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Ren B.,Dalian University of Technology | Jin Z.,China Northeast Architectural Design and Research Institute Co. | Gao R.,China Petroleum Pipeline Bureau CPP No.6 Construction Company | He M.,Dalian University of Technology | Wang Y.-X.,Dalian University of Technology
Dalian Ligong Daxue Xuebao/Journal of Dalian University of Technology | Year: 2013

A 2D SPH-DEM fluid-solid coupled numerical model is presented to simulate the hydrodynamic characteristics and motion of the armor blocks of the mound breakwater under wave force. The hydrodynamic conditions of the blocks are treated using the Riemann-CSPM revised SPH method. The solid boundaries, such as the wave maker, tank bottom and tank wall, are simulated by wall particles. The interaction forces and motions between different discretized blocks are calculated using the DEM model. The interface force equilibrium conditions are met on interface of fluid-solid. Based on the above 2D SPH-DEM coupled numerical model, the interaction of wave and armor block of mound breakwater is simulated, and the variation of flow field during the process of wave shoaling and the pressure distribution along the slope are analyzed. The impact pressures when the wave slams on the parapet are also compared with the physical model experimental results. Source


Shi W.X.,Harbin Institute of Technology | Duan Y.S.,Harbin Institute of Technology | Duan Y.S.,China Northeast Architectural Design and Research Institute Co. | Yi X.S.,Tongji University | And 3 more authors.
Desalination | Year: 2013

Nitrogen removal in polluted water with low carbon source by a membrane bioreactor-attapulgite clay integrated system was investigated, and the contribution of membrane and microorganisms to organic pollutant removal was evaluated and discussed. The result confirmed that the two MBR treatments can be effective for the removal of trace organic matters, which CODMn and UV254 were higher than 80% and 78%, respectively. Moreover, it can be also highlighted that there is a limitation of MBR in removing nitrogen (e.g. ammonia, nitrite, and nitrate) and that attapulgite clay could complement MBR well as a biological carrier. The MBR-attapulgite clay system obviously showed higher nitrogen removal efficiency; the ammonia nitrogen and total nitrogen efficiencies improved by 8% and 40% than that of MBR. Furthermore, the membrane fouling in MBR-attapulgite clay system remarkably reduced as well, which provided a longer operation time (more than 35days) before backwashing with chemical solution. ®Biological removal of nitrogen by a membrane bioreactor-attapulgite clay system in treating micro polluted water was studied.®The rejection coefficients of all kinds of nitrogen by the two different MBR systems were investigated.®Compared with MBR, membrane fouling in MBR-attapulgite clay system was a little lower. © 2013 Elsevier B.V.. Source


Guo X.-Y.,Northeastern University China | Guo X.-Y.,China Northeast Architectural Design and Research Institute Co.
Shenyang Gongye Daxue Xuebao/Journal of Shenyang University of Technology | Year: 2011

Traditional central air-conditioning system has large hysteretic, inertial and non-linear characteristics, which may cause the energy mismatch between system power supply and load energy demand in regular control method and result in the unbalance of energy supply and demand between central air-conditioning system and application environment. And thus, a great amount of electric energy is wasted. Aiming at the control performance of central air-conditioning system, a neural network based prediction control method to combine Elman neural network predictor with neural network controller was proposed. The control strategy can be adjusted real time in order to match the system energy demand and air-conditioning energy output through predicting future energy demand. With adopting the control method of combining Elman neural network predictor and neural network controller, the system exhibits good performances of dynamics and stability as well as obvious energy-saving effect. The predictive energy-saving central air-conditioning system using neural network can effectively control the relationship between the central air-conditioning system and application environment energy supply, and provide a reliable guarantee for reducing energy consumption of intelligent buildings. Source


Guo X.-Y.,Northeastern University China | Guo X.-Y.,China Northeast Architectural Design and Research Institute Co.
Shenyang Gongye Daxue Xuebao/Journal of Shenyang University of Technology | Year: 2013

Aiming at the problems that the variable air volume (VAV) central air conditioning system has such characteristics as multi-variables, large time delay and nonlinearity and the routine control algorithm exhibits such disadvantages as slow system response and low control precision, a fuzzy neural network predictive control strategy was proposed. The fuzzy neural network control was combined with the predictive control technology in the proposed method, and a compound controller model combining both fuzzy neural network and predictive control was established. Through optimizing the control mode of VAV, the predictive control of central air conditioning system was effectively realized. The results show that with adopting the proposed control method, the system exhibits good dynamic and steady performances, high control precision, obvious energy-saving effect and wide application prospect. Source


Guo X.-Y.,Northeastern University China | Guo X.-Y.,China Northeast Architectural Design and Research Institute Co.
Procedia Environmental Sciences | Year: 2011

Fuzzy Data Envelopment Analysis (DEA) evaluation model in Airport Construction Energy-saving have improved incomplete weight deficiency of information processing. Firstly, indices values were converted to trapezoid fuzzy numbers, then with incomplete information on indices weights as constraints, a fuzzy DEA model with outputs only and preference was established, and then by applying the α-cut approach, the model was transformed to a family of crisp DEA models and was solved. Experiments demonstrated the feasibility and applicability of the method. © 2011 Published by Elsevier Ltd. Source

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