• Atmosphere
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• v.34 no.1
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• pp.23-34
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• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.7-14
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• 2010

In order to analyze the vibro-impacts in the torsional system, several clearance types of nonlinearities should be included with the analytical or numerical method. These kinds of nonlinear factors can cause the errors while the system is calculated specifically with the numerical method, also it might take too long to get right answers with the every nonlinearity in the original system. Therefore, there are several methods developed for the sake of overcoming the deficiency of the analysis with the original system and saving the calculating time. The original system can be reduced by keeping the system characteristics such as from 14 to 6 DOF. Especially, since the torque flow in the torsional system is connected with the specific gear ratios, the original system can be transferred into the simpler system corresponding to each gear ratio rather than the original system, which can also show the same system characteristics such as the natural frequencies and the mode shapes. By using the reduced system, the calculating time can be saved and the redundant nonlinear effects for the system analysis can be ignored without any numerical errors.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.2
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• pp.161-170
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• 2013

The flow and combustion characteristics in a premixed swirl combustor with a double cone burner are numerically analyzed to adopt a swirler model. The internal recirculation zone formed at the burner exit can be realized by a swirler with inner and outer diameters of 56 and 152 mm, respectively, and accordingly, the flow rate and radial velocity were determined. To select the tangential velocity, swirl and recirculation angles are introduced. A tangential velocity of 40 m/s produces an internal recirculation zone similar to that in a combustor. At the liner exit, the errors in temperature and velocity are 2.8% and 0%, respectively, and they are negligibly small. However, NOx emissions are underestimated by 67% in the numerical results obtained using the swirler model. Although considerable quantitative errors are induced by the swirler model, it can be useful numerical model for the EV burner because it can approximately simulate the essential flow and combustion characteristics in a premixed swirl combustor with a double cone burner and it is expected to make combustion analysis efficient in a gas turbine combustor with complex geometries.

• Smart Structures and Systems
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• v.20 no.2
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• pp.127-137
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• 2017

Identification of damping characteristics is of significant importance for dynamic response analysis and condition assessment of structural systems. Damping is associated with the behavior of the energy dissipation mechanism. Identification of damping ratios based on the sensitivity of dynamic responses and the model updating technique is investigated with numerical and experimental investigations. The effectiveness and performance of using the sensitivity-based model updating method and vibration monitoring data for damping ratios identification are investigated. Numerical studies on a three-dimensional truss bridge model are conducted to verify the effectiveness of the proposed approach. Measurement noise effect and the initial finite element modelling errors are considered. The results demonstrate that the damping ratio identification with the proposed approach is not sensitive to the noise effect but could be affected significantly by the modelling errors. Experimental studies on a steel planar frame structure are conducted. The robustness and performance of the proposed damping identification approach are investigated with real measured vibration data. The results demonstrate that the proposed approach has a decent and reliable performance to identify the damping ratios.

• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.218-232
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• 2015

Piecewise linear (G01-based) tool paths generated by CAM systems lack $G_1$ and $G_2$ continuity. The discontinuity causes vibration and unnecessary hesitation during machining. To ensure efficient high-speed machining, a method to improve the continuity of the tool paths is required, such as B-spline fitting that approximates G01 paths with B-spline curves. Conventional B-spline fitting approaches cannot be directly used for tool path B-spline fitting, because they have shortages such as numerical instability, lack of chord error constraint, and lack of assurance of a usable result. Progressive and Iterative Approximation for Least Squares (LSPIA) is an efficient method for data fitting that solves the numerical instability problem. However, it does not consider chord errors and needs more work to ensure ironclad results for commercial applications. In this paper, we use LSPIA method incorporating Energy term (ELSPIA) to avoid the numerical instability, and lower chord errors by using stretching energy term. We implement several algorithm improvements, including (1) an improved technique for initial control point determination over Dominant Point Method, (2) an algorithm that updates foot point parameters as needed, (3) analysis of the degrees of freedom of control points to insert new control points only when needed, (4) chord error refinement using a similar ELSPIA method with the above enhancements. The proposed approach can generate a shape-preserving B-spline curve. Experiments with data analysis and machining tests are presented for verification of quality and efficiency. Comparisons with other known solutions are included to evaluate the worthiness of the proposed solution.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.91-96
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• 2001

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamics, and a sliding mode control is introduced to attenuate the effects of the neural network's reconstruction errors and the disturbances of AUV's dynamics. The presented controller is consist of three parallel schemes; linear feedback control, sliding mode control and neural network. Lyapunov theory is used to guarantee the asymptotic convergence of trajectory tracking errors and the neural network's weights errors. Numerical simulations for motion control of an AUV are performed to illustrate to effectiveness of the proposed techniques.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.17-26
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• 1989

This paper is concerned with forecasting the existing number of errors in the computer software and optimizing the stopping time of the software test based upon the forecasted number of errors. The most commonly used models have assessed software reliability under the assumption that the software failure late is proportional to the current fault content of the software but invariant to time since software faults are independents of others and equally likely to cause a failure during testing. In practice, it has been observed that in many situations, the failure rate decrease. Hence, this paper proposes a mathematical model to describe testing situations where the failure rate of software limearly decreases proportional to testing time. The least square method is used to estimate parameters of the mathematical model. A cost model to optimize the software testing time is also proposed. In this cost mode two cost factors are considered. The first cost is to test execution cost directly proportional to test time and the second cost is the failure cost incurred after delivery of the software to user. The failure cost is assumed to be proportional to the number of errors remained in the software at the test stopping time. The optimal stopping time is determined to minimize the total cost, which is the sum of test execution cast and the failure cost. A numerical example is solved to illustrate the proposed procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5370-5393
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• 2019

In this paper, we consider a two-way relay non-orthogonal multiple access (TWR-NOMA) system with residual hardware impairments (RHIs) and channel estimation errors (CEEs), where two group users exchange their information via the decode-and-forward (DF) relay by using NOMA protocol. To evaluate the performance of the considered system, exact analytical expressions for the outage probability of the two groups users are derived in closed-form. Moreover, the asymptotic outage behavior in the high signal-to-noise ratio (SNR) regime is examined and the diversity order is derived and discussed. Numerical simulation results verify the accuracy of theoretical analyses, and show that: i) RHIs and CEEs have a deleterious effects on the outage probabilities; ii) CEEs have significant effects on the performance of the near user; iii) Due to the RHIs, CEEs, inter-group interference and intra-group interference, there exists error floors for the outage probability.

• Environmental Engineering Research
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• v.21 no.2
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• pp.171-179
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• 2016

This study analyzes guidelines to select optimum number of grids to represent behavior of a given water system appropriately. The EFDC model was chosen as a 3-D hydrodynamic and water quality model and salt was chosen as a surrogate variable of pollutant. The model is applied to an artificial canal that receives salt water from coastal area and fresh water from a river from respective gate according to previously developed gate operation rule. Grids are subdivided in vertical and horizontal (longitudinal) directions, respectively until no significant changes are found in salinity concentrations. The optimum grid size was determined by comparing errors in average salt concentrations between a test grid systems against the most complicated grid system. MSE (mean squared error) and MAE (mean absolute error) are used to compare errors. The CFL (Courant-Friedrichs-Lewy) number was used to determine the optimum number of grid systems for the study site though it can be used when explicit numerical method is applied only. This study suggests errors seem acceptable when both MSE and MAE are less than unity approximately.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.