Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks

Leaks are present to some extent in all water-distribution systems. This paper proposes a leakage localisation method based on the pressure measurements and pressure sensitivity analysis of nodes in a network. The sensitivity analysis using analytical tools is not a trivial job in a real network because of the huge non-explicit non-linear systems of equations that describe its dynamics. Simulations of the network in the presence and the absence of leakage may provide an approximation of this sensitivity. This matrix is binarised using a threshold independent of the node. The binary matrix is assumed as a signature matrix for leakages. However, there is a trade-off between the resolution of the leakage isolation procedure and the number of available pressure sensors. In order to maximise the isolability with a reasonable number of sensors, an optimal sensor placement methodology, based on genetic algorithms, is also proposed. These methodologies have been applied to the Barcelona Network using PICCOLO simulator. The sensor placement and the leakage detection and localisation methodologies are applied to several district management areas (DMA) in simulation and in reality.     

Learning-based tuning of supervisory model predictive control for drinking water networks

This paper presents a constrained Model Predictive Control (MPC) strategy enriched with soft-control techniques as neural networks and fuzzy logic, to incorporate self-tuning capabilities and reliability aspects for the management of drinking water networks (DWNs). The control system architecture consists in a multilayer controller with three hierarchical layers: learning and planning layer, supervision and adaptation layer, and feedback control layer. Results of applying the proposed approach to the Barcelona DWN show that the quasi-explicit nature of the proposed adaptive predictive controller leads to improve the computational time, especially when the complexity of the problem structure can vary while tuning the receding horizons.     

Determination of optimal actuator forces and positions in smart structures using adjoint method

The problem of optimal design of structures with active support is analyzed in the paper. The sensitivity expressions with respect to the generalized force and the position of actuator are derived by the adjoint structure approach. Next, the optimality conditions are formulated by means of an introduced Lagrangian function. The problem of introduction of a new actuator is also considered and the condition of modification is expressed by means of the topological derivative. The obtained sensitivity formula, optimality conditions and modification conditions are applied in the optimization algorithm with respect to the number, positions and generalized forces of the actuators. Numerical examples of optimal control of beams illustrate the procedure proposed in the paper.     

Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling

The application of Artificial Neural Networks (ANNs) in the field of environmental and water resources modelling has become increasingly popular since early 1990s. Despite the recognition of the need for a consistent approach to the development of ANN models and the importance of providing adequate details of the model development process, there is no systematic protocol for the development and documentation of ANN models. In order to address this shortcoming, such a protocol is introduced in this paper. In addition, the protocol is used to critically review the quality of the ANN model development and reporting processes employed in 81 journal papers since 2000 in which ANNs have been used for drinking water quality modelling. The results show that model architecture selection is the best implemented step, while greater focus should be given to input selection considering input independence and model validation considering replicative and structural validity.     

A new approach for instantaneous pole placement with recurrent neural networks and its application in control of nonlinear time-varying systems

In this paper, we first show that online computation of feedback gain used for pole placement of nonlinear systems in recent years is not reliable, and then we present a new approach for instantaneous pole placement and apply it with dynamical recurrent neural networks for online computation of feedback gain. Because of high-speed convergence of neural network to feedback gain, we can apply this method for pole placement of nonlinear time-varying systems. One strategy for realization of this method is instantaneous linearization, as we do here by simulation. The advantage of the proposed method is a global uniform asymptotical exponential stability (GUAES) of closed-loop system around the equilibrium point.     

Application of a fractional step method for the numerical solution of the shallow water waves in a rotating rectangular basin

A numerical method is applied to the problem of an incompressible fluid in a slowly rotating rectangular basin for the simulation of wave propagation in shallow water. The present work is a complete study of the wave motion through evaluation of the wave height and the velocity components. The results are found by the application of a fractional step method and illustrated graphically. The technique is applied by splitting the shallow water equations and successive integration in every direction along the characteristics using the Riemann invariants associated with cubic spline interpolation. It has the advantage of reducing the multidimensional matrix inversion problem into an equivalent one-dimensional problem. Numerical results are represented in three dimensions for the velocity components at different times. The distribution of temperature and concentration are also calculated and plotted.     

Improvement of numerical instabilities in topology optimization using the SLP method

In this paper, we present a method for preventing numerical instabilities such as checkerboards, mesh-dependencies and local minima occurring in the topology optimization which is formulated by the homogenization design method and in which the SLP method is used as optimizer. In the present method, a function based on the concept of gravity (which we named “the gravity control function”) is added to the objective function. The density distribution of the topology is concentrated by maximizing this function, and as a result, checkerboards and intermediate densities are eliminated. Some techniques are introduced in the optimization procedure for preventing the local minima. The validity of the present method is demonstrated by numerical examples of both the short cantilever beam and the MBB beam. Received February 23, 1999     

循环冷却水系统成垢过程软件预测

循环冷却水系统中无机垢的形成预测是一个相当复杂的研究课题,涉及到包括热力学、动力学、流体力学、晶体生长和表面化学等方面的知识。到目前为止,人们已经提出许多理论来试图解决此难题。但不足在于这些理论对成垢过程影响因素的讨论很不全面。本文几乎考虑了冷却水中常见的所有成垢阳、阴离子和非成垢离子,详细讨论了水溶液中所存在的各种平衡,并考察了温度、pH值、离子强度等因素对成垢过程的影响。所建立的模型通过实验数据进行了验证。结果显示,模型的计算结果与实验数据大体一致。利用Visual Basic6．0语言开发循环冷却水系统成垢预测专家系统软件。该软件可在windows 9X操作平台下独立运行,具有界面友好、操作方便、运行可靠稳定等优点。     

On numerical stabilization in the solution of Saint-Venant equations using the finite element method

Solving the Saint-Venant equations by using numerical schemes like finite difference and finite element methods leads to some unwanted oscillations in the water surface elevation. The reason for these oscillations lies in the method used for the approximation of the nonlinear terms. One of the ways of smoothing these oscillations is by adding artificial viscosity into the scheme. In this paper, by using a suitable discretization, we first solve the one-dimensional Saint-Venant equations by a finite element method and eliminate the unwanted oscillations without using an artificial viscosity. Second, our main discussion is concentrated on numerical stabilization of the solution in detail. In fact, we first convert the systems resulting from the discretization to systems relating to just water surface elevation. Then, by using M-matrix properties, the stability of the solution is shown. Finally, two numerical examples of critical and subcritical flows are given to support our results.     

A lumped Galerkin method for the numerical solution of the modified equal-width wave equation using quadratic B-splines

The numerical solution of the one-dimensional modified equal width wave (MEW) equation is obtained by using a lumped Galerkin method based on quadratic B-spline finite elements. The motion of a single solitary wave and the interaction of two solitary waves are studied. The numerical results obtained show that the present method is a remarkably successful numerical technique for solving the MEW equation. A linear stability analysis of the scheme is also investigated.     

Application of an expert system using neural network to control the coagulant dosing in water treatment plant

The coagulation process is one of the most important stages in water treatment plant, which involves many complex physical and chemical phenomena. Moreover, coagulant dosing rate is non-linearly correlated to raw water characteristics such as turbidity, conductivity, PH, temperature, etc. As such, coagulation reaction is hard or even impossible to control satisfactorily by conventional methods. Based on neural network and rule models, an expert system for determining the optimum chemical dosage rate is developed and used in a water treatment work, and the results of actual runs show that in the condition of satisfying the demand of drinking water quality, the usage of coagulant is lowered.     

直流电阻率法在煤层底板水害监测中的应用研究

目前针对直流电阻率法在煤层底板水害监测中应用的研究成果主要集中于底板变形与破坏的电阻率响应特征上,对导水通道动态发育过程的电阻率变化规律研究较少。针对华北型煤田面临的底板承压水害问题,采用直流电阻率法对采动影响下的底板含、导水异常构造进行监测。首先,介绍了采煤工作面直流电阻率监测系统工作原理和基于电阻率三维反演的监测数据自动处理解释方法;然后,构建了底板突水过程监测地质模型,对底板含、导水构造发育过程进行数值模拟研究;最后,在煤矿井下开展了底板直流电阻率监测试验。数值模拟结果表明:根据电阻率三维反演结果可识别含、导水异常构造在测线走向上的展布范围;根据电阻率随时间的变化趋势可推断异常构造的发育情况,随着含、导水异常构造向上发育,低阻异常响应逐渐增强,低阻异常在垂向的展布范围逐渐增大。井下试验结果表明:利用直流电阻率监测成功捕捉了采煤工作面底板出水过程,电阻率出现异常变化的时间早于工作面实际出水时间;工作面涌水量增加之前,低阻响应表现出逐渐增强的变化趋势,与数值模拟结果基本一致;工作面出水后,低阻异常逐渐减弱。研究结果表明可利用直流电阻率法进行工作面水害预警,但要准确判断异常构造的发育高度还需结合其他监测手段进行综合解释。     

PLC控制在内冷水水质监测系统中的应用

直流输电中内冷水循环系统的水质问题涉及到换流站的安全稳定、运行,是电力系统必须定期监测的项目。本文介绍了应用PLC控制一套换流站内冷水在线监测系统,利用OPC服务实现西门子S7-200型号的PLC与上位机之间的通讯,实时在线对内冷水水质状况进行监测,对水质变异提前进行预警。     

全遥控式原油水的质量分数监测仪

我国石油化工行业原油各生产加工环节的水的质量分数计量主要是靠原始的蒸馏化验方法来完成。介绍了一种先进的全遥控式原油水的质量分数监测仪,说明了其主要工作原理,提出了关键问题的解决办法,给出了全遥控式测量仪器的应用实例。     

Efficacy of utilizing a hybrid algorithmic method in enhancing the functionality of multi-instance multi-label radial basis function neural networks

The facts show that multi-instance multi-label (MIML) learning plays a pivotal role in Artificial Intelligence studies. Evidently, the MIML learning introduces a framework in which data is described by a bag of instances associated with a set of labels. In this framework, the modeling of the connection is the challenging problem for MIML. The RBF neural network can explain the complex relations between the instances and labels in the MIMLRBF. The parameters estimation of the RBF network is a difficult task. In this paper, the computational convergence and the modeling accuracy of the RBF network has been improved. The present study aimed to investigate the impact of a novel hybrid algorithm consisting of Gases Brownian Motion optimization (GBMO) algorithm and the gradient based fast converging parameter estimation method on multi-instance multi-label learning. In the current study, a hybrid algorithm was developed to estimate the RBF neural network parameters (the weights, widths and centers of the hidden units) simultaneously. The algorithm uses the robustness of the GBMO to search the parameter space and the efficiency of the gradient. For this purpose, two real-world MIML tasks and a Corel dataset were utilized within a two-step experimental design. In the first step, the GBMO algorithm was used to determine the widths and centers of the network nodes. In the second step, for each molecule with fixed inputs and number of hidden nodes, the parameters were optimized by a structured nonlinear parameter optimization method (SNPOM). The findings demonstrated the superior performance of the hybrid algorithmic method. Additionally, the results for training and testing the dataset revealed that the hybrid method enhances RBF network learning more efficiently in comparison with other conventional RBF approaches. The results obtain better modeling accuracy than some other algorithms.     

The numerical study on the unsteady flow of gas in a semi-infinite porous medium using an RBF collocation method

In this paper, we study a nonlinear two-point boundary value problem on semi-infinite interval that describes the unsteady gas equation. The solution of the mentioned ordinary differential equation (ODE) is investigated by means of the radial basis function (RBF) collocation method. The RBF reduces the solution of the above-mentioned problem to the solution of a system of algebraic equations and finds its numerical solution. To examine the accuracy and stability of the approach, we transform the mentioned problem into another nonlinear ODE which simplifies the original problem. The comparisons are made between the results of the present work and the numerical method by shooting method combined with the Runge–Kutta technique. It is found that our results agree well with those by the numerical method, which verifies the validity of the present work.     

Operational algorithm for the retrieval of water quality in the Great Lakes

A new operational non-satellite-specific algorithm for the simultaneous retrieval from satellite data of phytoplankton chlorophyll content (chl), suspended minerals (sm), and dissolved organics (doc) in both clear and turbid waters is presented. It contains an array of neural networks providing input for the Levenberg-Marquardt multivariate optimization procedure as the final retrieval tool. With a given accuracy threshold, the developed algorithm is sufficiently robust for data with noise up to 15% for certain hydro-optical conditions. To avoid inadequate retrieval results, the algorithm identifies and eventually discards the pixels with inadequate atmospheric correction and/or water optical properties incompatible with the applied hydro-optical model. The validity of the developed algorithm was tested for Lake Michigan. Two dedicated field campaigns in the vicinity of the Kalamazoo River mouth have been conducted concurrently or quasi-concurrently with SeaWiFS and MODIS overpasses. In addition, some archival shipborne measurements of mostly chl and occasionally sm and doc were employed to validate the facility of the algorithm. Notwithstanding the aforementioned shipborne data limitations, the conducted comparison of the ground truth and retrieved data on the water quality parameters in Lake Michigan is strongly indicative of the algorithm's operational efficiency.     

The sample solution approach for determination of the optimal shape parameter in the Multiquadric function of the Kansa method

The Kansa method with the Multiquadric-radial basis function (MQ-RBF) is inherently meshfree and can achieve an exponential convergence rate if the optimal shape parameter is available. However, it is not an easy task to obtain the optimal shape parameter for complex problems whose analytical solution is often a priori unknown. This has long been a bottleneck for the MQ-Kansa method application to practical problems. In this paper, we present a novel sample solution approach (SSA) for achieving a reasonably good shape parameter of the MQ-RBF in the Kansa method for the solution of problems whose analytical solution is unknown. The basic assumption behind the SSA is that the optimal shape parameter is considered to be largely depended on the shape of computational domain, the type of the boundary conditions, the number and distribution of nodes, and the governing equation. In the procedure of the SSA, we set up a pseudo-problem as the sample solution whose solution is known. It is not difficult to obtain the optimal parameter of the MQ-RBF in the numerical solution of the pseudo-problem. The SSA suggests that the optimal shape parameter of the pseudo-problem can also achieve an approximately optimal accuracy in the solution of the original problem. Numerical examples and comparisons are provided to verify the proposed SSA in terms of accuracy and stability in solving homogeneous problems and non-homogeneous modified Helmholtz problems in several complex domains even using chaotic distribution of collocation points.     

A numerical comparison of partial solutions in the decomposition method for linear and nonlinear partial differential equations

In this study, the decomposition method for solving the linear heat equation and nonlinear Burgers equation is implemented with appropriate initial conditions. The application of the method demonstrated that the partial solution in the x-direction requires more computational work when compared with the partial solution developed in the t-direction but the numerical solution in the x-direction are performed extremely well in terms of accuracy and efficiency.     

An efficient numerical method for simulating the dynamics of coupling Bose–Einstein condensates in optical resonators

In this paper, we present an efficient numerical method for computing the dynamics of coupling Bose–Einstein condensates in optical resonators at extremely low temperature, which is modeled by Gross–Pitaevskii equations (GPEs) coupled with an integral and ordinary differential equation (IODE). Our numerical method is based on an integration factor method for solving the IODE and a time-splitting sine pseudospectral method for solving the GPEs. Our numerical method keeps well the dynamical properties of the mathematical model and have spectral accuracy in space. Through extensive numerical simulations, we analyze which factors may be useful for uniting Bose–Einstein condensates in optical resonators and study the possible way of dynamically uniting two Bose–Einstein condensates in optical resonators.