• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1065-1071
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• 2009

Satellite application services can be divided into realtime services like voice communications and non-real time services like traditional data communications. To support both types of services on the same On-Board Switching(OBS), a scheduler which depends on their service classes is required. A fixed priority scheduling policy has a starvation problem. In this paper we propose a scheduling scheme based on premium and age. Premium is a fixed value which is given to a certain class of services. Age is another parameter of the scheduling policy and it will be increased by one for every scheduling cycle. The scheme we propose chooses a packet which has the largest sum of its age and premium. Simulation results indicate that the proposed approach shows better performance in both average cell delay and std-dev of cell delay for the lower class of service. There is no staying in infinite starvation state.

• Journal of Power Electronics
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• v.13 no.4
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• pp.516-527
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• 2013

This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.703-710
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• 2011

Odor emission from domestic sewer systems has become a serious environmental problem. An investigation on a sewer manhole revealed that anaerobic decay of sediment organic matters (SOMs) and related declines of oxidation reduction potential (ORP) in the sediment layer were the main reason of the production of volatile sulfur compounds. In addition, as the anaerobic decaying period continued, the odor intensity rapidly increased with increasing concentrations of $H_2S$ and dimethyl sulfide. As a feasible method to control SOMs and to minimize odor emission potentials, an electrolytic oxidation process has been employed to the sediment sludge phase. In this study, voltages applied to the electrolytic oxidation process were varied as a main system parameter, and its effects on odor removal efficiencies and reaction characteristics were investigated. At the applied voltages greater than 20 V, the system efficiently oxidized the organic matter, and the ORP in the sludge phase increased rapidly. As a consequence, the removal efficiency of hydrogen sulfide was found to be >99% within 60 minutes of the electrolytic oxidation. Overall, the electrolytic oxidation process can be an alternative to control odor emission from sewer systems, and a threshold input energy needs to be determined to achieve effective operation of the process.

• Tunnel and Underground Space
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• v.24 no.4
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• pp.282-288
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• 2014

Stoping method has been acknowledged as one of the typical metalliferous underground mining methods. Notwithstanding with the popularity of the method, the majority of stoping mines are suffering from excessive unplanned dilution which often becomes as the main cause of mine closure. Thus a reliable unplanned dilution management system is imperatively needed. In this study, reliable unplanned dilution prediction system is introduced by adopting artificial neural network (ANN) based on data investigated from one underground stoping mine in Western Australia. In addition, contributions of input parameters were analysed by connection weight algorithm (CWA). To validate the reliability of the proposed ANN, correlation coefficient (R) was calculated in the training and test stage which shown relatively high correlation of 0.9641 in training and 0.7933 in test stage. As results of CWA application, BHL (Length of blast hole) and SFJ (Safety factor of Joint orientation) show comparatively high contribution of 18.78% and 19.77% which imply that these are somewhat critical influential parameter of unplanned dilution.

• Journal of Korean Society of Steel Construction
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• v.12 no.2 s.45
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• pp.197-207
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• 2000

A transient heat transfer analysis and thermo-elastic analysis have been performed for the residual stress distribution on the fillet weldment used by finite element method. Specimen is fabricated single-pass fillet welding. This computation was performed for conditions including surface heat flux and temperature dependent thermo-physical properties using by heat input as parameter. Also, cut-off temperature of residual stress estimation by thermo-elastic analysis is determined. The fillet weldment were measured to determined their residual stress distributions for using hole-drilling method. As result, it was found that large tensile residual stress is about material yield strength, and the numerical simulation results for finite element method similar to residual stresses by hole-drilling method and other exiting research. Also, cut-off temperature is effectively determined by temperature which calculated maximum thermal stress equal to material yield strength.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.419-425
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• 2004

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera. Our approach is to only compute three vanishing points without informations such as the focal length and rotation matrix from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector v. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.67-75
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• 2004

In this study, real-time forecasting model(Neural Dam Inflow Forecasting Model; NDIFM) based on neural network to predict the dam inflow which is occurred by flood runoff is developed and applied to check its availability for the operation of multi-purpose reservoir Developed model Is applied to predict the flood Inflow on dam Nam-Gang in Nak-dong river basin where the rate of flood control dependent on reservoir operation is high. The input data for this model are average rainfall data composed of mean areal rainfall of upstream basin from dam location, observed inflow data, and predicted inflow data. As a result of the simulation for flood inflow forecasting, it is found that NDIFM-I is the best predictive model for real-time operation. In addition, the results of forecasting used on NDIFM-II and NDIFM-III are not bad and these models showed wide range of applicability for real-time forecasting. Consequently, if the quality of observed hydrological data is improved, it is expected that the neural network model which is black-box model can be utilized for real-time flood forecasting rather than conceptual models of which physical parameter is complex.

• Journal of Welding and Joining
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• v.28 no.5
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• pp.51-57
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• 2010

Brittle microstructure created in a heat affected zone (HAZ) during the welding of low alloy steel can be eliminated by post-weld heat treatment (PWHT). If the PWHT is not possible during a repair welding, the controlled bead depositions of multi-pass welding should be applied to obtain tempering effect on the HAZ without PWHT. In order to anticipate and control the tempering effect during the temper bead welding, the definition of temperature curve obtained from the analytical solution was suggested in this research. Because the analytical solution for heat flow is expressed as a mathematical equation of weld parameters, it may be effective in anticipating the effect of each weld parameter on the tempering in HAZ during the successive bead depositions. The reheating effect by the successive bead layer on the brittle coarse grained HAZ formed by earlier bead deposition was estimated by comparing the overlapped distance between the temperature curves in the HAZ. Three layered weld specimens of SA508 base metal with A52 filler were prepared by controlling heat input ratio between layers. The tempering effect anticipated by using the overlapped distance between the temperature curves was verified by measuring the micro-hardness distribution in the HAZ of prepared specimens. The temperature curve obtained from analytical solution was expected as a good tool to find optimal temper bead welding conditions.

• Journal of Korean Society on Water Environment
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• v.34 no.3
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• pp.328-338
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• 2018

The objective of this study was to evaluate the applicability of a HSPF (Hydrological Simulation Program-Fortran) model for runoff estimation in the Namgang dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input for the HSPF model, which was calibrated and validated using observed runoff data from 2004 to 2015 for three stations (Sancheong, Shinan, Changchon) in the study watershed. Parameters for runoff calibration were selected based on the user's manual and references, and parameter calibration was done by trial and error. The $R^2$ (determination coefficient), RMSE (root-mean-square error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (relative mean absolute error) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within a ${\pm}5%$ error in Sancheong and Shinan, whereas there was a14% error in Changchon. The model performance criteria for calibration and validation showed that $R^2$ ranged from 0.80 to 0.92, RMSE was 2.33 to 2.39 mm/day, NSE was 0.71 to 0.85, and RMAE was 0.37 to 0.57 mm/day for daily runoff. Visual inspection showed that the simulated daily flow, monthly flow, and flow exceedance graph agreed well with observations for the Sancheong and Shinan stations, whereas the simulated flow was higher than observed at the Changchon station.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3_1spc
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• pp.518-524
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• 2013

Recently, probabilistic assessments of nuclear power plant components have generated interest in the nuclear industries, either for the efficient inspection and maintenance of older nuclear plants or for improving the safety and cost-effective design of newly constructed nuclear plants. In the present paper, the partial safety factor (PSF) of wall-thinned nuclear piping is evaluated based on a reliability index method, from which the effect of each statistical variable (assessment parameter) on a certain target probability is evaluated. In order to calculate the PSF of a wall-thinned pipe, a limit state function based on the load and resistance factor design (LRFD) concept is first constructed. As for the reliability assessment method, both the advanced first-order second moment (AFOSM) method and second-order reliability method (SORM) are employed to determine the PSF of each probabilistic variable. The present results can be used for developing maintenance strategies considering the priorities of input variables for structural integrity assessments of wall-thinned piping, and this PSF concept can also be applied to the optimal design of the components of newly constructed plants considering the target reliability levels.