• 한국전산유체공학회:학술대회논문집
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• 1998.05a
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• pp.138-144
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• 1998

The BGK equation, which is the kinetic model equation of Boltzmann equation, is solved using FDDO(finite difference with the discrete-ordinate method) to compute the rarefied flow of monatomic gas. Using reduced velocity distribution and discrete ordinate method, the scalar equation is transformed into a system of hyperbolic equations. High resolution ENO(Essentially Non-Oscillatory) scheme based on Harten-Yee's MFA(Modified Flux Approach) method with Strang-type explicit time integration is applied to solve the system equations. The calculated results are well compared with the experimental density field of NACA0012 airfoil, validating the developed computer code. Next. the computed results of circular cylinder flow for various Knudsen numbers are compared with the DSMC(Direct Simulation Monte Carlo) results by Vogenitz et al. The present scheme is found to be useful and efficient far the analysis of two-dimensional rarefied gas flows, especially in the transitional flow regime, when compared with the DSMC method.

• Journal of Communications and Networks
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• v.6 no.3
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• pp.197-202
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• 2004

This work presents a stability analysis of the synchronous state for one-way master-slave time distribution networks with single star topology. Using bifurcation theory, the dynamical behavior of second-order phase-locked loops employed to extract the synchronous state in each node is analyzed in function of the constitutive parameters. Two usual inputs, the step and the ramp phase perturbations, are supposed to appear in the master node and, in each case, the existence and the stability of the synchronous state are studied. For parameter combinations resulting in non-hyperbolic synchronous states the linear approximation does not provide any information, even about the local behavior of the system. In this case, the center manifold theorem permits the construction of an equivalent vector field representing the asymptotic behavior of the original system in a local neighborhood of these points. Thus, the local stability can be determined.

• International Journal of Aerospace System Engineering
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• v.7 no.2
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• pp.6-12
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• 2020

The precise prediction of future position of satellite depends on the accurate determination of orbit, which is also helpful in performing orbit maneuvers and trajectory correction maneuvers. For estimating the orbit of satellite many methods are being used. Some of the conventional methods are based on (i) Differential Correction (DC) (ii) Extended Kalman Filter (EKF). In this paper, Differential Evolution (DE) is used to determine the orbit. Orbit Determination using DC and EKF requires some initial guess of the state vector to initiate the algorithm, whereas DE does not require an initial guess since a wide range of bounds for the design unknown variables (orbital elements) is sufficient. This technique is uniformly valid for all orbits viz. circular, elliptic or hyperbolic. Simulated observations have been used to demonstrate the performance of the method. The observations are generated by including random noise. The simulation model that generates the observations includes the perturbation due to non-spherical earth up to second zonal harmonic term.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.337-348
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• 2021

Brillouin Optical Frequency Domain Analysis (BOFDA) is a distributed fiber optic sensing (DFOS) technique that has unique advantages for performance monitoring of piles. However, the complicated production process and harsh operating environment of offshore PHC pipe piles make it difficult to apply this method to pile load testing. In this study, sensing cables were successfully pre-installed into an offshore PHC pipe pile directly for the first time and the BOFDA technique was used for in-situ monitoring of the pile under axial load. High-resolution strain and internal force distributions along the pile were obtained by the BOFDA sensing system. A finite element analysis incorporating the Degradation and Hardening Hyperbolic Model (DHHM) was carried out to evaluate and predict the performance of the pile, which provides an improved insight into the offshore pile-soil interaction mechanism.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.359-368
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• 1996

This paper introduces PGD(Preprocessed Givens Downdating)and PHD(Preprocessed Hyperbolic Downdating) algorithms, wherein a multiple-row observation matrix $Z^T$ is factorized into a partial Cholesky factor Rz, such that $Z^T$ = $Q_zR_z, Q_zQ^T_z=I$, and then Rz is recursively downdated by using GD(Givens Downdating)and HD(Hyperbolic Dondating), respectively. Time complexities of PGD and PHD algorithms are $pn^2$ ＋ $5n^3/6$ 및 $pn^2$＋$n^3/3$ flops, respectively, if p$\geq$n, while those of the existing GD and HD are known to be $5pn^2/2$ and $2pn^2$ flops,, respectively. This concludes that the factorization of observation matrices, which we call preprocessing, would improve the overall performance of the downdating process. Benchmarks on the Sun SPARC/2 system also show that preprocessing would shorten the required downdating times compared to those of downdatings without preprocessing. Furthermore, benchmarks also show that PHD provides better performance than PGD.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.1-11
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• 2021

To develop an efficient procedure related to the flamelet library, the machine learning process based on artificial neural network(ANN) is applied for the gaseous hydrogen/liquid oxygen combustor under a supercritical pressure condition. For hidden layers, 25 combinations based on Rectified Linear Unit(ReLU) and hyperbolic tangent are adopted to find an optimum architecture in terms of the computational efficiency and the training performance. For activation functions, the hyperbolic tangent is proper to get the high learning performance for accurate properties. A transformation learning data is proposed to improve the training performance. When the optimal node is arranged for the 4 hidden layers, it is found to be the most efficient in terms of training performance and computational cost. Compared to the interpolation procedure, the ANN procedure reduces computational time and system memory by 37% and 99.98%, respectively.

• Coupled systems mechanics
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• v.3 no.3
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• pp.267-289
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• 2014

A proper physical modeling of infilled building frame-foundation beam-soil mass interaction system is needed to predict more realistic and accurate structural behavior under static vertical loading. This is achieved via finite element method considering the superstructure, foundation and soil mass as a single integral compatible structural unit. The physical modelling is achieved via use of finite element method, which requires the use of variety of isoparametric elements with different degrees of freedom. The unbounded domain of the soil mass has been discretized with coupled finite-infinite elements to achieve computational economy. The nonlinearity of soil mass plays an important role in the redistribution of forces in the superstructure. The nonlinear behaviour of the soil mass is modeled using hyperbolic model. The incremental-iterative nonlinear solution algorithm has been adopted for carrying out the nonlinear elastic interaction analysis of a two-bay two-storey infilled building frame. The frame and the infill have been considered to behave in linear elastic manner, whereas the subsoil in nonlinear elastic manner. In this paper, the computational methodology adopted for nonlinear soil-structure interaction analysis of infilled frame-foundation-soil system has been presented.

• Structural Engineering and Mechanics
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• v.13 no.2
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• pp.187-209
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• 2002

The infrastructure system in the United States has been aging faster than the resource available to restore them. Therefore decision for allocating the resources is based in part on the condition of the structural system. This paper proposes to use neural network to predict the overall rating of the structural system because of the successful applications of neural network to other fields which require a "symptom-diagnostic" type relationship. The goal of this paper is to illustrate the potential of using neural network in civil engineering applications and, particularly, in bridge evaluations. Data collected by the Tennessee Department of Transportation were used as "test bed" for the study. Multi-layer feed forward networks were developed using the Levenberg-Marquardt training algorithm. All the neural networks consisted of at least one hidden layer of neurons. Hyperbolic tangent transfer functions were used in the first hidden layer and log-sigmoid transfer functions were used in the subsequent hidden and output layers. The best performing neural network consisted of three hidden layers. This network contained three neurons in the first hidden layer, two neurons in the second hidden layer and one neuron in the third hidden layer. The neural network performed well based on a target error of 10%. The results of this study indicate that the potential for using neural networks for the evaluation of infrastructure systems is very good.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.601-611
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• 2005

In this paper, an active vibration control of a tensioned, elastic, axially moving string is investigated. The dynamics of the translating string are described with a non-linear partial differential equation coupled with an ordinary differential equation. A right boundary control to suppress the transverse vibrations of the translating continuum is proposed. The control law is derived via the Lyapunov second method. The exponential stability of the closed-loop system is verified. The effectiveness of the proposed control law is simulated.

• Journal of the Ergonomics Society of Korea
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• v.30 no.2
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• pp.319-330
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• 2011

In computer forensics investigation, the investigators collect, protect, analyze and interpret massive amount of data which were used in cyber crime. However, due to its huge amount of information, it takes a great deal of time and errors often result even when they use forensics investigation tool in the process. The information visualization techniques will greatly help to improve the information processing ability of human when they deal with the overwhelming amount of data and have to find out significant information in it. The importance of Intrusion Detection System(IDS) among network forensics is being emphasized in computer forensics. In this study, we apply the information visualization techniques which are proposed to be a great help to IDS and carry out the usability test to find out the most effective information visualization techniques for IDS.