• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.9
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• pp.825-834
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• 2008

Nose chine shape optimization study has been performed to maximize the directional stability at high angle of attack supersonic flow. Various chine shapes are generated using super ellipse equation. By numerically investigating the directional stability characteristics of those shapes, the baseline configuration for the shape optimization has been selected using the three-dimensional Navier-Stokes equations. The configuration is represented by the NURBS curves which can adjust the surface geometry by the control points. The response surfaces are constructed to obtain optimum shape which has high directional stability characteristics and lift-to-drag ratio. From this study, an efficient configuration design and optimization process which utilizes the parameter-based configuration generation techniques and approximation method has been established, then 29% improvement of the directional stability by strong vortexes from chine nose is accomplished.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.7
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• pp.575-580
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• 2007

During the conceptual design phase of a canard type high maneuverable aircraft, the low speed small scale wind tunnel test was conducted to investigate the high angle-of-attack static stability of the aircraft. In this study, 1/50th scale generic canard-body-wing model was used for the small scale wind tunnel test. For the analysis of static stability including high angle-of-attack nonlinear characteristics, the vertical tail effects were studied due to canard deflections. In addition, the nose chine effects were studied at high angle-of-attack. Based on the results obtained from the experimental study, the configuration change effects for canard type aircraft on high angle-of-attack static stability have been able to analyze.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1495-1504
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• 2012

This paper proposes an algorithm to classify and analyze facial features such as eyebrow, eye, mouth and chin based on the geometric features of the face. As a preprocessing process to classify and analyze the facial features, the algorithm extracts the facial features such as eyebrow, eye, nose, mouth and chin. From the extracted facial features, it detects the shape and form information and the ratio of distance between the features and formulated them to evaluation functions to classify 12 eyebrows types, 3 eyes types, 9 mouth types and 4 chine types. Using these facial features, it analyzes a face. The face analysis algorithm contains the information about pixel distribution and gradient of each feature. In other words, the algorithm analyzes a face by comparing such information about the features.