, an ore dressing subsystem was installed in the model. The mining subsystem is composed of a self-propelled collector--a pipeline with submersible hydraulic pumps for crust lifting. The smelting and chlorine leach method was selected for metallurgical processing. The production scales were established at 2,500t/y of cobalt metal. The production of three metals--cobalt, nickel, and copper--was considered in terms of metallurgical processing. The economic feasibility analyses demonstrated that the payback period was 11.4 years, the NPV was 36M$, and the IRR was 9.6% with the economic factors in the case of a cobalt price of US$ 25/lb. It was also demonstrated in this study that the payback period was 8.6 years, the NPV was 154M$, and the IRR was 14.0% in the case of a cobalt price of US$ 30/lb. This indicates that the approach under consideration appears to offer greater potential given the predicted metal prices.

• Atmosphere
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• v.22 no.2
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• pp.245-257
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• 2012

The Asian dust (Hwangsa) forecasting model, Asian Dust Aerosol Model (ADAM) has been modified by using satelliate monitoring of surface vegetation, which enables to simulate dusts occuring not only in springtime but also for all-year-round period. Coupled with the Unified Model (UM), the operational weather forecasting model at KMA, UM-ADAM2 was implemented for operational dust forecasting since 2010, with an aid of development of Meteorology-Chemistry Interface Processor (MCIP) for usage UM. The performance analysis of the ADAM2 forecast was conducted with $PM_{10}$ concentrations observed at monitoring sites in the source regions in China and the downstream regions of Korea from March to December in 2010. It was found that the UM-ADAM2 model was able to simulate quite well Hwangsa events observed in spring and wintertime over Korea. In the downstream region of Korea, the starting and ending times of dust events were well-simulated, although the surface $PM_{10}$ concentration was slightly underestimated for some dust events. The general negative bias less than $35{\mu}g\;m^{3}$ in $PM_{10}$ is found and it is likely to be due to other fine aerosol species which is not considered in ADAM2. It is found that the correlation between observed and forecasted $PM_{10}$ concentration increases as forecasting time approaches, showing stably high correlation about 0.7 within 36 hr in forecasting time. This suggests the possibility that there is potential for the UM-ADAM2 model to be used as an operational Asian dust forecast model.