Influence of Stratification and Shoreline Erosion on Reservoir Sedimentation Patterns

Sedimentation in the main pool of a deep (maximum depth: 50?m), 227?km2 hydropower reservoir was modeled using a three-dimensional numerical model of hydrodynamics and sedimentation for different wind, inflow, and outflow conditions. Short-term velocity measurements made in the reservoir were used to validate some aspects of the hydrodynamic model. The effects of thermal stratification on sedimentation patterns were investigated, since the reservoir is periodically strongly stratified. Stratification alters velocity profiles and thus affects sedimentation in the reservoir. Sedimentation of reservoirs is often modeled considering only the deposition of sediments delivered by tributaries. However, the sediments eroding from the shorelines can contribute significantly to sedimentation if the shorelines of the reservoir erode at sufficiently high rates or if sediment delivery via tributary inflow is small. Thus, shoreline erosion rates for a reservoir were quantified based on measured fetch, parameterized beach profile shape, and measured wind vectors, and the eroded sediments treated as a source within the sedimentation modeling scheme. The methodology for the prediction of shoreline erosion was calibrated and validated using digital aerial photos of the reservoir taken in different years and indicated approximately 1?m/year of shoreline retreat for several locations. This study revealed likely zones of sediment deposition in a thermally stratified reservoir and presented a methodology for integration of shoreline erosion into sedimentation studies that can be used in any reservoir.     

Multivariable Regulator Approach to Sewer Network Flow Control

The problem of optimal water distribution to a range of retention reservoirs in an urban sewer network during rainfall events is considered in this paper. The goal of the control actions is the minimization of overflows and eventually the reduction of their polluting impact on receiving waters. A multilayer control structure consisting of an adaptation, an optimization, and a direct control layer, is proposed for the solution of this complex control problem. Several approaches have been proposed with regard to the optimization layer. This paper proposes a linear multivariable feedback regulator that is developed via a systematic design procedure, including a simplified model, a quadratic minimization criterion, and subsequent application of the linear-quadratic optimization method. Inflow predictions are accommodated through feedforward terms in the control law. The control design guidelines facilitate a quick and efficient regulator design for a broad class of sewer network control problems. Simulation tests for a particular large network and various inflow scenarios indicate that significant overflow reductions are achieved by the application of the linear-quadratic regulator.     

Impact of Turbidity Currents on Reservoir Sedimentation

All lakes created on natural rivers are subjected to reservoir sedimentation. The construction of a dam significantly modifies the flow conditions of natural streams inside and downstream of an artificial lake. The sediment concentration is often high during the flood season, and the entering flow shows a greater density than the ambient fluid. Suspended load can therefore be carried along the reservoir bottom to the dam in the form of turbidity currents. This paper presents research results that help to better understand this physical phenomenon, which contributes to reservoir sedimentation. It is based on in situ measurements, a laboratory scale model of turbidity currents and numerical flow simulations. The study of a thousand-year flood in the Luzzone Reservoir in the Swiss Alps using the developed computer model revealed the potential of such a tool. In particular, the impact on the sediment deposits was analyzed. A valuable evaluation of the incidence of such a turbidity flow is presented and its effects are compared to observations. Significant progress has been made in understanding the importance of turbidity currents in reservoir sedimentation.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

Observation and Simulation of Floodwater Intrusion and Sedimentation in the Shichikashuku Reservoir

Wash load sedimentation during flood events is studied through comprehensive field measurements at the Shichikashuku Reservoir, Japan and numerical simulation. Field data during a flooding event caused by a typhoon in 1996 are used to set the boundary conditions for the model and to verify the simulation. In the field experiments, continuous monitoring of inflow turbidity is shown to be an effective and reliable means of estimating sediment influx. In the simulations, the proposed model is shown to provide an accurate reproduction of floodwater currents and sedimentation in the reservoir. The model achieves good accuracy and resolution by adopting an orthogonal curvilinear grid to discretize the reservoir and by solving the flow field using a three-dimensional standard k–ε turbulence model. The simulation reproduces the observed velocity, turbidity, and distribution of sedimentation well, demonstrating the potential utility of such models in the management of reservoir water quality and sedimentation.     

Neural Approximation for the Optimal Control of a Hydroplant with Random Inflows and Concave Revenues

We present a method for computing an approximately optimal policy for the control of a hydroelectric reservoir with random inflows and concave, piecewise linear revenues from electricity sales. Our approach uses neurodynamic programming to approximate the future value function by a neural network. Our approximation architecture, based on the feedforward network, gives very smooth approximate functions, allowing the use of a coarse discretization of the state and inflow variables in the training step of the neural functions. Our model takes into account the head variations on the turbine efficiency and assumes the water flows at a steady rate during each period of the planning horizon, while related models in the literature have made less realistic assumptions of constant head or that the natural inflows were unusable until the next period. Moreover, we extend previous results on the concavity of the expected future rewards as a function of the potential energy in the reservoir and on the structure of optimal decision rules.     

Automatic Downstream Water-Level Feedback Control of Branching Canal Networks: Simulation Results

Previous research on canal automation has dealt with the control of single, in-line canals, while canal operators typically have to control an entire network of canals. Because the branches in a network are hydraulically coupled with each other, control of a branching canal network based on separate controllers for each branch may not be the most effective control strategy. A methodology by which existing automatic control systems could be modified to control branching canal networks is provided in a companion paper. This paper presents results of hydraulic simulations of the new methodology to estimate the controllability of a large portion of the branching canal network operated by the Salt River Project (SRP). Two types of controllers were used for this study: (1) linear quadratic regulator (LQR) and (2) model predictive control (MPC). Both controllers used the same underlying process model [integrator-delay (ID) model], and both controllers were capable of feedback and feedforward control. Under feedback control alone, both controllers gave similar performance, but were unable to effectively control the overall system because of the long delay times. When feedforward control was added to the feedback controller, both of these control systems were able to effectively control the branching canal network operated by SRP. For the LQR controller, the volume compensation method for routing known demand change was used as the feedforward controller. For the MPC controller, the ID model was used as the feedforward controller. Slight differences were noted between the performance of the two feedforward controllers.     

Optimal Design of a Stable Trapezoidal Channel Section Using Hybrid Optimization Techniques

A cost effective channel section for a specified flow rate, roughness coefficients, longitudinal slope, and various cost parameters can be determined using an optimization technique. However, the derived optimal channel section may not be feasible for construction because of in situ conditions. The local soil conditions may not support the optimal side slope of the channel and if constructed, the slope may fail. It is therefore necessary to also incorporate the criteria for side slope stability in designing an optimal open channel section. In this paper, a new methodology has been developed to design a stable and optimal channel section using hybrid optimization techniques. A genetic algorithm based optimization model is developed initially to determine the factor of safety of a channel slope for given soil parameters. This optimization model is then externally linked with a separate sequential quadratic programming based optimization model to evaluate the parameters of the stable and optimal channel section. Solution for various example problems incorporating different soil parameters are illustrated to demonstrate the applicability of the developed methodology.     

Case Study: Delayed Sedimentation Response to Inflow and Operations at Sanmenxia Dam

This paper presents a study on the reservoir sedimentation processes in response to changes in incoming flow at the upstream and changes in the pool level at the downstream for Sanmenxia Reservoir, which is located on the middle reach of the Yellow River in China and has experienced serious sedimentation problems even since its impoundment in 1960. The hysteresis effect in reservoir sedimentation was used as the basis for analysis and its behavior was fully investigated throughout this study. The research found that the rise in the elevation of Tongguan, which is located in the backwater region at a distance of 113.5?km upstream of the Sanmenxia Dam, had a time delay of about 2?years compared with the sediment deposition in the reservoir area downstream of Tongguan. Moreover the accumulated sediment deposition in the reservoir area was closely related not only to the current year’s flow and dam operational conditions, but also to the preceding 3–4?years’ flow and dam operational conditions. Likewise the variation of Tongguan’s elevation was a function of 6?years’ linearly superimposed runoff, and the channel bed slope in the vicinity of Tongguan was determined by a moving average pool level over a 7?year period. The research results are of practical importance in particular for optimizing the operation of Sanmenxia Dam, and the finding of the hysteresis phenomenon in the sedimentation process of the reservoir is of merit to the advancement of sedimentation science.     

钢铁生产过程富余煤气动态优化分配模型

基于混合整数线性规划,以操作成本最小为目标函数建立了富余煤气优化分配模型.与前人的优化模型相比,本文模型选取了较短的时间步长,并考虑了锅炉权重因子及煤气柜权重因子对优化结果的影响.根据国内某钢铁企业生产数据进行计算,发现优化结果对煤气柜权重因子和锅炉权重因子敏感,因此合理确定煤气柜权重因子和锅炉权重因子十分重要.优化模拟计算与现场经验调度的结果相比,降低了煤气柜储气量波动,提高了锅炉45.9%的发电量,煤气系统运行稳定性增强.      

Automatic Downstream Water-Level Feedback Control of Branching Canal Networks: Theory

Most of the research on the design of feedback controllers for irrigation canals has been concentrated on single, in-line canals with no branches. Because the branches in a network are hydraulically coupled with each other, it may be difficult to automatically control a branching canal network by designing separate feedback controllers for each branch and then letting them run simultaneously. Thus feedback control of an entire branching canal system may be more efficient if the branching flow dynamics are explicitly taken into account during the feedback controller design process. This paper develops two different feedback controllers for branching canal networks. The first feedback controller was developed using linear quadratic regulator theory and the second using model predictive control. Both algorithms were able to effectively control a simple branching canal network example with relatively small flow changes.     

Investigation of a System Identification Methodology in the Context of the ASCE Benchmark Problem

This article briefly presents the theory for a system identification and damage detection algorithm for linear systems, and discusses the effectiveness of such a methodology in the context of a benchmark problem that was proposed by the ASCE Task Group in Health Monitoring. The proposed approach has two well-defined phases: (1) identification of a state space model using the Observer/Kalman filter identification algorithm, the eigensystem realization algorithm, and a nonlinear optimization approach based on sequential quadratic programming techniques, and (2) identification of the second-order dynamic model parameters from the realized state space model. Structural changes (damage) are characterized by investigating the changes in the second-order parameters of the “reference” and “damaged” models. An extensive numerical analysis, along with the underlying theory, is presented in order to assess the advantages and disadvantages of the proposed identification methodology.     

智能集成优化控制技术及其在工业中的应用

研究和讨论了复杂工业过程的优化控制技术 ,提出了智能集成优化控制的理论框架。以冶金工业生产中三个典型的复杂生产过程为应用背景 ,分别将模糊神经网络集成建模、基于改进模拟退火算法的混合罚函数目标优化技术、基于混沌神经网络的优化技术及基于模型的专家优化控制技术应用于工业生产过程控制 ,为企业带来了巨大的经济效益和社会效益。     

Investigations of exemplar and decision bound models in large, ill-defined category structures.

Experiments involving large-size, ill-defined categories were conducted to distinguish between the predictions of an exemplar model and linear and quadratic decision bound models. In conditions in which the optimal classification boundary was of a more complex form than the quadratic model, the exemplar model provided significantly better accounts of study participants' data than did the decision bound models, even in situations in which a linear bound would have yielded nearly optimal performance. The results suggest that participants are not predisposed or constrained to use linear or quadratic decision bounds for classifying multidimensional perceptual stimuli and that exemplar models may provide a parsimonious process-level account of the complex types of decision bounds used by experiment participants. The results also suggest some limitations on the complexity of the decision bounds that can be learned, in contrast to the predictions of the exemplar model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Life of Maithon Reservoir on Ground of Sedimentation: Case Study in India

This case study discusses the life of the Maithon Reservoir studied based upon the past reservoir sedimentation trends and downstream demands for which the reservoir was built, where increased or projected demands were not considered during the study. Various studies have been done to observe declining storage in different zones of the reservoir, including reliability of the conservation storage, rise of reservoir bed level, reduction of reservoir trap efficiency, etc., at different projected years. An attempt has also been made to discuss the full life of the reservoir and to provide a short discussion of different strategies for its prolonged life because sediment is filling the reservoir much faster than its designed life. An additional life of 58?years for the Maithon Reservoir may be obtained if the Balpahari Reservoir is constructed as a siltation trap at just the upstream of the Maithon Reservoir within the year 2005. Actually, this case study provides a guideline for dealing with a practical sedimentation problem along with the serviceability of a reservoir based upon Murthy’s recommendations.     

μ Control for Satellites Formation Flying

In this paper, a μ controller is designed for a satellite formation flying system around the Earth based on an uncertainty model derived from a nonlinear relative position equation. In this model, nonzero eccentricity and varying semimajor axis are included as parametric uncertainties. J2 perturbation, atmospheric drag, and actuation and sensor noise are bounded by functional uncertainties. The μ controller design based on the nominal mission (an 800?km altitude circular reference orbit) is capable of achieving desired performance, is robust to uncertainties, and satisfies fuel consumption requirements even in a challenge nonnominal mission (a 0.1 eccentricity and 7,978?km semimajor axis elliptic reference orbit) with the same control gain. In this nonnominal mission, the designed μ controller is able to keep formation with almost the same level of the ΔV budget (43.86?m/s/year) as used in the nominal mission (39.65?m/s/year). For comparison, linear quadratic regulator (LQR) and sliding mode controllers (SMC) are developed and extensively tuned to get the same ΔV consumption as that of the designed μ controller for the nominal mission. However, as shown in the simulation, the designed linear robust controller (LQR) and nonlinear robust controller (SMC) have a serious ΔV consumption penalty (1.72?km/s/year for SMC) or are unstable (for LQR) in the nonnominal mission.     

Simultaneous Zonation and Calibration of Pipe Network Parameters

A procedure for simultaneously zoning and calibrating pipe network parameters is proposed and applied to the determination of pipe resistance coefficients. The methodology is aimed at grouping the parameters of all the pipes into a small number of zone parameters, constrained to keep the difference between the computed and the measured water heads below a given tolerance. It is shown that, in the case of nonlooped networks, the methodology leads to a linear minimization problem where the objective function is a measure of the heterogeneity of the estimated parameters. In the case of looped networks an iterative procedure, where the linear problem is coupled with a nonlinear problem having a restricted number of decision variables, is proposed and demonstrated. Application of the procedure to a hypothetical example is shown. In a lab experiment, the model of a pipe network made by two different types of links has been calibrated using two measurement points and three different measured data sets, each of which was obtained by adjusting the valves located in the network to modify the pressure field. Comparison of the measured and the estimated resistance coefficients shows good correlation.     

Robust Stationkeeping Control for Libration Point Quasi-Periodic Orbits

Libration orbit stationkeeping controls are designed based on selected reference quasi-periodic orbit trajectories. The baseline trajectory is designed to meet science requirements and in the same time achieve minimum fuel consumptions. The success of finding libration point reference orbits is based on accurate numerical computation, dynamics, and space environment modeling. The linear quadratic regulator controller has been developed widely for maintaining a spacecraft in such libration orbit reference trajectories as close as possible. However, any dynamics models, including the circular restricted three-body dynamics, space environment, sensor, and actuator, are only approximations of real physical systems. Any noise and uncertainties can cause spacecraft’ motion to diverge due to the high instability region around libration points. This study investigates the modeling and designing of a passive robust μ controller and an active adaptive linear quadratic regulator in libration point stationkeeping controls around L1. The adaptive law in the linear quadratic regulator is used to estimate unknown gains of spacecraft’ subsystems. The results are compared for a family of libration orbits with reasonable ΔV yearly budgets under the influence of perturbations, noise, and unmodeled dynamics. The comparison with a publicly accessible work indicates that the controller developed in this work can provide comparable annual cost by nearly even including the worst case of perturbations.     

Optimization of Water Distribution Networks Using Integer Linear Programming

In this study optimum design of municipal water distribution networks for a single loading condition is determined by the branch and bound integer linear programming technique. The hydraulic and optimization analyses are linked through an iterative procedure. This procedure enables us to design a water distribution system that satisfies all required constraints with a minimum total cost. The constraints include pipe sizes, which are limited to the commercially available sizes, reservoir levels, pipe flow velocities, and nodal pressures. Accuracy of the developed model has been assessed using a network with limited solution alternatives, the optimal solution of which can be determined without employing optimization techniques. The proposed model has also been applied to a network solved by others. Comparison of the results indicates that the accuracy and convergence of the proposed method is quite satisfactory.     

DORA Algorithm for Network Flow Models with Improved Stability and Convergence Properties

A new methodology for the solution of shallow water equations is applied for the computation of the unsteady-state flow in an urban drainage network. The inertial terms are neglected in the momentum equations and the solution is decoupled into one kinematic and one diffusive component. After a short presentation of the DORA (Double ORder Approximation) methodology in the case of a single open channel, the new methodology is applied to the case of a sewer network. The transition from partial to full section and vice versa is treated without the help of the Preissmann approximation. The algorithm also allows the computation of the diffusive component in the case of vertical topographic discontinuities, without the introduction of any internal boundary conditions and without any change in the structure of the linear system matrix. The algorithm is tested on one field example, and its performance is compared with the performance of other popular commercial codes.