• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.923-926
• /
• 1992

ARMA fast Transversal filter(FTF) algorithm solves the extended least squres estimation problems in a very efficient way. But unfortunately, it exhibits a very unstable behavior, due to the accumulation of round-off errors. So, in this paper, two effective method to stabilize ARMA FTF algorithm is proposed. They are based on the analysis of the propagation of the numerical errors according to a first order linear model. The proposed methods modify the numerical properties of the variables responsible for the numerical instability, while proeserving the theoretical form of the algorithm. The proposed algorithms still have the nice complexity properties of the original algorithm, but have a much more stable brhavior.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.21 no.3
• /
• pp.341-349
• /
• 1997

The characteristics of defect correction method are discussed in a sample heat conduction problem showing the numerical solution of the error correction equation can predict the error of the numerical solution of the original governing equation. A way of using defect correction method combined with the existing algorithm for the incompressible fluid flow, is proposed and subsequently tested for the driven square cavity problem. The error correction equations for the continuity equation and the momentum equations are considered to estimate the errors of the numerical solutions of the original governing equations. With this new approach, better velocity and pressure fields can be obtained by correcting the original numerical solutions using the estimated errors. These calculated errors also can be used to estimate the orders of magnitude of the errors of the original numerical solutions.

• 유체기계공업학회:학술대회논문집
• /
• 1999.12a
• /
• pp.324-332
• /
• 1999

This paper presents the artificial life algorithm which is remarkable in the area of engineering for optimum design. As artificial life organisms have a sensing system, they can find the resource which they want to find and metabolize it. And the characteristics of artificial life are emergence and dynamical interacting with environment. In other words, the micro interaction with each other in the artificial life's group results in emergent colonization in the whole system. In this paper, therefore, artificial life algorithm by using above characteristics is employed into functions optimization. The effectiveness of this proposed algorithm is verified through the numerical test of single and multi objective functions. The numerical tests also show that the proposed algorithm is superior to genetic algorithm and immune algorithm for the Multi-peak function. And artificial life algorithm is also applied to optimum design of high-speed, short journal bearings and verified through the numerical test.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2008.10b
• /
• pp.463-467
• /
• 2008

Heuristic optimization using hybrid algorithms have provided a robust and efficient approach for solving many optimization problems. In this paper, a new hybrid algorithm using adaptive genetic algorithm (aGA) and particle swarm optimization (PSO) is proposed. The proposed hybrid algorithm is applied to solve numerical optimization functions. The results are compared with those of GA and other conventional PSOs. Finally, the proposed hybrid algorithm outperforms others.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.79-87
• /
• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• Journal of the Korean Society of Safety
• /
• v.25 no.3
• /
• pp.91-99
• /
• 2010

In this study, the advanced numerical algorithm is developed which can performed the static and dynamic stochastic finite element analysis by considering the effect of uncertainties included in the member stiffness of steel cable-stayed bridges and seismic load. After conducting the linear and nonlinear initial shape analysis, the advanced numerical algorithm is the assessment tool which can performed structural the response analysis considering the static linearity and non-linearity of before or after induced intial tensile force, and examined the reliability assessment more efficiently. The verification of the developed numerical algorithm is evaluated by analyzing the regression analysis and coefficient of correlation using the direct monte carlo simulation. Also, the dynamic response characteristic and coefficient of variation of the steel cable-stayed bridge is calculated by considering the uncertainty of random variables using the developed numerical algorithm. In addition, the quantitative structural safety of the steel cable-stayed bridges is evaluated by conducting the reliability assessment based upon the dynamic stochastic finite element analysis result.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2002.10a
• /
• pp.483-488
• /
• 2002

In this paper numerical algorithm for the continuum large crack model is proposed based on the return-mapping formulation. The numerical test results show that the present algorithm works appropriately under cyclic loading. It is also shown that in continuum damage models a large crack model to prevent excessive tensile plastic strain should be used to have realistic cyclic loading simulation results.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2004.04a
• /
• pp.1-8
• /
• 2004

For the linearized differential algebraic equation of the nonlinear constrained system, exact initial values of the acceleration are needed to solve itself. It may be very troublesome to perform the inverse operation for obtaining the incremental quantities since the mass matrix contains the zero element in the diagonal. This fact makes the mass matrix impossible to be positive definite. To overcome this singularity phenomenon the mass matrix needs to be modified to allow the feasible application of predictor and corrector in the iterative computation. In this paper the proposed numerical algorithm based on the modified mass matrix combines the conventional implicit algorithm, Newton-Raphson method and Newmark method. The numerical example presents reliabilities for the proposed algorithm via comparisons of the 4th order Runge-kutta method. The proposed algorithm seems to be satisfactory even though the acceleration, Lagrange multiplier, and energy show unstable behaviour. Correspondingly, it provides one important clue to another algorithm for the enhancement of the numerical results.

• Proceedings of the KIEE Conference
• /
• 1999.11a
• /
• pp.43-51
• /
• 1999

The power flow calculations(PFc) are the most important and powerful tools in power systems engineering. The conventional power flow problem is solved generally with numerical methods such as Newton-Raphson(NR). The conventional numerical method generally have some convergency problem, which is sensitive to initial value, and numerical stability problem concerned with jacobian matrix inversion. This paper presents a new PFc algorithm based on the improved genetic algorithm (IGA) which can overcome the disadvantages mentioned above. The parameters of GA, with dynamical hierarchy of the coding system, are improved to make GA a practical algorithm in the problem of real system. Some case studies with test bus system also present to show the performance of proposed algorithm. The results of proposed algorithm are compared with the results of PFc obtained using a conventional NR method.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.4
• /
• pp.460-467
• /
• 2008

This paper presents a new numerical algorithm for the fault location estimation and arcing fault detection when a single-phase arcing ground fault occurs on a transmission line. The proposed algorithm derived in the spectrum domain is based on the synchronized voltage and current samples measured from the PMUs(Phasor Measurement Units) installed at both ends of the transmission lines. In this paper, the algorithm uses DFT(Discrete Fourier Transform) for estimation. The algorithm uses a short data window for real-time transmission line protection. Also, from the calculated arc voltage amplitude, a decision can be made whether the fault is permanent or transient. The proposed algorithm is tested through computer simulation to show its effectiveness.