• Journal of the Society of Naval Architects of Korea
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• v.61 no.4
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• pp.226-235
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• 2024

A method for quantifying the adaptability of ship maneuver scenarios for data-driven modeling of ship dynamics is developed based on the principal component analysis. A random maneuver scenario is suggested as a reference for ship dynamics, which can obtain the converged principal components of ship dynamics features by the Monte Carlo simulation. Principal components of conventional maneuver scenarios defined by the International Maritime Organization (IMO) are compared to that of the random maneuver. A conventional ship dynamics model for a container carrier vessel for four degrees of freedom dynamics is introduced to simulate the random and IMO maneuver scenarios. It is confirmed that the IMO tests follow the tendency of random maneuver scenario in terms of execution time and adaptability.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.4
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• pp.465-472
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• 2008

An automotive windshield wiper system is modeled mainly for vibration analysis purpose. The model is composed of solid links, ideal joints, imperfect joints to simulate unavoidable manufacturing defects and bushings having stiffness, contact between a wiper blade and a wind screen glass, friction, a spring and an actuator. Main stream of wiper dynamics analysis has been obtaining a closed form of system of equations using Newton's or Lagrange's formula and doing a numerical simulation study to understand and predict the behavior of it. However, the modeling process is complex since a wiper system is of multibody and a contact problem occurs. When imperfection, such as dead zone of a joint and stiffness of a rubber bushing, should be included, the added complexity makes the modeling difficult. Since the imperfection is understood as main cause of problematic vibration, the dynamics model of a wiper system aiming vibration analysis should include such unavoidable manufacturing defects in the model. An open form of dynamic model of a automotive windshield wiper system with imperfect joints using a commercial software is obtained and a simulation analyssis is conducted for vibration reduction study.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.5
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• pp.414-422
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• 2005

This paper shows the results of atomistic modeling for the Interaction between spherical nano abrasive and substrate In chemical mechanical polishing processes. Atomistic modeling was achieved from 2-dimensional molecular dynamics simulations using the Lennard-jones 12-6 potentials. We proposed and investigated three mechanical models: (1) Constant Force Model; (2) Constant Depth Model, (3) Variable Force Model, and three chemical models, such as (1) Chemically Reactive Surface Model, (2) Chemically Passivating Surface Model, and (3) Chemically Passivating-reactive Surface Model. From the results obtained from classical molecular dynamics simulations for these models, we concluded that atomistic chemical mechanical polishing model based on both Variable Force Model and Chemically Passivating-reactive Surface Model were the most suitable for realistic simulation of chemical mechanical polishing in the atomic scale. The proposed model can be extended to investigate the 3-dimensional chemical mechanical polishing processes in the atomic scale.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.1
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• pp.88-98
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• 2014

A supercavitation is modern technology that can be used to reduce the frictional resistance of the underwater vehicle. In the process of reaching the supercavity condition which cavity envelops whole vehicle body, a vehicle passes through transition phase from fully-wetted to supercaviting operation. During this phase of flight, unsteady hydrodynamic forces and moments are created by partial cavity. In this paper, analytical and numerical investigations into the dynamics of supercavitating vehicle in transition phase are presented. The ventilated cavity model is used to lead rapid supercavity condition, when the cavitation number is relatively high. Immersion depth of fins and body, which is decided by the cavity profile, is calculated to determine hydrodynamical effects on the body. Additionally, the frictional drag reduction associated by the downstream flow is considered. Numerical simulation for depth tracking control is performed to verify modeling quality using PID controller. Depth command is transformed to attitude control using double loop control structure.

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.229.1-229.1
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• 2007

• International Journal of Aeronautical and Space Sciences
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• v.18 no.2
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• pp.197-205
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• 2017

We investigate the slat noise generation mechanism by using large-eddy simulation (LES) and simple source modeling based on linearized Euler equations. An incompressible LES of an MD 30P30N three-element airfoil in the high-lift configuration is conducted at $Re_c=1.7{\times}10^6$. Using the total derivative of the hydrodynamic pressure (DP/Dt) acquired from the incompressible LES, representative noise sources in the slat cove region are characterized in terms of simple sources such as frequency-specific monopoles and dipoles. Acoustic radiation around the 30P30N multi-element airfoil is effectively computed using the Brinkman penalization method incorporated with the linearized Euler equation. The directivity pattern of $p^{\prime}_{rms}$ at $r=20c_{slat}$ in the multiple sources is closely compared to that obtained by the application of the LES/Ffowcs-Williams and Hawking's methods to the entire flow field. The power spectrum of p' at ${\theta}=290^{\circ}$ is in good agreement with the data reported in BANC-III, especially the broadband part of the spectrum with a decaying slope ${\propto}f^{-3}$.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.233-236
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• 1996

This paper describes a liner state-space model for a flexible stick balencer. The method employed to generate the model utilizes a separable formulation of assumed modes to represents the transverse displacement due to bending Lagrangian dynamics are applied to determine the kinetic and potential energies for the system. The resultant dynamic equations are then organized into a state space model and linearized using Taylor series expansion method. A minimum order observer is designed to estimate unmeasurable states.

• 한국전산유체공학회:학술대회논문집
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• 1999.05a
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• pp.1-10
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• 1999

This paper briefly introduces the work done up to 1998 during the past twenty years for numerical modeling of ocean process focussing on the neighbouring seas of Korean Peninsula. Modeling of global ocean dynamics has also been performed as a pathway to understand the regional ocean dynamics. The ocean simulation produces a vast amount of multidimensional multivariate dataset therefore adoption of scientific and technical visualization techniques were essential to properly understand the physics involved.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.133-136
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• 2000

In recent years, hybrid neural network approaches which combine neural networks and mechanistic models have been gaining considerable interests. These approaches are potentially very efficient to obtain more accurate predictions of process dynamics by combining mechanistic and neural models in such a way that the neural network model properly captures unknown and nonlinear parts of the mechanistic model. In this work, such an approach was applied in the modeling of a full-scale coke wastewater treatment process. First, a simplified mechanistic model was developed based on the Activated Sludge Model No.1 and the specific process knowledge, Then neural network was incorporated with the mechanistic model to compensate the errors between the mechanistic model and the process data. Simulation and actual process data showed that the hybrid modeling approach could predict accurate process dynamics of industrial wastewater treatment plant. The promising results indicated that the hybrid modeling approach could be a useful tool for accurate and cost-effective modeling of biochemical processes.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.18-21
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• 1996

Even though there are several deterministic methods for the modeling of linear systems, there is no standard method for the modeling of nonlinear systems. For the modeling of nonlinear systems we have applied the genetic programming method to estimate nonlinear time sereis. We get the time series from the simple known nonlinear dynamics, and fed those to genetic programming. For the tested nonlinear systems, suggested method estimated the nonlinear dynamics correctly.