• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.3
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• pp.190-198
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• 2006

Radiation use efficiency (RUE), the amount of biomass produced per unit intercepted photosynthetically active radiation (PAR), constitutes a main part of crop growth simulation models. The objective of the present study was to evaluate the variation of RUE of rice plants under various nitrogen nutritive conditions. from 1998 to 2000, shoot dry weight (DW), intercepted PAR of rice canopies, and nitrogen nutritive status were measured in various nitrogen fertilization regimes using japonica and Tongil-type varieties. These data were used for estimating the average RUEs before heading and the relationship between RUE and the nitrogen nutritive status. The canopy extinction coefficient (K) increased with the growth of rice until maximum tillering stage and maintained constant at about 0.4 from maximum tillering to heading stage, rapidly increasing again after heading stage. The DW growth revealed significant linear correlation with the cumulative PAR interception of the canopy, enabling the estimation of the average RUE before heading with the slopes of the regression lines. Average RUE tended to increase with the increased level of nitrogen fertilization. RUE increased approaching maximum as the nitrogen nutrition index (NNI) calculated by the ratio of actual shoot N concentration to the critical N concentration for the maximum growth at any growth stage and the specific leaf nitrogen $(SLN;\;g/m^2\;leaf\;area)$ increased. This relationship between RUE (g/MJ of PAR) and N nutritive status was expressed well by the following exponential functions: $$RUE=3.13\{1-exp(-4.33NNNI+1.26)\}$$ $$RUE=3.17\{1-exp(-1.33SLN+0.04)\}$$ The above equations explained, respectively, about 80% and 75% of the average RUE variation due to varying nitrogen nutritive status of rice plants. However, these equations would have some limitations if incorporated as a component model to simulate the rice growth as they are based on relationships averaged over the entire growth period before heading.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.699-708
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• 2017

The present study was to develop an approach for predicting soybean yield using a crop growth simulation model at the regional level where the detailed and site-specific information on cultivation management practices is not easily accessible for model input. CROPGRO-Soybean model included in Decision Support System for Agrotechnology Transfer (DSSAT) was employed for this study, and Illinois which is a major soybean production region of USA was selected as a study region. As a first step to predict soybean yield of Illinois using CROPGRO-Soybean model, genetic coefficients representative for each soybean maturity group (MG I~VI) were estimated through sowing date experiments using domestic and foreign cultivars with diverse maturity in Seoul National University Farm ($37.27^{\circ}N$, $126.99^{\circ}E$) for two years. The model using the representative genetic coefficients simulated the developmental stages of cultivars within each maturity group fairly well. Soybean yields for the grids of $10km{\times}10km$ in Illinois state were simulated from 2,000 to 2,011 with weather data under 18 simulation conditions including the combinations of three maturity groups, three seeding dates and two irrigation regimes. Planting dates and maturity groups were assigned differently to the three sub-regions divided longitudinally. The yearly state yields that were estimated by averaging all the grid yields simulated under non-irrigated and fully-Irrigated conditions showed a big difference from the statistical yields and did not explain the annual trend of yield increase due to the improved cultivation technologies. Using the grain yield data of 9 agricultural districts in Illinois observed and estimated from the simulated grid yield under 18 simulation conditions, a multiple regression model was constructed to estimate soybean yield at agricultural district level. In this model a year variable was also added to reflect the yearly yield trend. This model explained the yearly and district yield variation fairly well with a determination coefficients of $R^2=0.61$ (n = 108). Yearly state yields which were calculated by weighting the model-estimated yearly average agricultural district yield by the cultivation area of each agricultural district showed very close correspondence ($R^2=0.80$) to the yearly statistical state yields. Furthermore, the model predicted state yield fairly well in 2012 in which data were not used for the model construction and severe yield reduction was recorded due to drought.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.1-8
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• 2015

In this paper, computational evaluation method for fatigue crack growth rate(FCGR) based on material viscoplastic-damage model is proposed. Viscoplastic-damage model expressing material constitutive behavior of 7% nickel steel is introduced and is implemented into commercial finite element analysis(FEA) code, ABAQUS, as a user defined material subroutine(UMAT) for application in the FEA environments. Verification of developed UMAT and material parameters of material model are carried out by uniaxial tensile test simulations of 7% nickel steel. Moreover, jump-in-cycles procedure and rearrangement of critical damage are employed and also implemented to the ABAQUS UMAT for fatigue damage analysis. Typical FCGR test results such as relationship between crack length and number of cycles and relationship between da/dN and ${\Delta}K$ could be obtained from FCGR test simulation using developed UMAT and these results are compared with experimental results in order to verify of proposed computational method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.20-25
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• 2020

Spatial simulation of crop growth often requires application of management conditions to each cell. In particular, it is of great importance to determine the temperature conditions during the nursery period for rice seedlings, which would affect heading date projections. The objective of this study was to determine the value of TMPSB, which is the parameter of ORYZA2000 model to represent temperature increase under a plastic tunnel during the rice seedling periods. Candidate values of TMPSB including 0℃, 2℃, 5℃, 7℃ and 9℃ were used to simulate rice growth and yield. Planting dates were set from mid-April to mid-June. The simulations were performed at four sites including Cheorwon, Suwon, Seosan, and Gwangju where climate conditions at rice fields common in Korea can be represented. It was found that the TMPSB values of 0℃ and 2℃ resulted in a large variation of heading date due to low temperature occurred in mid-April. When the TMPSB value was >7℃, the variation of heading date was relatively small. Still, the TMPSB value of 5℃ resulted in the least variation of heading date for all the planting dates. Our results suggested that the TMPSB value of 5℃ would help reasonable assessment of climate change impact on rice production when high resolution gridded weather data are used as inputs to ORYZA2000 model over South Korea.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.27 no.4
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• pp.380-389
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• 1994

Larvae of the freshwater shrimp, Macrobrachium nipponense(De Haan) were reared in the laboratory under constant conditions ($25^{\circ}C,\;7\%0$ S), and their feeding rate, oxygen consumption, ammonia nitrogen excretion, and growth were measured at regular intervals during development from hatching to post larval stage. Growth was measured as dry weight, carbon, nitrogen, hydrogen, protein and lipid. All these physiological and biochemical traits revealed significant changes from instar to instar. Average feeding rate was high in intermolt stage of the molt cycle and it showed a bell-shaped pattern. Respiration(R) increased from hatching to post larval stage. Excretion(U) increased in intermolt phase of larvae and it showed a bell-shaped variation pattern, in all larval instars with a maximum near the middle of the molt cycle. Regression equations describing rates of feeding, growth, respiration and ammonia excretion as functions of time during individual larval molt cycles were inserted in a simulation model, in order to analyse time-dependent patterns of variation as well as in bioenergetic efficiencies. Carbon was initially increased and nitrogen showed a tendency to increase in premolt phase during individual molt cycles. Protein remained clearly the predominant biochemical constituent in larval biomass.

• Journal of the Korean Wood Science and Technology
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• v.44 no.3
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• pp.440-448
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• 2016

As recent buildings become more air tight, the natural ventilation rate is significantly reduced and it leads to difficulty in removing accumulated moisture in buildings. Hot and humid weather in summer and the large amount of moisture caused by indoor activity are the major factors of moisture problem in Korea. The hygrothermal behavior of building environment has to be considered carefully to reduce condensation risk and mold growth potential, and comfortable indoor environment. In this study, we evaluated hygrothermal behavior of Standard Wood-frame Structure published in the Korea Rural Community Corporation Using WUFI simulation program. The results indicated that the total water contents of wood wall measured in 2014 was lower than wood wall in 2010. As a result of evaluation by separating the farming and fishing areas, Moisture problems in fishing area became larger. The walls had a significant impact on the relative humidity than the temperature each areas. Furthermore, excessive water content problem of the wood-based material was reduced in the wall that could be applied in the fishing villages by changing the outdoor finishing materials. And Mold growth risk on the interior materials could be removed through the different setting of the indoor temperature during summertime.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.228-232
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• 2018

Process-based crop models have been used to assess the impact of climate change on crop production. These models are implemented in procedural or object oriented computer programming languages including FORTRAN, C++, Delphi, Java, which have a stiff learning curve. The requirement for a high level of computer programming is one of barriers for efforts to develop and improve crop models based on biophysical process. In this study, we attempted to develop a Chinese cabbage model using Microsoft Excel with Visual Basic for Application (VBA), which would be easy enough for most agricultural scientists to develop a simple model for crop growth simulation. Results from Soil-Plant-Atmosphere-Research (SPAR) experiments under six temperature conditions were used to determine parameters of the Chinese cabbage model. During a plant growing season in SPAR chambers, numbers of leaves, leaf areas, growth rate of plants were measured six times. Leaf photosynthesis was also measured using LI-6400 Potable Photosynthesis System. Farquhar, von Caemmerer, and Berry (FvCB) model was used to simulate a leaf-level photosynthesis process. A sun/shade model was used to scale up to canopy-level photosynthesis. An Excel add-in, which is a small VBA program to assist crop modeling, was used to implement a Chinese cabbage model under the environment of Excel organizing all of equations into a single set of crop model. The model was able to simulate hourly changes in photosynthesis, growth rate, and other physiological variables using meteorological input data. Estimates and measurements of dry weight obtained from six SPAR chambers were linearly related ($R^2=0.985$). This result indicated that the Excel/VBA can be widely used for many crop scientists to develop crop models.

• Fire Science and Engineering
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• v.23 no.5
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• pp.57-65
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• 2009

This study was intended to conduct a Real-scale fire test to predict the fire behavior by unit space at the apartment building where a huge casualties and injuries are likely. After setting the inflammables inside the house, the test aimed to identify the fire characteristics to each unit item was carried out. The house was divided into 4 unit space such as kitchen, living room, bedroom and a study for a real scale fire test. As a result, bedroom reached to flashover state in 5minutes after setting the fire, indicating a rapid fire growth such as 7433.3kW of maximum thermal emissivity, 578.6ppm of carbon monoxide, 1.25ppm of carbon dioxide and $1,350^{\circ}C$ of maximum indoor temperature. Particularly, the fire growth was made up to critical temperature which might cause a severe damage to the people within 3minutes, if the fire were not extinguished at inflammable space at the early stage of fire, which stressed the need of early response. The result of a real scale fire test could be compared with the outcome of expanded simulation test and used in predicting the fire spread at the space for different use.

• Fire Science and Engineering
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• v.32 no.1
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• pp.16-23
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• 2018

In a closed-compartment with various configurations, the correlation that can predict the maximum heat release rate (HRR) with the changes in internal volume and fire growth rate was investigated numerically. The volume of the compartment was controlled by varying the length ratio based on the bottom surface shape of the ISO 9705 fire room, where the ceiling height was fixed to 2.4 m. As a main result, the effect of a change in ceiling height on the maximum HRR was examined by a comparison with a previous study that considered the change in ceiling height. In addition, a more generalized correlation equation was proposed that could predict the maximum HRR in closed-compartments regardless of the changes in ceiling height. This correlation had an average error of 7% and a maximum error of 19% for various fire growth rates when compared with the numerical results. Finally, the applicability of the proposed correlation to representative fire compartments applied to the domestic performance-based design (PBD) was examined. These results are expected to provide useful information on predicting the maximum HRR caused by flashover in closed-compartments as well as the input information required in a fire simulation.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.8
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• pp.1188-1196
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• 2016

This study evaluated the risk of Clostridium perfringens (C. perfringens) foodborne illness from natural and processed cheeses. Microbial risk assessment in this study was conducted according to four steps: hazard identification, hazard characterization, exposure assessment, and risk characterization. The hazard identification of C. perfringens on cheese was identified through literature, and dose response models were utilized for hazard characterization of the pathogen. For exposure assessment, the prevalence of C. perfringens, storage temperatures, storage time, and annual amounts of cheese consumption were surveyed. Eventually, a simulation model was developed using the collected data and the simulation result was used to estimate the probability of C. perfringens foodborne illness by cheese consumption with @RISK. C. perfringens was determined to be low risk on cheese based on hazard identification, and the exponential model ($r=1.82{\times}10^{-11}$) was deemed appropriate for hazard characterization. Annual amounts of natural and processed cheese consumption were $12.40{\pm}19.43g$ and $19.46{\pm}14.39g$, respectively. Since the contamination levels of C. perfringens on natural (0.30 Log CFU/g) and processed cheeses (0.45 Log CFU/g) were below the detection limit, the initial contamination levels of natural and processed cheeses were estimated by beta distribution (${\alpha}1=1$, ${\alpha}2=91$; ${\alpha}1=1$, ${\alpha}2=309$)${\times}$uniform distribution (a = 0, b = 2; a = 0, b = 2.8) to be -2.35 and -2.73 Log CFU/g, respectively. Moreover, no growth of C. perfringens was observed for exposure assessment to simulated conditions of distribution and storage. These data were used for risk characterization by a simulation model, and the mean values of the probability of C. perfringens foodborne illness by cheese consumption per person per day for natural and processed cheeses were $9.57{\times}10^{-14}$ and $3.58{\times}10^{-14}$, respectively. These results indicate that probability of C. perfringens foodborne illness by consumption cheese is low, and it can be used to establish microbial criteria for C. perfringens on natural and processed cheeses.