• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.116-119
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• 2009

HSPF is a comprehensive, continuous, lumped parameter, watershed-scale model that simulates the movement of water, sediment, and a wide range of water quality constituents on pervious and impervious surfaces, in soil profiles, and within streams and well-mixed reservoirs. The hydrologic calibration of HSPF is performed manually using the decision-support software Expert System for the Calibration of HSPF (HSPEXP). The initial values for the HSPF hydrologic parameters were estimated based on guidance from BASINS Technical Note 6. Initial parameter values were adjusted for the study watershed during the calibration period within the recommended ranges for the parameters.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.657-664
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• 1999

This paper introduced the basic theory of LRCS(Linear Reservoir and Channel System) rainfall runoff model proposed by Korean researchers(Lee and Lee, 1995), and discussed the change of model output according to objective functions in sensitivity analysis and calibration process of model. It proposed "hat" matrix and affluence measures for affluence analysis of parameters in calibration, and investigated relationship between change of model output according to error propagation in parameter estimation, and sensitivity of model output according to variance of model output and change of parameters. Accuracy of parameter estimates was known by analysis of sensitivity coefficient, diagonal element $h_i$ and $D_i$._i$.

• Geomechanics and Engineering
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• v.22 no.1
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• pp.97-108
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• 2020

The time-consuming and less objectivity are the main problems of conventional micromechanical parameters calibration method of Particle Flow Code simulations. Thus this study aims to address these two limitation of the conventional "trial-and-error" method. A new calibration method for the linear parallel bond model (CM-LPBM) is proposed. First, numerical simulations are conducted based on the results of the uniaxial compression tests on limestone. The macroscopic response of the numerical model agrees well with the results of the uniaxial compression tests. To reduce the number of the independent micromechanical parameters, numerical simulations are then carried out. Based on the results of the orthogonal experiments and the multi-factor variance analysis, main micromechanical parameters affecting the macro parameters of rocks are proposed. The macro-micro parameter functions are ultimately established using multiple linear regression, and the iteration correction formulas of the micromechanical parameters are obtained. To further verify the validity of the proposed method, a case study is carried out. The error between the macro mechanical response and the numerical results is less than 5%. Hence the calibration method, i.e., the CM-LPBM, is reliable for obtaining the micromechanical parameters quickly and accurately, providing reference for the calibration of micromechanical parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1256-1265
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• 2011

Automated parking assist systems are being commercialized and rapidly spread in the market. In order to improve odometry accuracy, we proposed a practical odometry calibration scheme of Car-Like Mobile Robot (CLMR). However, there were some open problems in our prior work. For example, it was not clear whether the kinematic parameters always converged or not using the proposed calibration scheme. In addition, test driving had to be carried out "twice" without detailed explanation. This research aims to provide answers for the addressed questions though the convergence property analysis of the calibration scheme. In this paper, we evaluate on the effect of the kinematic parameter error on the odometry error at the final pose by numerical computation. The evaluation will show that the wheel diameter and tread of the CLMR can be calibrated by iterative test drives. In addition, the region of convergence in the parametric space will be discussed. Presented experimental results clearly showed that the proposed calibration scheme would be useful in practical applications.

• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.549-559
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• 1997

A multiply-connected network unsteady flow model for the main reach of the Han River is developed. It is a variable parameter model which allows variable roughness coefficient for each computational point according to the spatial position and the value of discharge. Sensitivities of the model to roughness coefficient and weir-flow discharge coefficient are tested, and as a result Manning's roughness coefficient is selected as the calibration parameter. The model is calibrated and verified using the records of the past flood events. A modified Gauss-Newton method is used for the optimal calibration of roughness coefficients. From the calibration of variable parameter model, spatial variation and discharge dependence of Manning's roughness coefficient are identified. That is, the roughness coefficient is higher for the upstream reach of the Wangsook stream Junction, and it decreases as the discharge increases. It turns out through the verification that the stages calculated by the variable parameter model agree better with the observed than those by the conventional single parameter model. Spatial variation of the roughness coefficient appears to be more significant than the dependence of the discharge.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.665-674
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• 1999

This paper confirmed the applicability of model to Korean rivers through the calibration and sensitivity analysis of LRCS rainfall runoff model for 18 storm events of Songriweon station in Nakdong river system, and achieved that LS and WLS were better than LAD by model fitting results. Diagonal element of "hat" matrix and affluence measures were used by analysis of parameter estimates, and parameter IL was the most important parameter in model output. By the results of error propagation according to parameter error, parameters IL, TP, F1 were affected by error propagation, and this is measure of sensitivity for the model output. This paper confirmed the relationship of calibration and sensitivity analysis of model through analysis of sensitivity coefficient, diagonal element $h_i$ and $D_i$._i$.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.368-377
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• 2009

In this paper we study the gyro bias calibration method of SDINS(Strap-Down Inertial Navigation System). Generally, SDINS's calibration is performed in 2-axis(or 3-axis) rate table with chamber for varying ambient temperature. We assumed that the majority of calibration-parameter except for gyro bias is knowned. During gyrobias calibration procedure, it can be induced some disturbances(accelerometer's short-term error induced rate table rotation and anti-vibration mount's rotation). In these cases, old gyro-bias calibration methods(using velocity error or attitude error) have an error, because these disturbances are not detectable at the same time. So that, we propose a new gyro-bias calibration method(heading error minimizing using equivalent linear transformation) that can detect anti-vibration mount's rotation. And we confirm efficiency of the new gyro-bias calibration method by simulation.

• Journal of applied mathematics & informatics
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• v.11 no.1_2
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• pp.327-340
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• 2003

For motion analysis electromagnetic sensors are often used to measure positions and orientations of human subjects. It is observed from several experiments of the Ergonomics Research group that there exist systematic errors and unexpected serious distortions due to some metal masses in the test area. A calibration process is necessary to fix these errors. In this article three models are proposed to correct position measurement errors based on observations from calibration experiments.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.109-114
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.63-70
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• 2017

The purpose of this study was to calibrate the hydrologic parameters of SWAT model and analyze the daily runoff for the study watershed using SWAT-CUP. The Hardware watershed is located in Virginia, USA. The watershed area is $356.15km^2$, and the land use accounts for 73.4 % of forest and 23.2 % of pasture. Input data for the SWAT model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1990 to 1994 was used for calibration and from 1997 to 2005 was for validation. The SUFI-2 module of the SWAT-CUP program was used to calibrate the hydrologic parameters. The parameters were calibrated for the highly sensitive parameters presented in previous studies. The P-factor, R-factor, $R^2$, Nash-Sutcliffe efficiency (NS), and average flow were used for the goodness-of-fit measures. The applicability of the model was evaluated by sequentially increasing the number of applied parameters from 4 to 11. In this study, 10-parameter set was accepted for calibration in consideration of goodness-of-fit measures. For the calibration period, P-factor was 0.85, R-factor was 1.76, $R^2$ was 0.51 and NS was 0.49. The model was validated using the adjusted ranges of selected parameters. For the validation period, P-factor was 0.78, R-factor was 1.60, $R^2$ was 0.60 and NS was 0.57.