• The Korean Journal of Rheology
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• v.11 no.2
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• pp.91-96
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• 1999

Semiconductive polyaniline and its derivatives such as poly(aniline-co-sodium diphenylamine sulfonate), poly (aniline-co-o-ethoxyaniline), poly (o-methylaniline), and poly (o-methoxyaniline) were synthesized, and then adopted as suspending particles of the electrorheological (ER) fluids. All suspensions of these polyaniline derivatives showed typical ER properties under high applied electric fields. However, flow behaviors are observed to be quite different depending on the polyaniline derivatives, especially in the stress plateau regions obtained at low shear rates. Using a scaling law, we also obtained universal cures of ER fluids from the flow curves at each applied electric field based on the relationship between the dynamic yield stress with the applied electric field and flow curve changes according to the electric fields.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1655-1658
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• 1997

To obtain aircraft dynamic parameters, various estimation methods such as Maximum Likelihood, Linear Regression are applied. In this paper we adopt the extended Kalman filter(EKF) to estimate the stability and control derivatives in aircraft dynamic models from flight test data. The extended Kalman filter is applied to nonlinear augmented system assuming that unknown parameters are additional states. In this work, the results of the extended Kalman filter are compared with the results of the wind tunnel test using Chang Gong-91 aircraft flight test data.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.61-69
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• 1999

A dynamic stability test was performed to determine dynamic stability derivatives for the pure pitching motion of air-to-ground missile model in the low speed wind tunnel. The free vibration technique was employed to acquire oscillation characteristics of the model for damping coefficients. Damping coefficients are obtained by the method of logarithmic decrement. Results show good damping effects and stability capability at Mach numbers 0.1 and 0.2, with the angle of attack ranging from -15 to +20 degrees.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1663-1666
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• 1997

The purpose of this paper is to find how to determine the controllability and stability derivatives form flight test and to display the stability of the Twinbee aircraft. There are various methods developed to find the derivatives : wind tunnel testing, predicted result from empirical data, flight test and so on. Among those methods, the estimation form flight test of real aricraft is the most reliable. We performed the flight test of Twinbee and recorded the states of aorcraft. Using those states and parameter setimation algorithem based on the Maximum Likdlihood(MMLE) criterion, we can estimate the controllability and stability derivatives. In this paper, wel will show the process form designing the proper flight test input to estimation of derivatives.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.38-44
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• 1998

The modified maximum likelihood estimation method is used to estimate the nondimensional aerodynamic derivatives of a single turbo-prop aircraft at a specified flight condition for the best deduction of the dynamic characteristics. In wind axes the six degree of freedom equations are algebraically linearized so that the linear state equation contains aerodynamic derivatives in a state-space form and is used in the maximum likelihood method. The simulated data added with the measurement noise is used as a flight test data which is necessary to the estimation of nondimensional aerodynamic derivatives. It is obtained by implementing the 6-DOF nonlinear flight simulation. In the flight simulation, the effects of several control input types, control deflection amplitudes, and the turbulence intensities on the statistical convergence criteria are also examined and quantitative analysis of the results is discussed.

• Aerospace Engineering and Technology
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• v.2 no.2
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• pp.1-10
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• 2003

An airship is statically unstable, because it has no wing, comparatively small tail and large hull. Hence, an accurate prediction of dynamic stability is critical. In this study, dynamic stability data of the Mid-Size Airship is acquired through forced oscillation wind tests. The test was done in BAR LAMP which is Birhle Applied Research Inc's facility located in Germany. The test was composed with 16 static runs and 26 dynamic runs. As a result, dynamic characteristics of the airship depends on sideslip angle, angular rate and its direction as well as angle of attack. Generally, it is obtained that 3 directional moments have damping, but normal force, side force, and cross-derivatives are unstable. The dynamic derivatives are not sensitive to control surfaces, but have nonlinear dependency on sideslip angle.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.7
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• pp.552-561
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• 2016

In this experimental study, the dynamic stability derivatives of a tailless lambda-shape UAV are estimated from time history data of aerodynamic moments measured from the internal balance while the test model is forced to oscillate at given frequencies and amplitudes. A 3-axis forced oscillation apparatus is designed to induce decoupled roll, yaw, pitch oscillations respectively. The results show that the roll damping derivatives remain stable at the entire range of angle of attack tested, whereas the pitch damping derivatives become unstable beyond $15^{\circ}$ angle of attack. The amplitude and frequency have little impact on roll damping derivatives while the smaller amplitude and frequency of oscillation improves the pitch stability. The yaw damping derivative values are fairly small as expected for a tailless configuration. The results indicate that the proposed methodology and test apparatus area valid for estimating the dynamic stability derivatives of a tailless UAV.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.90-93
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• 2006

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.526-531
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• 1992

Partial derivatives are easily computed analytically assuming that all the geometric information is known. However, there are computational difficulties in getting accurate partial derivatives directly from a range image since an image is a discrete version of continuous data contaminated with some noise. In this paper, we develop a general window function to compute partial derivatives based on the least square surface fitting method. A dynamic selective surface fitting method is introduced to make the window less sensitive to noise. Any degree of partial derivative can be obtained by a simple convolution between an image and window functions.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.8-16
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• 2006

This paper discusses design sensitivity analysis and its application to a structural dynamics modification. Eigenvalue derivatives are determined with respect to the element parameters, which include intrinsic property parameters such as Young's modulus, density of the material, diameter of a beam element, thickness of a plate element, and shape parameters. Derivatives of stiffness and mass matrices are directly calculated by derivatives of element matrices. The first and the second order derivatives of the eigenvalues are then mathematically derived from a dynamic equation of motion of FEM model. The calculation of the second order eigenvalue derivative requires the sensitivity of its corresponding eigenvector, which are developed by Nelson's direct approach. The modified eigenvalue of the structure is then evaluated by the Taylor series expansion with the first and the second derivatives of eigenvalue. Numerical examples for simple beam and plate are presented. First, eigenvalues of the structural system are numerically calculated. Second, the sensitivities of eigenvalues are then evaluated with respect to the element intrinsic parameters. The most effective parameter is determined by comparing sensitivities. Finally, we predict the modified eigenvalue by Taylor series expansion with the derivatives of eigenvalue for single parameter or multi parameters. The examples illustrate the effectiveness of the eigenvalue sensitivity analysis for the optimization of the structures.