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Tri, Nguyen Minh,Truong, Dinh Quang,Thinh, Do Hoang,Binh, Phan Cong,Dung, Dang Tri,Lee, Seyoung,Park, Hyung Gyu,Ahn, Kyoung Kwan Elsevier 2016 RENEWABLE ENERGY Vol.97 No.-
<P><B>Abstract</B></P> <P>This paper introduces a novel control approach to maximizing the output energy of an adjustable slope angle wave energy converter (ASAWEC) with oil-hydraulic power take-off. Different from typical floating-buoy WECs, the ASAWEC is capable of capturing wave energy from both heave and surge modes of wave motions. For different waves, online determination of the titling angle plays a significant role in optimizing the overall efficiency of the ASAWEC. To enhance this task, the proposed method was developed based on a learning vector quantitative neural network (LVQNN) algorithm. First, the LVQNN-based supervisor controller detects wave conditions and directly produces the optimal titling angles. Second, a so-called efficiency optimization mechanism (EOM) with a secondary controller was designed to regulate automatically the ASAWEC slope angle to the desired value sent from the supervisor controller. A prototype of the ASAWEC was fabricated and a series of simulations and experiments was performed to train the supervisor controller and validate the effectiveness of the proposed control approach with regular waves. The results indicated that the system could reach the optimal angle within 2s and subsequently, the output energy could be maximized. Compared to the performance of a system with a vertically fixed slope angle, an increase of 5% in the overall efficiency was achieved. In addition, simulations of the controlled system were performed with irregular waves to confirm the applicability of the proposed approach in practice.</P> <P><B>Highlights</B></P> <P> <UL> <LI> This paper proposes a novel energy maximization algorithm of a sliding-buoy wave energy converter (SBWEC). </LI> <LI> An efficiency optimization mechanism is designed and integrated into the SBWEC. </LI> <LI> The control logic is based on a learning vector quantitative neural network for classifying the wave information. </LI> <LI> The effectiveness of the proposed approach is verified through both simulations and experiments. </LI> </UL> </P>
Nguyen Le Minh Tri,김지태,Bach Long Giang,T.M. Al Tahtamouni,Pham Thi Huong,이창하,Nguyen Minh Viet,Do Quang Trung 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.80 No.-
In this study a novel Ag-doped graphitic carbon nitride (g-C3N4) photocatalyst was synthesized and appliedas high efficientmaterial under solarlight towardsemerging antibiotic pollutantin hospital wastewater. Thetetracycline (TC) was chosen as a target pollutant and the content of Ag doping at 3 mmol revealed thehighest photocatalytic degradation efficiency of TC (96.8%) after 120 min under solar light irradiation. Thephotoluminescence and UV–vis analysis confirmed the enhancement of charge separation and transfer inthe graphitic carbon structure after Ag-doping. The removal efficiency of TC using g-C3N4 and Ag-doped g-C3N4 (AgCN) underdark conditions was only 25.6 and 31.8%, respectively. While under solarlight conditions,the removal efficiency of TC increased to 68.3 and 96.8% for g-C3N4 and AgCN, respectively. The reusabilityprocess showed that AgCN displayed extremely high stability after 6 cycles without significant drop inantibiotic degradation efficiency. The application of AgCN was tested for treatment of TC from hospitalwastewater and it showed high removal efficiency of 89.6% within 120 min reaction time. In addition, theintermediatesgeneratedandreductionof total organiccarbon(TOC)duringthephotocatalyticreactionweredetected to support information of possible TC removal mechanism.
Huynh Tan Nhut,Nguyen Tri Quang Hung,Tran Cong Sac,Nguyen Huynh Khanh Bang,Tran Quang Tri,Nguyen Trung Hiep,Nguyen Minh Ky 대한환경공학회 2020 Environmental Engineering Research Vol.25 No.5
This study evaluates the efficiency of domestic wastewater treatment via Sponge-Based Moving Bed Biofilm Reactor (S-MBBR). The laboratory-based treatment plan uses polyurethane sponge with a specific surface area was 260 ㎡/㎥ as a carrier. The treatment plan operated under four different organic load rate: OLR1 = 0.4 ㎏ BOD/㎥.day; OLR2 = 0.6 ㎏ BOD/㎥.day; OLR3 = 0.8 ㎏ BOD/㎥.day; and OLR4 = 1.0 ㎏ BOD/㎥.day. During 80 d of the experiment, the highest treatment efficiency was at the organic load rate of 0.4 ㎏ BOD/㎥.day, with COD, SS, TN and TP were found to be 85.0 ± 12.9%, 85.7 ± 5.3%, 68.9 ± 1.7%, and 40.3 ± 0.2%, respectively. In which, the influent SS concentration were from 117.3 to 126.0 ㎎/L, the effluent concentration were in ranged 18.0 to 34.22 ㎎/L, respectively. The values of influent and effluent COD were 298.8 ± 12.88 and 44.8 ± 3.78 ㎎/L in turn. The OLR1 influent TN, TP concentrations were respectively 47.9 ± 2.11 and 3.6 ± 0.15 ㎎/L; the effluent TN, TP concentration were 14.9 ± 0.18 and 2.2 ± 0.06 ㎎/L, respectively. The study suggests that the effluent is within the allowable limits of National technical regulation on domestic wastewater (Column B1), indicating the applicability of S-MBBR for the domestic wastewater treatment plant.
Huan Quang NGO,Thang Quyet NGUYEN,Nguyen Thanh LONG,Tung Van TRAN,Tri M. HOANG 한국유통과학회 2019 The Journal of Asian Finance, Economics and Busine Vol.6 No.3
The paper aims to examine the factors affecting brand and student decision in buying fresh milk. Combining qualitative and quantitative research methods, this study used self-completed questionnaires to investigate 520 students in Ho Chi Minh City. The results of the study show that that there are five key determinants affecting the dairy brand and student decision in buying fresh milk, including: (1) product quality, (2) fair price, (3) product promotion and customer services, (4) product convenience, and (5) reference group’s attitude to the brand. In addition, it is also found that product brand has a direct and positive impact on the student decision. The finding in this study is quite different from other existing literatures in terms of the importance level of the determinants of the student decision in buying fresh milk; specifically, in deciding to buy their fresh milk, students are often interested in the promotion and customer service, the product convenience, and the reference group for the purchase, more than in the quality and price of the product. From these findings, some managerial implications are proposed for policy-makers and relevant enterprises to have appropriate policies and strategies for their business development.