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This paper focus on optimization operation problem of ecology and power generation considering uncertainty of inflow on the Three Gorges reservoir. A model with constraint violation as objective is proposed to obtain ecological and power generation optimization dispatch rule of the Three Gorges Reservoir using stochastic dynamic programming. In the model, minimization of ecological water shortage and constraint violation and maximization of power generation benefit are taken as objective, simple discrete-time Markov chain and stochastic dynamic programming take into account the uncertainties of inflow. A case study shows that the proposed approach is feasible and efficient to produce a dispatch rule to balance ecological and economic benefits. Some conclusions of the influence of ecology and power generation are finally drawn.

With the reservoir construction gradually completed, joint operation of reservoir groups is an important measure to realize reservoir flood control potential,but when the river basin is large, the flood channel routing and time-lag cannot be simplified, in addition, the curse of dimensionality is very difficult for model solving With the expansion of the number of reservoirs. These factors restrict the application of joint operation of large scale mixed reservoirs.In this study, The DP-POA cyclic iterative algorithm which is based on large scale system decomposed-coordinating method was proposed to solve the optimal problem considering the flood routing and time-lag.The upper Yangtze River is selected as a case study. 6 reservoirs, including the Three Gorges Reservoir(TGR)、Xiangjiaba Reservoir(XJB)、Xiluodu Reservoir (XLD)、 Pubugou Reservoir (PBG)、Goupitan Reservoir (GPT) and Tingzikou Reservoir (TZK)are taken into accounts.Compared with current operation of reservoirs independent,results demonstrate that the method can effectively reduce the maximum operating water level of TGR and flood diversion in the lower reaches of the TGR. Therefore, the safety of the flood control points along the river has been largely improved based on the proposed method.

To realize a fast and high-precision simulation of unsteady flows and water quality process in river networks, a 1-D mathematical modelling system for free-surface flows and water quality process is developed. In the hydrodynamic model, a θ semi-implicit method is used to discretize the free-surface gradient term in the momentum equation while the Eulerian-Lagrangian method is employed to solve the advection term. To achieve good mass conservation, the finite-volume method is used to discretize continuity equation. Moreover, the resulting hydrodynamic model is unconditionally stable with respect to the gravity wave speed and flow advection. In solving the scalar transport equation, the forward difference is used for discretization in time while the centre-difference is in space. A sub-cycling is introduced to divide the computational time step and improve the stability of water quality model. Therefore, large time steps are allowed in both the hydrodynamic and the transport models. The coupling of the branches of the river networks is solved using a predictioncorrection method. Then, a Gaussian pulse test and a rectangular wave test are employed to demonstrate the accuracy and the efficiency of the system, which will also provide powerful supports for ecological operations of cascade reservoirs in drainage basins.

This paper presents a theoretical study on the design of an X-ray fluorescence (XRF) analyzer. The relative geometric positions of the analyzer’s source, detector and specimen are emphasized, which impacts the analyte’s characteristic X-ray fluorescence counts. The theoretical formula for the X-ray fluorescence intensity was derived. The geometric factors (angle and distance) were simulated using Monte Carlo Neutron-Particle Transport Code MCNP5. The Cu’s X-ray characteristic peak counts were calculated. These Monte Carlo model calculations analyzed two types of geometry changes. The best geometric positions for the XRF analyzer had the incident angle for the excitation source (β) equivalent to the exit angle for the specimen’s characteristic X-ray (β). The maximal characteristic X-ray peak counts were obtained when α and β were orthogonal, and the minimum counts were obtained when parallel. To increase the fluorescence counts, the source and detector should be set as close to the specimen as possible. This method and these conclusions can provide technical guidance for designing XRF analyzers.