• Journal of computational fluids engineering
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• v.14 no.2
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• pp.68-76
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• 2009

The sloshing tank causes the instability of the fluid flows and the fluctuation of the impact pressure by the liquid on the tank. These flow characteristics inside the sloshing tank can generate the uncomfortable sloshing noise. In the present study, a numerical analysis for the reduction of a fuel tank sloshing noise was performed. To simulate the flow characteristics in a sloshing tank with partially filled liquid, a VOF method was used for interfacial flows by applying a momentum source term for the sloshing motion in a non-inertial reference frame. This numerical method was verified by comparing its results with the available experimental data. For the reduction of the sloshing noise, the horizontal and vertical baffles and porous media inside a sloshing tank were considered and numerically analyzed in the present study. For various installations of these baffles and porous media, the characteristics of the liquid behavior in the sloshing tank were obtained along with the impact pressure on the wall and the height of the free surface along the wall. These basic results can be used for the design of the actual vehicular fuel tank with the reduced sloshing noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.