• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.201-208
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• 2019

Numerical integration is necessary for satellite orbit determination and its prediction. The numerical integration algorithm can be divided into single-step and multi-step method. There are lots of single-step and multi-step methods. However, the Runge-Kutta method in single-step and the Adams method in multi-step are generally used in global navigation satellite system (GNSS) satellite orbit. In this study, 4th and 8th order Runge-Kutta methods and various order of Adams-Bashforth-Moulton methods were used for GLObal NAvigation Satellite System (GLONASS) orbit integration using its broadcast ephemeris and these methods were compared with international GNSS service (IGS) final products for 7days. As a result, the RMSE of Runge-Kutta methods were 3.13m and 4th and 8th order Runge-Kutta results were very close and also 3rd to 9th order Adams-Bashforth-Moulton results. About result of computation time, this study showed that 4th order Runge-Kutta was the fastest. However, in case of 8th order Runge-Kutta, it was faster than 14th order Adams-Bashforth-Moulton but slower than 13th order Adams-Bashforth-Moulton in this study.

• Kyungpook Mathematical Journal
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• v.56 no.2
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• pp.311-327
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• 2016

In this paper, we propose an error embedded Runge-Kutta method to improve the traditional embedded Runge-Kutta method. The proposed scheme can be applied into most explicit embedded Runge-Kutta methods. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. These solution and error are obtained by solving an initial value problem whose solution has the information of the error at each integration step. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. For the assessment of the effectiveness, the van der Pol equation and another one having a difficulty for the global error control are numerically solved. Finally, a two-body Kepler problem is also used to assess the efficiency of the proposed algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.573-578
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• 2010

Precise determination of satellite positions is necessary to improve positioning accuracy in GNSS. In this study, GLONASS orbits were predicted from broadcast ephemeris using the 4th-order Runge-Kutta numerical integration method and their accuracy dependence on the integration step and the integration time was analyzed. The 3D RMS (Root Mean Square) differences between the results from I-second integration step and 300-second integration step was about 3 cm, but the processing time was one hundred times less for the I-second integration time case. For trials of different integration times, the 3D RMS errors were 8.3 m, 187.3 m, and 661.5 m for 30-, 150-, and 300-minutes of integration time, respectively. Though this integration-time analysis, we concluded that the accuracy gets higher with a shorter integration time. Thus we suggest forward and backward integration methods to improve GLONASS positioning accuracy, and with this method we can achieve a 5-meter level of 3-D orbit accuracy.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.3
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• pp.264-270
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• 2011

This paper deals with dynamic response of a beam structure with discrete spring-damper supports under a moving mass. Governing equations of motion taking into account of all inertia effects of the moving mass were derived by Galerkin's mode summation method, and Runge-Kutta integration method was applied to solve the differential equations. The effects of the speed of the moving mass, spring stiffness, damping coefficient, span number of a beam structure, mass ratio of the moving mass on the dynamic response of the beam structure have been studied. Some numerical results provide design engineers for the beam structure design with discrete supports under a moving mass.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.868-873
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• 2003

This paper deals with the linear dynamic response of an elastically restrained beam under a moving mass, where the elastic support was modelled by translational springs of variable stiffness. Governing equations of motion taking into account of all inertia effects of the moving mass were derived by Galerkin's mode summation method, and Runge-Kutta integration method was applied to solve the differential equations. The effects of the speed, the magnitude of the moving mass, stiffness and the position of the support springs on the response of the beam have been studied. A variety of numerical results allows us to draw important conclusions for structural design purposes.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.383-388
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• 1991

This paper analizes two numerical integration methods, both based on the Runge Kutta 4-th order formula for deterministic systems, for digital simulation of a differential equation driven by white noise. It is shown that a "standard' Runge Kutta method for stochasitic systems yields solutions of Stratonovich differential equations, while Riggs and Phillips' method results in solutions of Ito differential equations. Therefore the white noise differential equation must be converted into the equivalent Ito equation before the latter method is used. Digital simulation results for a simple differential equation are also presented.nted.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.4
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• pp.365-373
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• 2011

This paper presents the dynamic response and the vibration characteristics for a rail-track supported by discrete springs and dampers. Recently, automatic conveyer system, rail-track, rack-master system demand the soundproof facilities and vibration suppression measures in order to satisfy the strict environmental standards. The equations of motions of the dynamic characteristics for a vibration suppression rail-track under a traveling mass were derived by Galerkin's mode summation method considering gravity, centrifugal force, Coriolis force, inertia force of the moving mass, transverse inertia of the rail-track. Also, numerical results were calculated by Runge-Kutta integration method. In order to investigate vibration characteristics and dynamic responses, modal testing and measurement of the responses of the rail-track were performed. Through the experiment and numerical simulations, numerical results have a good agreement with experimental ones.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.87-99
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• 1994

Reynolds Averaged Navier-Stokes equations are solved numerically for the computation of turbulent flow around a Wigley double model. A second order finite difference method is applied for the spatial discretization on the nonstaggered grid system and 4-stage Runge-Kutta scheme for the numerical integration in time. In order to increase the time step, residual averaging scheme of Jameson is adopted. Pressure field is obtained by solving the pressure-Poisson equation with the appropriate Neumann boundary condition. For the turbulence closure, 0-equation turbulence model of Baldwin-Lomax is used. Numerical computation is carried out for the Reynolds number of 4.5 million. Comparisons of the computed results with the available experimental data show good agreements for the velocity and pressure distributions.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.15-20
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• 2006

This paper describes research on intelligent game character through performance enhancements of physics engine in computer games. The algorithm that recognizes the physics situation uses momentum back-propagation neural networks. Also, we present an experiment and its results, integration methods that display optimum performance based on the physics situation. In this experiment on integration methods, the Euler method was shown to produce the best results in terms of fps in a simulation environment with collision detection. Simulation with collision detection was shown similar fps for all three methods and the Runge-kutta method was shown the greatest accuracy. In the experiment on physics situation recognition, a physics situation recognition algorithm where the number of input layers (number of physical parameters) and output layers (destruction value for the master car) is fixed has shown the best performance when the number of hidden layers is 3 and the learning count number is 30,000. Since we tested with rigid bodies only, we are currently studying efficient physics situation recognition for soft body objects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.1
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• pp.1-7
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• 1990

A method is developed for solving the elastica of cantilever beam subjected to a tip point load and uniform load. The Bernoulli-Euler differential equation of deflected beam is used. The Runge-Kutta method and the Regula Falsi method are used to perform the integration of the differential eqution and to determine the horizontal deflection, respectively. The horizontal and vertical deflections of the free end, and the free-end rotations are calculated for a range of parameters representing variations in tip point load and uniform load. All results are presented in nondimensional forms. And some typical elastic are also presented.