• Journal of the Korea Concrete Institute
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• v.15 no.6
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• pp.820-828
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• 2003

Recent research has indicated that the current ACI shear provision provides unconservative predictions for large slender beams and beams with low level of longitudinal reinforcement, and conservative results for deep beams. To modify some problems of ACI shear provision, ultimate shear strength equation considering size effect and arch action to compute shear strength in high-strength concrete beams without stirrups is presented in this research. Three basic equations, namely size reduction factor, rho factor, and arch action factor, are derived from crack band model of fracture mechanics, analysis of previous some shear equations for longitudinal reinforcement ratio, and concrete strut described as linear prism in strut-tie model deep beams. Constants of basic equations are determined using statistical analysis of previous shear testing data. To verify proposed shear equation for each variable, effective depth, longitudinal reinforcement ratio, concrete compressive strength and shear span-to-depth ratio, about 300 experimental data are used and proposed shear equation is compared with ACI 318-99 code, CEB-FIP Model code, Kim &Park's equation and Zsutty's equation. The proposed shear equation is not only simpler than other shear equations, it is but also shown to be economical predictions and reasonable safety margin. Hence proposed shear strength equation is expected to be applied to practical shear design.

• Journal of Korean Society of Steel Construction
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• v.27 no.2
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• pp.251-260
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• 2015

The end plate connection is applied to beam-column moment connections in various forms. Such end plate connection displays changes in the behavioral characteristics, strength and stiffness, and energy dissipation capacity based on the thickness and length of the end plate, the number and diameter of the high strength bolt, the gauge distance of the high strength bolt, prying action force of the high strength bolt, and dimensions and length of the welds. Accordingly, this study has apprehended the axial tensile stiffness and prying action force of the high strength bolt connected on the tensile side based on the difference in thickness of the end plate, and was conducted to propose an analysis model for the prediction of such variables that affect the operating properties of the end plate. To achieve this, this study has conducted a three-dimensional non-linear finite-element analysis of the unstiffened expanding end plate connection by selecting only the thickness of the end plate as the variable.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.1
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• pp.31-36
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• 2009

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near reflectance infrared spectroscopy (NIRS) was used to evaluate the possibility of forage analysis and collect 258 samples such as barley for whole crop silage, forage corn and sudangrass from 2002 to 2007. The samples were analyzed for CP (crude protein), CF (crude fiber), ADF (acid detergent fiber), NDF (neutral detergent fiber) and IVTD (in vitro true digestibility), and also scanned using NIRSystem with wavelength from $400{\sim}2,400nm$. Multiple linear regression was used with wet analysis data for developing the calibration model and validate unknown samples. The important index In this experiment was SEC and SEP $r^2$ for CF, CP, NDF, ADF and IVTD in calibration set were 0.70, 0.86, 0.94, 0.94 and 0.89, also 0.47, 0.39, 0.89, 0.90 and 0.61 in validation sample, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality, specially in CF, ADF and IVTD, sample should be included for respective forage samples to get accurate result. More robust calibrations can be made to cover every forage samples if added representative sample set.

• Journal of Service Research and Studies
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• v.10 no.1
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• pp.55-67
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• 2020

Fine dust has recently become one of the greatest concerns of Korean people and has been a target of considerable efforts by governments and local governments. In the academic world, many researches have been carried out in relation to fine dust, but the research on the economic field has been relatively few. So we wanted to know how fine dust affects the economy. Big data of PM10 concentration for fine dust and fine dust theme stock price were collected for five years from 2013 to 2017. Regression analysis was performed using the linear regression model, the generalized least squares method. As a result, the change in the fine dust concentration was found to have a effect on the related theme stocks' price. When the fine dust concentration increased compared to the previous day, the fine dust theme stocks' price also showed a tendency to increase. Also, according to the analysis of stock price change from 2013 to 2017 based on fine dust theme stocks, companies with large regression coefficients were changed every year. Among them, the regression coefficients of Monalisa were repeatedly high in 2014, 2015, 2017, Samil Pharmaceutical in 2015, 2016 and 2017, and Welcron in 2016 and 2017, and the companies were judged to be sensitive to the concentration of fine dust. The companies that responded the most in the past 5 years were Wokong, Welcron, Dongsung Pharmaceutical, Samil Pharmaceutical, and Monalisa. If PM2.5 measurement data are accumulated enough, it would be meaningful to compare and analyze PM2.5 concentration with independent variables. In this study, only the fine dust concentration is used as an independent variable. However, it is expected that a more clear and well-explained result can be found by adding appropriate additional variables to increase the explanatory power.

• Journal of The Korean Society of Grassland and Forage Science
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• v.31 no.4
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• pp.409-414
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• 2011

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near Infrared Reflectance Spectroscopy (NIRS) was used to evaluate the possibility of forage analysis. 175 samples consisted of Italian ryegrass, whole crop barley and pea seeded spring in 2009 were collected. The samples were analyzed for moisture, crude protein (CP), crude ash (CA), acid detergent fiber (ADF), and neutral detergent fiber (NDF), and also scanned using NIRSystem with wavelength from 400~2,500 nm. Multiple linear regression was used with wet analysis data for developing the calibration model and validated unknown samples. The important index in this experiment were SEC, SEP. The r2 value for moisture, CP, CA, ADF, and NDF in calibration set was 0.65, 0.97, 0.93, 0.99, and 0.97 and also was 0.15, 0.94, 0.96, 0.98 and 0.98 in validation set, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality for CP, CA ADF and NDF except moisture content in forage when proper samples incorporated into the equation development.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.126-131
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• 2019

The estimation of available solar energy at particular locations is critical to find and assess suitable locations of PV sites. The amount of PV power generation is however affected by various geographical factors (e.g., weather), which may make it difficult to identify the complex relationship between affecting factors and power outputs and to apply findings from one study to another in different locations. This study thus undertakes a regression analysis using data collected from 172 PV plants spatially distributed in Korea to identify critical weather conditions and estimate the potential power generation of PV systems. Such data also include solar radiation, precipitation, fine dust, humidity, temperature, cloud amount, sunshine duration, and wind speed. The estimated PV power generation is then compared to the actual PV power generation to evaluate prediction performance. As a result, the proposed model achieves a MAPE of 11.696(%) and an R-squred of 0.979. It is also found that the variables, excluding humidity, are all statistically significant in predicting the efficiency of PV power generation. According, this study may facilitate the understanding of what weather conditions can be considered and the estimation of PV power generation for evaluating and determining suitable locations of PV facilities.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.13-18
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• 2013

This study was conducted to estimate the Genomic Estimated Breeding Value (GEBV) using Genomic Best Linear Unbiased Prediction (GBLUP) method in Hanwoo (Korean native cattle) population. The result is expected to adapt genomic selection onto the national Hanwoo evaluation system. Carcass weight (CW), eye muscle area (EMA), backfat thickness (BT), and marbling score (MS) were investigated in 552 Hanwoo progeny-tested steers at Livestock Improvement Main Center. Animals were genotyped with Illumina BovineHD BeadChip (777K SNPs). For statistical analysis, Genetic Relationship Matrix (GRM) was formulated on the basis of genotypes and the accuracy of GEBV was estimated with 10-fold Cross-validation method. The accuracies estimated with cross-validation method were between 0.915~0.957. In 534 progeny-tested steers, the maximum difference of GEBV accuracy compared to conventional EBV for CW, EMA, BT, and MS traits were 9.56%, 5.78%, 5.78%, and 4.18% respectively. In 3,674 pedigree traced bulls, maximum increased difference of GEBV for CW, EMA, BT, and MS traits were increased as 13.54%, 6.50%, 6.50%, and 4.31% respectively. This showed that the implementation of genomic pre-selection for candidate calves to test on meat production traits could improve the genetic gain by increasing accuracy and reducing generation interval in Hanwoo genetic evaluation system to select proven bulls.

• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.121-145
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• 1992

This paper examines characteristics of time series data related to the construction investment(stationarity and time series components such as secular trend, cyclical fluctuation, seasonal variation, and random change) and surveys predictibility, fitness, and explicability of independent variables of various models to build a short-term construction investment forecasting model suitable for current economic circumstances. Unit root test, autocorrelation coefficient and spectral density function analysis show that related time series data do not have unit roots, fluctuate cyclically, and are largely explicated by lagged variables. Moreover it is very important for the short-term construction investment forecasting to grasp time lag relation between construction investment series and leading indicators such as building construction permits and value of construction orders received. In chapter 3, we explicate 7 forecasting models; Univariate time series model (ARIMA and multiplicative linear trend model), multivariate time series model using leading indicators (1st order autoregressive model, vector autoregressive model and error correction model) and multivariate time series model using National Accounts data (simple reduced form model disconnected from simultaneous macroeconomic model and VAR model). These models are examined by 4 statistical tools that are average absolute error, root mean square error, adjusted coefficient of determination, and Durbin-Watson statistic. This analysis proves two facts. First, multivariate models are more suitable than univariate models in the point that forecasting error of multivariate models tend to decrease in contrast to the case of latter. Second, VAR model is superior than any other multivariate models; average absolute prediction error and root mean square error of VAR model are quitely low and adjusted coefficient of determination is higher. This conclusion is reasonable when we consider current construction investment has sustained overheating growth more than secular trend.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.4
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• pp.201-212
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• 2016

A Wind resource assessment and optimal micrositing of wind turbines were implemented for the development of an onshore wind farm of 30 MW capacity on Gadeok Island in Busan, Republic of Korea. The wind data measured by the automatic weather system (AWS) that was installed and operated in the candidate area were used, and a reliability investigation was conducted through a data quality check. The AWS data were measured for one year, and were corrected for the long term of 30 years by using the modern era retrospective analysis for research and application (MERRA) reanalysis data and a measure- correlate-predict (MCP) technique; the corrected data were used for the optimal micrositing of the wind turbines. The micrositing of the 3 MW wind turbines was conducted under 25 conditions, then the best-optimized layout was analyzed with a various wake model. When the optimization was complete, the estimated park efficiency and capacity factor were from 97.6 to 98.7 and from 37.9 to 38.3, respectively. Furthermore, the annual energy production (AEP), including wake losses, was estimated to be from 99,598.4 MWh to 100,732.9 MWh, and the area was confirmed as a highly economical location for development of a wind farm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.23-30
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• 2003

In this study, the various load cases by specified by the IEC61400-1 international specification and GL Regulations for the wind energy conversion system were considered, and a specific composite structure configuration which can effectively endure various loads was proposed. In order to evaluate the structure, the structural analysis for the composite wind turbine blade was performed using the finite element method(FEM). In the structural design, the acceptable configuration of blade structure was determined through the parametric studies, and the most dominant design parameters were confirmed. In the stress analysis using the FEM, it was confirmed that the blade structure was safe and stable for all the considerd load cases. Moreover the safety of the blade root joint with insert bolts, newly devised in this study, was checked against the design loads and also the fatigue loads. The fatigue life for operating more than 20 years was estimated by using the well-known S-N linear damage rule, the load spectrum and Spera's empirical equations. The full-scale static test was performed under the simulated aerodynamic loads. from the experimental results, it was found that the designed blade had the structural integrity. Furthermore the measured results were agreed with the analytical results such as deflections, strains, the mass and the radial center of gravity. The studied blade was successfully certified by an international institute, GL, of Germany.