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	1. Research on Coanda effect of surface jet by Remold Stress Model
	FU Xiaoli
	Hydraulic Engineering 07 November 2012
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	Abstract:In this paper, Coanda effect is observed to attract the water to free surface. A surface jet attracts water from the surroundings and the phenomenon is called water entrainment, which is found to be resulting from one of the combined effects-Coanda effect. To capture these surface currents several turbulence model are used. In this paper, two isotropic and anisotropic turbulent models (standard k-ε, Realizable k-ε and RSM) are employed with different boundary conditions to compare with the experimental data. The simulated results indicated Realizable k- ε and standard are unable to capture streamwise vorticity and surface current. The RSM with proper boundary condition is proved to have good agreement with experimental data and to predict the Coanda effect best. The results showed that an anisotropic RANS model with the appropriate boundary conditions can give good results for the surface jets, at least for this simple geometry. It also can predict the Coanda effect more properly than the isotropic models.
	TO cite this article:FU Xiaoli. Research on Coanda effect of surface jet by Remold Stress Model[OL].[ 7 November 2012] http://en.paper.edu.cn/en_releasepaper/content/4494487


	2. The Best Configuration Selection of Underwater Modular Self-Reconfigurable Robots
	XU Xuesong
	Hydraulic Engineering 24 April 2012
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	Abstract:Underwater Modular Self-Reconfigurable (UMSR) robots, made up of many identical modules, can change their overall configuration in the underwater environment. Their survival in complex and unpredictable underwater environment necessitates the ability of selecting the best configuration from their configuration library automatically. To fulfill this ability, this paper proposes a hybrid reasoning mechanism, in which the fuzzy logic approach is employed to select the best configuration category, and the competing neuron network approach is used to select the best configuration in the best category.
	TO cite this article:XU Xuesong. The Best Configuration Selection of Underwater Modular Self-Reconfigurable Robots[OL].[24 April 2012] http://en.paper.edu.cn/en_releasepaper/content/4476120


	3. Groundwater level Simulation and forecasting using ANN at Wadi –Nyala watershed, Darfur Sudan
	Mohammed Mokhtar Eisa,Thomas Oromo,Adam Ishag,John Leju,Nahla Mustafa,Nabela Hamed
	Hydraulic Engineering 30 March 2010
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	Abstract:A proper design of the architecture of Artificial Neural Network (ANN) models can provide a robust tool in water resources modeling and forecasting. The performance of neural networks in a groundwater level forecasting is examined in order to identify an optimal ANN architecture that can simulate the decreasing trend of the groundwater level and provide acceptable predictions up to 17 months ahead. Wadi –Nyala watershed in the south Darfur Nyala, Sudan. Was chosen as the study area as its groundwater resources have being overexploited during the last twenty years and the groundwater level has been decreasing steadily. The model efficiency and accuracy were measured based on the root mean square error (RMSE) and regression coefficient ( ). The model provided the best fit and the predicted trend followed the observed data closely (RMSE = 0.445 and = 0.973). Thus, for precise and accurate groundwater level simulation, ANN appears to be a promising tool.
	TO cite this article:Mohammed Mokhtar Eisa,Thomas Oromo,Adam Ishag, et al. Groundwater level Simulation and forecasting using ANN at Wadi –Nyala watershed, Darfur Sudan[OL].[30 March 2010] http://en.paper.edu.cn/en_releasepaper/content/41342


	4. Application of GAs and GIS in Xin’anjiang Model
	Song Xiaomeng,Kong Fanzhe
	Hydraulic Engineering 16 October 2009
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	Abstract:Generally, in Xin’anjiang model, the basin is divided into a set of sub-basins by Thiessen method so that the spatial distribution of rainfall can be taken account, which the same recession constants of runoff concentration are used in all sub-basins. It can be seen that topography is not taken account. However, it is well known that the runoff concentration behaviors of basin largely depended on topographic characteristic. And also it adopts a traditional method to make parameters calibration and optimization which takes on uncertain factor. The paper make use of GIS to carve up sub-basins and genetic algorithm to make parameters calibration and optimization, and the application results in Dapoling River Basin show that the number of flood with the qualified rate of error of peak-time increased to 100% from 90%, and excellent rate increased to 30% from 20%, and that with relative error of peak of less than 5% increased to 50% from 30%.
	TO cite this article:Song Xiaomeng,Kong Fanzhe. Application of GAs and GIS in Xin’anjiang Model[OL].[16 October 2009] http://en.paper.edu.cn/en_releasepaper/content/35876


	5. Surrogate Modeling in Predicting Fine Sediment transportation along the Dutch Coastal Area
	Chu Kai
	Hydraulic Engineering 24 July 2009
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	Abstract:The use of both process-based model and data driven model (DDM) in simulating sediment processes have shown to be useful by previous research. However, both approaches have disadvantages. This paper explored several data driven methods to build simple models in predicting SPM based on output from the process-based models. Artificial neural network (ANN) is adopted as surrogate model to predict suspended particulate matter (SPM) concentration in the Southern North Sea. Surrogate model is essentially a simple and fast ‘model of the model’. The simulation by surrogate models is acceptable and simulation time reduces dramatically. Surrogate models are also built with linear regression method which refers to ‘parsimonious model’. Parsimonious model is the simplest feasible model with the fewest possible number of variables It requires less computation time, the simulation is transparent and results are easy to interpret.
	TO cite this article:Chu Kai. Surrogate Modeling in Predicting Fine Sediment transportation along the Dutch Coastal Area[OL].[24 July 2009] http://en.paper.edu.cn/en_releasepaper/content/34067


	6. Risky dam analysis and stability evaluation of reinforcement
	Dong Liang
	Hydraulic Engineering 17 March 2009
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	Abstract:Shortly after construction of the Shuanghe Arch Dam, substantial perforative cracks emerged, and these cracks would threaten the stabilization of the dam. A three dimensional model was established and the finite element analysis was employed to investigate the formation cause of the cracks. From the stress sensitive analysis in different types of loading case, the results show: The load combination condition of normal water level and temperature drop is most dangerous, and the temperature drop is the main external cause of crack growing. Four policies were applied to reinforce the arch dam: Thickening the dam body between 491.70~525.00m; consolidation grouting in downriver foundation; downriver drainage system; prestressed anchor in downriver slope. The finite element method is used to analyse the displacement, stress and the safety degree of abutment with comparing the reinforced dam to that without reinforcement. The results indicate that the reinforced arch dam is safe and stable.
	TO cite this article:Dong Liang. Risky dam analysis and stability evaluation of reinforcement[OL].[17 March 2009] http://en.paper.edu.cn/en_releasepaper/content/30379

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