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RISS 인기검색어
- 검색키워드
- 저자 : Hoang Quan Dinh (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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The Study of Mach Waves Generated by a Roughness Element
Hoang Quan Dinh,Anh Tuan Nguyen,Ivan Vladimirovich Egorov,Ngoc Hai Duong 한국항공우주학회 2022 International Journal of Aeronautical and Space Sc Vol.23 No.3
In this paper, a simplified inviscid boundary condition is applied to solve the problem of Mach waves generated by a roughness element on the wall surface of a supersonic wind tunnel. The geometry of the roughness element is simplified by a parabolic function, to which mathematical formulas are introduced to model the boundary condition. These techniques help simplify the problem and minimize the required computer resources for the simulation performance. Using the direct numerical simulation (DNS) method while employing the above-mentioned techniques, the authors can simulate the generation and the propagation of Mach waves from a roughness element at a Mach number of 2.5. The result shows that a pair of Mach waves are generated at the leading and trailing edges of the roughness element and oscillate with small amplitudes. We also study the effect of the height of the element, the flow speed, the Reynolds number, and the unsteadiness of the flow on the simulation result. The numerical result is compared with published experimental data for the validation.
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FGW-FER: Lightweight Facial Expression Recognition with Attention
Huy-Hoang Dinh,Hong-Quan Do,Trung-Tung Doan,Cuong Le,Ngo Xuan Bach,Tu Minh Phuong,Viet-Vu Vu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9
The field of facial expression recognition (FER) has been actively researched to improve human-computer interaction. In recent years, deep learning techniques have gained popularity for addressing FER, with numerous studies proposing end-to-end frameworks that stack or widen significant convolutional neural network layers. While this has led to improved performance, it has also resulted in larger model sizes and longer inference times. To overcome this challenge, our work introduces a novel lightweight model architecture. The architecture incorporates three key factors: Depth-wise Separable Convolution, Residual Block, and Attention Modules. By doing so, we aim to strike a balance between model size, inference speed, and accuracy in FER tasks. Through extensive experimentation on popular benchmark FER datasets, our proposed method has demonstrated promising results. Notably, it stands out due to its substantial reduction in parameter count and faster inference time, while maintaining accuracy levels comparable to other lightweight models discussed in the existing literature.
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Effect of boattail angle on near-wake flow and drag of axisymmetric models: a numerical approach
The Hung Tran,Hoang Quan Dinh,Hoang Quan Chu,Van Quang Duong,Chung Pham,Van Minh Do 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.2
Flow behavior around axisymmetric boattail surface was studied by numerical methods. A wide range of boattail angles from 0° to 24° was investigated to find the drag trend of the model. Numerical simulation was validated by experimental results with the same flow conditions. Results showed that the use of boattail model always has a positive effect on drag reduction. Total drag showed minimum value at boattail model of around 14°. Length of the recirculation after body decreases with increasing boattail angle up to 14° and then becomes constant at higher angle. The trend of boattail pressure drag showed similar to previous studies for high-speed flow. However, base drag showed different trend to previous observation. The base drag showed to be the most important parameter to determine drag trend of the model. The effect of flow fields around boattail on pressure distribution and drag is discussed in detail.
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