• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.19-28
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• 2006

Most conventional model updating methods must use mathematical objective function with experimental modal matrices and analytical system matrices or must use information about the gradient or higher derivatives of modal properties with respect to each updating parameter. Therefore, most conventional methods are not appropriate for complex structural system such as bridge structures due to stability problem in inverse analysis with ill-conditions. Sometimes, moreover, the updated model may have no physical meaning. In this paper, a new FE model updating method based on a hybrid optimization technique using genetic algorithm (GA) and Holder-Mead simplex method (NMS) is proposed. The performance of hybrid optimization technique on the nonlinear problem is demonstrated by the Goldstein-Price function with three local minima and one global minimum. The influence of the objective function is evaluated by the case study of a simulated 10-dof spring-mass model. Through simulated case studies, finally, the objective function is proposed to update mass as well as stiffness at the same time. And so, the proposed hybrid optimization technique is proved to be an efficient method for FE model updating.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.479-485
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• 2007

In this paper, a hierarchical simulation with an approximate implicit method is proposed in order to efficiently and plausibly animate mass-spring based cloth models. The proposed hierarchical simulation method can generate realistic motion of extremely fine mesh in interactive rate. The proposed technique employs a fast and stable simulation method which approximates the implicit integration. Although the approximate method is efficient, it is extremely inaccurate and shows excessively damped behavior. The hierarchical simulation technique proposed in this paper constructs multi-level mesh structure in order to represent the realistic appearance of cloth model and performs simulation on each level of the mesh with constraints that enforce some of the mass-points of current level to follow the movement of the previous level. This hierarchical method efficiently generates a plausible movement of a cloth model composed of large number of mass points. Moreover, this hierarchical method enables us to generate realistic wrinkles on the cloth, and the wrinkle pattern on the cloth model can be easily controlled because we can specify different contraction resistance force of springs according to their hierarchical level.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.316-321
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• 1997

The purpose of this study is to reduce the vibration noise of differential gear by reducing torque fluctuation of drive pinion shaft which causes vibration noise of differential gear in rear wheel drive vehicles. For this we developed multi-degree of freedom analysis model in which mass moment of inertia and torsional spring combined, the validity of the simulation model was checked by the field test and we examined the influence of torsional vibration of driveline elements by performing forced vibration analysis of engine excitation torque. We studied the methods for reducing torsional vibration of driveline according to the design factor of propeller shaft and examined the effects reducing vibration differential gear by applying flexible coupling.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.192-199
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• 2002

This paper demonstrates that hybrid neural-genetic multimodel parameter estimation algorithm can be applied to structured system Identification of electro-hydraulic servo system. This algorithm are consist of a recurrent incremental credit assignment (ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. We manufactured electro-hydraulic servo system and the hybrid neural-genetic multimodel parameter estimation algorithm is applied to the task to find the parameter values(mass, damping coefficient, bulk modulus, spring coefficient) which minimize total square error.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.442-447
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• 2003

This paper demonstrates that a modified hybrid neural-genetic multimodel parameter estimation algorithm can be applied to structured system identification of an electro-hydraulic servo system. This algorithm is consists of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. The modified hybrid neural-genetic multimodel parameter estimation algorithm is applied to an electro-hydraulic servo system the task to find the parameter values such as mass, damping coefficient, bulk modulus, spring coefficient and disturbance, which minimizes the total square error.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.76-82
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• 2000

본 논문에서는 환경에 구속 받는 유연 매니퓨레이터의 힘/위치에 대하여 논하고자 한다. 일반적으로, 유연 매니퓨레이터의 모델링 방법은 분포 정수 모델과 집중 정수 모델로 분류할 수 있다. 전자인 분포 정수 모델을 이용해서는 평면 1 링크, 2 링크를 대상으로 한 위치/힘 제어는 가능하나, 운동 방정식의 복잡성으로 인하여 실시간에서 다 링크 다 관절 유연 매니퓨레이터의 힘/위치를 제어하기는 어렵게 여겨져 왔다. 본 논문에서는 집중 정수 모델링 방법인 집중 스프링 질량 모델(Lumped Spring Mass Model)을 이용하여 환경에 구속받는 유연 매니퓨레이터의 운동 방정식을 산출했다 이 모델을 실험기인 유연 매니퓨레이터 ADAM(Aerospace Dual Arm Manipulators)에 적용하여 실시간 위치/힘 제어 실험을 행하였으며, MATLAB를 이용하여 해석했다. 또한, ADAMS$^{TM}$ FEM를 이용하여 분포 정수 모델을 도출하여, 해석하였으며, 이 결과와 집중 정수 모델을 이용한 MATLAB 해석의 결과, 그리고 실험 결과를 비교 분석하여 본 논문에서 제안한 구속받는 유연 매니퓨레이터의 집중 정수 모델 타당성을 입증시켰다.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.196-203
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• 2003

This paper demonstrates that an improved hybrid neural-genetic multimodel parameter estimation algorithm can be applied to the structured system identification of an electro-hydraulic servo system. This algorithm is consists of a recurrent incremental credit assignment (ICRA) neural network and a genetic algorithm, The ICRA neural network evaluates each member of a generation of model and the genetic algorithm produces new generation of model. We manufactured an electro-hydraulic servo system and the improved hybrid neural-genetic multimodel parameter estimation algorithm is applied to the task to find the parameter values, such as mass, damping coefficient, bulk modulus, spring coefficient and disturbance, which minimize total square error.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.172-175
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• 2002

Sloshing of fuel in a liquid propellant tank is an important part of the dynamic and the stability analysis of the rocket. Baffles are installed in a propellant tank to reduce the instability due to sloshing. Multi degree of spring-mass-damper model was used to model sloshing of fuel in an axisymmetric tank. The natural frequencies and damping ratios are estimated. In order to verify the estimated natural frequencies and damping ratios, tests are performed for the real propellant tank of KSR-III with single ring baffle. Results of fuel sloshing analysis are compared with those of tests.

• KSTLE International Journal
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• v.2 no.1
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• pp.75-79
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• 2001

This paper is a report on the parametric study of the friction characteristics on the direct acting type OHC valve train system. The numerical simulation was performed by using the IV-TAP. Dynamic analysis by using the lumped mass method was previously performed to define the acting load. The friction characteristics were analyzed by using the partial asperity contact model. The effects of operating conditions and major design parameters on the total driving torque were investigated. From the analytical prediction, it is found that valve spring stillness, surface roughness, and base circle radius are the main factors to reduce the frictional loss on the valve train system.

• Structural Engineering and Mechanics
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• v.21 no.1
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• pp.101-119
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• 2005

An efficient methodology is presented to evaluate the seismic behavior of a Fluid-Elevated Tank-Foundation/Soil system taking the embedment effects into accounts. The frequency-dependent cone model is used for considering the elevated tank-foundation/soil interaction and the equivalent spring-mass model given in the Eurocode-8 is used for fluid-elevated tank interaction. Both models are combined to obtain the seismic response of the systems considering the sloshing effects of the fluid and frequency-dependent properties of soil. The analysis is carried out in the frequency domain with a modal analysis procedure. The presented methodology with less computational efforts takes account of; the soil and fluid interactions, the material and radiation damping effects of the elastic half-space, and the embedment effects. Some conclusions may be summarized as follows; the sloshing response is not practically affected by the change of properties in stiff soil such as S1 and S2 and embedment but affected in soft soil. On the other hand, these responses are not affected by embedment in stiff soils but affected in soft soils.