• Atmosphere
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• v.27 no.2
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.204-212
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• 2010

This study was performed in 22 unthinned Larix olgensis plantations in northeast China. Data were collected on 95 sample trees of different canopy positions and the diameter at breast height ($d_{1.3}$) ranged from 5.7 cm to 40.2 cm. The individual tree models for the prediction of vertical distribution of live crown, branch and needle biomass were built. Our study showed that the crown, branch and needle biomass distributions were most in the location of 60% crown length. These results were also parallel to previous crown studies. The cumulative relative biomass of live crown, branch and needle were fitted by the sigmoid shape curve and the fitting results were quite well. Meanwhile, we developed the crown ratio and width models. Tree height was the most important predictor for crown ratio model. A negative competition factor, ccf and bas which reflected the effect of suppression on a tree, reduced the crown ratio estimates. The height-diameter ratio was a significant predictor. The higher the height-diameter ratio, the higher crown ratio is. Diameter at breast height is the strongest predictor in crown width model. The models can be used for the planning of harvesting operations, for the selection of feasible harvesting methods, and for the estimation of nutrient removals of different harvesting practices.

• Journal of Welding and Joining
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• v.17 no.5
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• pp.40-46
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• 1999

The sensors employed in the robotic are welding system must detect the changes in weld characteristics and produce the output that is in some way related to the change being detected. Such adaptive systems, which synchronise the robot arm and eyes using a primitive brain will form the basis for the development of robotic GMA(Gas Metal Arc) welding which increasingly higher levels of artificial intelligence. The objective of this paper is to realize the mapping characteristics of bead height through learning. After learning, the neural estimation can estimate the bead height desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.145-152
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• 1996

In this study, the technique to evaluate the extreme design wave height of certain return period is developed from the given measured or hindcasted sea state data of concerned area for limited period. By using the order statistics and Monte Carlo Simulation method, the best fit probability distribution function with proper parameters describing the given wave height data is chosen, from which extreme design wave height can be predicted by extrapolation to the desired return period. The fitness and the confidence limit of the chosen probability function are also discussed. Application calculation is carried out for the wave height data given by applying the Wilson wave model theory to major 50 typhoon wind data affecting Korean South coast during the year from 1938 to 1987.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2194-2199
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• 2007

An experimental study is performed to investigate the thermal and flow characteristics of subcooled liquid nitrogen in a natural circulation loop. Experimental apparatus is designed and constructed such that a closed loop is cooled at the top by a cryocooler and heated nearly at the bottom by cartridge heaters. Steady state is obtained by controlling the heating power to the cartridge heaters and a thin-film heater to reduce the cooling power of the cryocooler. Temperature is measured at several locations of the loop and the mass flow rate through the loop is estimated from the energy balance in terms of the measured temperatures. Experiment is repeated for various values of the vertical height between the cooling and heating parts. The results show that the heat transfer capability of the loop has a maximum at a certain value of height. The optimal height to maximize the heat transfer is in a good agreement with analytical prediction to take into account the buoyancy and viscous forces in the loop.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.208-213
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• 2001

Objective of this paper is to develop a new approach involving the use of an Artificial Neural Network(ANN) and multiple regression methods in the prediction of process parameters on bead height for GMA welding process. Using a series of robotic are welding, multi-pass butt welds carried out in order to verify the performance of the neural network estimator and multiple regression methods. To verify the developed system, the design parameters of the neural network estimator are selected from an estimation error analysis. The experimental results show that the proposed models can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.517-520
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• 2003

The snow-fatting measurement system including the snow sensor applying the photo-coupler is investigated in this study and using this snow sensor the height of snow fallen is measured. To measure the snow depth, five photo sensors are arranged with 5 mm distance. The snow-falling measurement system, which is measuring the motor revolution controlled with stepping motor, is mounted above the snow surface. From this work, it is feasible to measure quantitatively the snow on real time. Its software implements a proven method to achieve valid measurements also under difficult conditions as future study. In cases where the snow sensor is applieded to the prediction of snow in the meteorological observation system and the snow removing system, it is recommend the GRS-Option in order to improve the quality of snow measurements for better compensation.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.93-95
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• 2007

Studies on ski-end shape control at the top end of rolling plate in heavy thick plate mill by using FEM analysis and measuring system have been performed. Plate shape behaviour at the top-end on rolling by the two different methods in finishing rolling process has been observed. One is to minimize the height of ski-end by using pass line based on the relational model between shape factor and pick-up and the other one is to prevent turn down problem caused by the impact between table roller and down bended plate on rolling by using roll speed difference. To minimize the height of ski-end, the prediction models based on the FEM analysis and measuring data was developed. The control method of ski - end shape on finishing rolling process was applied in actual mill and the height of ski-end was reduced by about 50% compared with conventional operation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.111-112
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• 2008

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.849-851
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• 2011