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On vanishing theorems for locally conformally flat Riemannian manifolds
Dang Tuyen Nguyen,Duc Thoan Pham 대한수학회 2022 대한수학회보 Vol.59 No.2
In this paper, we obtain some vanishing theorems for $p$-harmonic 1-forms on locally conformally flat Riemannian manifolds which admit an integral pinching condition on the curvature operators.
Camber effect on the stability and power performance of a right-swing hydrofoil turbine
Nguyen Le Dang Hai,Le Tuyen Quang,Jeong Dasom,고진환 대한조선학회 2022 International Journal of Naval Architecture and Oc Vol.14 No.1
In this study, performance of a right-swing turbine with a cambered hydrofoil was analyzed by CFD numerical simulations to assess its stability and power efficiency. It is found from the analysis that the right-swing trajectory, which is close to the kinematics of flying or swimming creatures, has advantages over the left-swing trajectory in terms of stability with a slight loss of the power efficiency. A cambered hydrofoil can be utilized to offset this loss, but doing so negatively affects the stability at the turning positions of the flapping motion. Consequently, in order to guarantee stability and high efficiency of a right-swing hydrofoil turbine, camber shapes adjustable at the positions of flapping motion, which is an excellent feature of flight and swimming creatures, are mandatory. Eventually, the analysis results of this study will be utilized to develop a high-performance flapping hydrofoil turbine.
Learning a Self-driving Bicycle Using Deep Deterministic Policy Gradient
Tuyen P. Le,Nguyen Dang Quang,SeungYoon Choi,TaeChoong Chung 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
This paper improves the method for learning a bicycle which can itself balance and go to any specified locations. The bicycle is controlled by a neural network policy which is learned by deep deterministic policy gradient algorithm (DDPG). We propose a procedure which allows the controller can be gradually learned until it can stably balance and lead the bicycle to any specified places.
Nguyen Van Tuyen,Lawrence A. Limjuco,이기세,Nhat Minh Dang 한국공업화학회 2022 공업화학 Vol.33 No.3
Microalgae is becoming a vital component for a circular economy and ultimately for sustainable development. Herein, recent developments in different outcomes of microalgae for wastewater treatment and biorefinery were reviewed. From its primary function as a third-generation resource of biofuel, the usage of microalgae has been diversified as an integral element for the CO2 sequestration and production of economically valuable products (e.g., pharmaceuticals, animal feeds, biofertilizer, biochar, etc.). Principles and recent challenges for each microalgae application were presented to suggest a motivation for future research and the direction of development. The integration of microalgae within the concept of the circular economy was also discussed with various routes of microalgae-based biorefinery.
( Nguyen Van Tuyen ),( Tran Hung Thuan ),( Chu Xuan Quang ),( Nhat Minh Dang ) 한국공업화학회 2023 공업화학 Vol.34 No.5
The effect of temperature and influent alkalinity/ammonia (K/A) ratio on the start-up of the partial nitrification (PN) process for an activated sludge-based domestic wastewater treatment was studied. Two different sequence batch reactors (SBR) were operated at 26 °C and 32 °C. The relationship between temperature and the concentration of free ammonia (FA) and free acid nitrite (FNA) was investigated. A stable PN process was achieved in the 32 °C reactor when the influent ammonium concentration was lower than 150 mg-N/L. In contrast, the PN process in the 26 °C reactor had a higher nitrite accumulation rate (NAR) and ammonium removal efficiency (ARE) when the influent ammonia concentration was increased to more than 150 mg-N/L. Then three different ranges of the K/A ratio were applied to an SBR reactor. In the K/A range of 2.48~1.65, the SBR reactor achieved the highest NAR ratio (75.78%). This ratio helps to achieve the appropriate level of alkalinity to maintain a stable pH and provide a sufficient amount of inorganic carbon source for the activity of microorganisms. At the same time, FA and FNA values also reached the threshold to inhibit nitrite-oxidizing bacteria (NOB) without a significant effect on ammonia-oxidizing bacteria (AOB). Results showed that the control of temperature and K/A ratio during the start-up period may be important in establishing a stable and steady PN process for the treatment of domestic wastewater.
The manufacturing of sintered bricks from clay and red mud derived from the alumina processing plant
Ngoc Tuyen Tran,Duc Vu Quyen Nguyen,Van Minh Hai Ho,Xuan Tin Dang,Ngoc Quang Tran 한양대학교 청정에너지연구소 2017 Journal of Ceramic Processing Research Vol.18 No.5
In this study, the manufacturing of sintered bricks from clay and red mud was presented. The initial materials and obtainedbricks were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope(TEM), X-ray fluorescence (XRF), and differential scanning calorimetry-thermal gravimetry (DSC-TG). The compressivestrength, water absorption, bulk density and sintering shrinkage of sintered bricks were performed. The effects of componentsof raw materials, sintering temperature and time on physico-mechanical properties of the products was investigated. Theresults showed that the bricks prepared at 1000 oC for 1 hr with raw material containing up to 50% of red mud providedexcellent physico-mechanical properties. The obtained brick met the Vietnam standard VS1451-1998 and was satisfied theconstruction material requirements that were safe to human’s health and friendly with environment in terms of alkalineleaching and radioactivity indexes.
Anh Linh Dang,Tuyen Quang Nguyen,Tri Thien Cao,Vinh Quang Dinh,Vinh Dinh Nguyen 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
Traffic detection is a topic of great interest in recent years due to a high demand for better traffic detection systems. Existing traffic detection algorithms work well under ideal driving conditions, however their performance decreases under difficult conditions such as insufficient lighting and illumination. Recently, local patterns have been successfully applied in order to handle complex texture conditions, such as stereo matching, and texture classification. We propose a method that applies Local Tetra Pattern for data preprocessing, so as to improve the performance of deep learning models under said conditions. Our approach achieved better performance than the original raw-models while the changes in inference time are maintained within a negligible interval. By fusing local patterns and raw images, the model gains an acquisition of discriminative information in regions that are highly similar. In challenging conditions, these kinds of information are essential for the model to recover its consciousness of concerned objects which cause many re-cognitional obstructions. Experimental results show a percentage as high as 35.847%, an increase of 12.575% in comparison with the original result on the SKKU data set.