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.     

Algorithm for Automatic Detection of Topological Changes in Water Distribution Networks

Topological and pressure-driven analyses are an integral part of reliability/risk considerations for a water distribution system. For example, it is often necessary to identify which parts of the distribution network are isolated from water sources after the valves have been closed in response to a mechanical pipe failure. Pressure-driven analysis is then necessary to ascertain the consequences of pipe failures in terms of the performance of the functioning subsystem while pipe breaks are being fixed in the isolated area. Therefore, it is extremely useful to have an algorithm for the automatic identification of nodes/pipes disconnected from the water source(s). However, this is a complex problem because valves sometimes significantly modify the network topology. Furthermore, the use of isolation valves can cause a demand shortage to some customers (due to pressure reduction) during the abnormal operating conditions in the system. Thus, pressure-driven simulation of the network behavior is required. For these reasons, a novel algorithm capable of automatic detection of topological network changes is coupled with a robust pressure-driven simulation model. This algorithm is tested on two case studies involving a small artificial water distribution system and a larger, real-life network. The results obtained clearly demonstrate the robustness of the algorithm developed.     

Modeling the Behavior of Flow Regulating Devices in Water Distribution Systems Using Constrained Nonlinear Programming

Currently the modeling of check valves and flow control valves in water distribution systems is based on heuristics intermixed with solving the set of nonlinear equations governing flow in the network. At the beginning of a simulation, the operating status of these valves is not known and must be assumed. The system is then solved. The status of the check valves and flow control valves are then changed to try to determine their correct operating status, at times leading to incorrect solutions even for simple systems. This paper proposes an entirely different approach. Content and co-content theory is used to define conditions that guarantee the existence and uniqueness of the solution. The work here focuses solely on flow control devices with a defined head discharge versus head loss relationship. A new modeling approach for water distribution systems based on subdifferential analysis that deals with the nondifferentiable flow versus head relationships is proposed in this paper. The water distribution equations are solved as a constrained nonlinear programming problem based on the content model where the Lagrangian multipliers have important physical meanings. This new method gives correct solutions by dealing appropriately with inequality and equality constraints imposed by the presence of the flow regulating devices (check valves, flow control valves, and temporarily closed isolating valves). An example network is used to illustrate the concepts.     

Well Loss Estimation: Variable Pumping Replacing Step Drawdown Test

An optimization method is presented for simultaneous estimation of aquifer parameters and well loss parameters utilizing all the drawdowns observed during a variable rate pumping or multiple step pumping test. The proposed method does not require any graphical analysis. It is shown that a variable rate pumping test is a better substitute for the conventional step drawdown test to estimate well loss parameters. It suggests that the pumping rate may be changed frequently without waiting for a near steady state to be reached (or a selected duration, say 60 min) in each step of a conventional step drawdown test. This can result in a substantial saving of time and money involved in conducting a step drawdown test with a view to estimate well loss parameters. This gives a greater number of distinct discharges, which improves the estimates of the well loss parameters. Application of the method is demonstrated on published data sets, the results of which show that the parameters estimated using the new method are more reliable as compared to those obtained using prior methods.     

Water Distribution Network Design Using Heuristics-Based Algorithm

Water distribution network that includes supply reservoirs, overhead tanks, consumer demand nodes, interconnecting pipes, lifting pumps, and control valves is the main mode of water supply for majority of the communities especially in urban areas. Supply of required quantity of water and at right time is the primary objective of water distribution network analysis. The analysis of water distribution networks can be broadly classified into design and operation problems and both problems have been the focus of many researchers over the past three decades. In the water distribution network design problems, the target is attaining the cost effective configuration that satisfies the minimum hydraulic head requirement at the demand nodes. In this paper, a new algorithm for design of water distribution network namely “heuristics-based algorithm” which completely utilizes the implicit information associated with the water distribution network to be designed has been proposed and validated with two water distribution networks. It is found that the proposed algorithm performs well for the least-cost design of water distribution networks.     

Considering Actual Pipe Connections in Water Distribution Network Analysis

The classical assumption of representing total demand along a pipe as two lumped withdrawals at its terminal nodes is hitherto common. It is a simplification of the network topology which is useful in order to drastically reduce the number of nodes during network simulation. Conversely, this simplification does not preserve energy balance equation of pipes and, for this reason, it is an approximation that could generate significant head loss errors. This paper presents a modification of the global gradient algorithm (GGA) which entails an enhancing of GGA (EGGA) permitting the effective introduction of the lumped nodal demands, without forfeiting correctness of energy balance, by means of a pipe hydraulic resistance correction. The robustness and convergence properties of the algorithm are compared with those of the classical GGA. Furthermore, the effectiveness of EGGA is demonstrated by computing the network pressure status under different configurations of the connections along the pipes of a test network.     

Electrical properties of frog skeletal muscle fibers interpreted with a mesh model of the tubular system

This paper presents the construction, derivation, and test of a mesh model for the electrical properties of the transverse tubular system (T-system) in skeletal muscle. We model the irregular system of tubules as a random network of miniature transmission lines, using differential equations to describe the potential between the nodes and difference equations to describe the potential at the nodes. The solution to the equations can be accurately represented in several approximate forms with simple physical and graphical interpretations. All the parameters of the solution are specified by impedance and morphometric measurements. The effect of wide circumferential spacing between T-system openings is analyzed and the resulting restricted mesh model is shown to be approximated by a mesh with an access resistance. The continuous limit of the mesh model is shown to have the same form as the disk model of the T-system, but with a different expression for the tortuosity factor. The physical meaning of the tortuosity factor is examined, and a short derivation of the disk model is presented that gives results identical to the continuous limit of the mesh model. Both the mesh and restricted mesh models are compared with experimental data on the impedance of muscle fibers of the frog sartorius. The derived value for the resistivity of the lumen of the tubules is not too different from that of the bathing solution, the difference probably arising from the sensitivity of this value to errors in the morphometric measurements.     

Prediction of the measured temperature after the last finishing stand using artificial neural networks

In this report the development of an artificial neural network, capable of predicting the temperature after the last finishing stand of a hot strip mill for a certain class of steels, is described. Three neural networks with different numbers of hidden nodes (3, 5 and 7) were trained. The relative standard deviation in finish temperature as predicted by the best performing neural network model (7 hidden nodes) was just over 25% smaller than that of the linear Hoogovens model. This improved accuracy can be explained by the incorrect assumption in the Hoogovens model of linear dependence of the finishing temperature on some input parameters. With the trained neural network, the influence of the various input parameters on the finishing temperature could be examined. The dependencies predicted by the neural network can be approximated by a linear fit and are a factor 2 lower for all input parameters. It is conceivable that operation of the mill using an artificial neural network for the prediction of the finishing temperature would have resulted in smaller operational fluctuations.     

Pharmacokinetic-pharmacodynamic model for educational simulations

Pharmacokinetic-pharmacodynamic (PK-PD) models play an important role in educational simulations. The parameters of PK-PD models described in the scientific literature are obtained from studies in which the drug concentrations and the drug-effect data are measured simultaneously. Simultaneous PK-PD studies cannot be expected to incorporate all possible combinations of drugs and patient physiology that are desired for educational simulations. To solve this problem, we elaborate on the traditional simultaneous PK-PD model, creating a new model that accepts parameter data from different, more readily available, nonsimultaneous pharmacologic studies. These data are incorporated in the model using a novel estimation procedure for the parameters kc0 and EC50. A sensitivity analysis of the parameter estimation procedure confirms that the time of peak effect following a bolus and the dose-response curve are accurately reflected by the new model. It also demonstrates how inconsistencies among the different parameter sets affect simulation of the recovery phase. The model is extended to incorporate any monotonic parametric or nonparametric dose-response curve. For the neuromuscular relaxant vecuronium, we demonstrate that data from different pharmacologic studies are available, and that the described estimation procedure leads to parameter estimates that are within the standard deviations of the parameters determined in a simultaneous PK-PD study.     

Calibration Assessment and Data Collection for Water Distribution Networks

Calibration of a water distribution network is intended to develop a model that mimics field conditions under a range of demand distributions. In this paper, a three-step calibration procedure is developed that considers the uncertainties in measurement and estimation and provides a measure of the quality of the calibration. The approach can also be used to identify preferable conditions for data collection. The procedure's steps are parameter estimation, calibration assessment, and data collection design. Parameter estimation considers input uncertainty and the resulting uncertainty in model parameters. Calibration assessment analyzes the propagation of the parameter errors on model predictions. The trace of the covariance matrix of the predictive heads is used to measure the model uncertainty. Based on this uncertainty and using a sensitivity-based heuristic analysis, data collection experiments can be designed for systemwide tests and critical pipe for individual pipe tests. An example system is analyzed to select calibration demand conditions.     

热轧带材多缺陷和单缺陷表面质量综合预报

针对目前热轧带材表面质量缺陷类型多、产生机理不同,不能实现在线诊断的问题,提出融合各降维层深度置信网络模型的热轧带材多缺陷和单一缺陷表面质量问题综合预报技术.考虑传统深度置信网络在模型层数和节点数方面的不足,提出并建立了融合各降维层的深度置信网络模型,降低由于网络算法节点个数及层数不确定性造成的预报误差,并利用相关性将...     

特钢返回钢优化利用及可利用资源的开发

特钢制造过程中产生的金属损耗,可用按工序测算的模式,建立回收和循环返回使用机制.根据钢种特性,对资源细分,实施精细化管理,匹配合理的使用工艺.无形损耗同样有很大的回收和循环使用潜能.回收特钢产品用户的加工废钢,有待建立有效网络体系.     

Transitional Flow between Orifice and Nonorifice Regimes at a Rectangular Sluice Gate

The hydraulic transition between nonorifice and orifice flow regimes at a rectangular sluice gate was analyzed to determine the value of a coefficient (Co) used to define the threshold between the two regimes. The transition coefficient was defined as the ratio of vertical gate opening to upstream water depth. Several dozen data sets were collected in a hydraulic laboratory, each including the measurement of upstream and downstream water depth for five different vertical gate openings, and 17 different steady-state discharges from 0.02?to?0.166?m3/s. Various approaches were tested to define the limits of the nonorifice-to-orifice regime transition, but the one presented herein uses the specific-energy equation for open-channel flow. After the transition limits were defined, an estimation of the nonorifice-to-orifice transition coefficient, Co, was made. The experimental results indicate that orifice flow always exists when Co is less than 0.83, and nonorifice flow always exists when Co is greater than 1.00. A procedure was developed to determine the flow regime and the discharge at a rectangular gate in the range 0.83相似文献   

Taxanes propagate apoptosis via two cell populations with distinctive cytological and molecular traits

Gross observation at the slaughterhouse determines the primary selection of porcine aortic valves for the manufacture of bioprostheses. This step is critical because only valves with significant abnormalities are rejected. The present study validated this selection process by investigating the pathological characteristics of one series of accepted valves and one series of rejected valves. Macroscopy, x-ray examination, light microscopy, and scanning electron microscopy (SEM) were performed on 5 initially rejected valves, 3 leaflets from 3 other initially rejected valves, and 6 valves that successfully passed this first step in the selection process. Abnormalities were macroscopically visible only on the rejected valves and were described as thick white areas, heavy white striations, thin spots, white plaques, and nodules. Individual variability in the structure of each leaflet was more significant in the rejected valves than in the valves that had passed the first inspection. The leaflets of the rejected valves were also irregularly thick with a lack of consistency in the position and prominence of the different layers. The formation of nodules and the presence of white plaques in the inner fibrosa layer were among the pathological features. The initially accepted valves considered defect free under gross observation continued to display some weaknesses, and not all of the valves selected during the first step of the process were suitable to become bioprostheses. Because the manufacturer carries out further quality control inspections at every step of preparation resulting in additional rejections, it is therefore anticipated that all valves with defects will be rejected. None of the rejected valves were defect free, and rejection was fully justified.     

An Experimental Test of Five Process Models for Subtraction.

This study is concerned with processes used by second- and fourth-grade children in solving single-digit subtraction problems. Five possible models of the solution process were evaluated by fitting observed reaction times to the linear regression predicted by each model. Most second graders and all fourth graders were best fit by a model in which the child either counted down from the larger number or counted up from the smaller, depending on which procedure required the fewest steps. In addition, there was a decrease between Grades 1 and 2 in the time taken for each step in the procedure. The results suggest a developmental trend in which children moved from a fixed algorithmic model to a more heuristic one involving judgment and estimation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于鲁棒H∞滤波的锂离子电池SOC估计

荷电状态（State of charge, SOC）估计是电池管理系统的核心功能之一,它在电动汽车的生命周期中起着重要作用。针对锂离子电池温度影响模型参数,进而导致SOC估计不准确的问题,本文提出了基于鲁棒H_∞滤波的SOC估计方法。首先,以二阶Thevenin等效电路模型做为锂离子电池基础模型,并将温度对电池模型参数的影响建模为标称电阻值和电池总容量的加性变量,视温度变化为系统的外部扰动。其次,采用滑动线性法对电池模型进行线性化,并在此基础上运用线性矩阵不等式技术设计了对SOC进行估计的鲁棒H_∞滤波器。最后,分别采用四种不同类型的动态电流激励进行仿真实验验证,并将SOC的估计结果与kalman滤波对SOC的估计结果进行对比。结果表明所设计的鲁棒H_∞滤波器能够实现对SOC更为准确的跟踪,同时对外部扰动具有较好的鲁棒性。      

Probability-Based Bridge Network Performance Evaluation

This paper presents a comprehensive mathematical model for evaluating the overall performance of a bridge network based on probability analyses of network connectivity, user satisfaction, and structural reliability of the critical bridges in the network. A bridge network consists of all nodes of interest in a geographical region. These nodes of interest are connected to each other through multiple paths. The network performance evaluation in terms of connectivity is formulated by using an event tree technique. The network performance measure of user satisfaction deals with traffic demand and capacity of each link in the network. Moreover, the shortest paths in terms of total traffic costs are identified by network optimization algorithms for each pair of the origin and destination nodes of interest under the specified traffic demands. Using this information, the minimum-weight spanning tree (MST) that consists of the identified shortest paths is constructed. The bridges associated with MST are defined as the critical bridges in the network. The network performance in terms of structural reliability of the critical bridges can be computed from system reliabilities of the critical bridges by using a series-parallel system model. Finally, by combining the above three criteria, a single numerical measure is proposed to evaluate the overall performance of the bridge network. This novel approach is illustrated on a group of fourteen existing bridges with different reliability profiles located in Colorado. This study provides the basis of a network-level bridge management system where lifetime reliability and life-cycle costs are the key considerations for optimal bridge maintenance strategies.     

Improved Pressurized Pipe Network Hydraulic Solver for Applications in Irrigation Systems

GESTAR is an advanced computational hydraulic software tool specially adapted for the design, planning, and management of pressurized irrigation networks. A summary is given of the most significant characteristics of GESTAR. The hydraulic solver for quasi-steady scenarios uses specific strategies and incorporates several new features that improve the algorithms for pipe network computation, overcoming some of the problems that arise when attempting to apply drinking water software, using the gradient method, to irrigation systems. It is shown that the gradient method is a nodal method variant, where flow rates are relaxed using head loss formula exponents. Although relaxation produces a damping effect on instabilities, it is still unable to solve some of the numerical problems common to the nodal methods. In this contribution the results of the research on computational strategies capable of dealing with low resistance elements, hydrant modelling, multiple regulation valves, numerous emitters, and pumps with complex curves are presented, obtaining accurate results even in conditions where other software fails to converge. GESTAR incorporates all these computational techniques, achieving a high convergence rate and robustness. Furthermore, GESTAR’s solver algorithm was easily adapted to incorporate inverse analysis options for optimum network control and parameter calibration. Illustrative examples are provided, documenting the improved numerical techniques and examples of GESTAR’s performance in comparison with EPANET2, a widely used gradient method-based hydraulic solver.     

Neural Network for Creep and Shrinkage Deflections in Reinforced Concrete Frames

A recently developed accurate procedure termed as the consistent procedure (CP) for evaluation of creep and shrinkage behavior in reinforced concrete (RC) frames is elaborate and requires large computational effort. An approximate procedure (AP) that has been available and widely used is simple and requires much less computational effort but can be erroneous. The feasibility of using the neural network model to simulate the inelastic deflections of CP from the results of AP for a class of RC frames is investigated. This model would enable rapid estimation of inelastic deflections of CP and would be useful at the planning stage. For this purpose, a ratio η of inelastic deflections of CP, to corresponding deflections of AP, designated as inelastic deflection ratio is defined as the output parameter. The sensitivity of η with the probable structural parameters in the practical range of values is studied and governing input parameters identified. The training is carried out for a practical range of the governing structural parameters. Trained network is validated for a number of example buildings.     

Water Treatment Units Residence-Time Distributions as Probabilistic Functions

A probabilistic approach to obtain theoretical residence-time distribution (RTD) functions for series of reactors with possible stagnation, bypassing, and recycle is presented. It is shown that most known RTD functions can be obtained from probability arguments alone, thus avoiding abstract Laplace transform mathematical techniques and providing additional physical insight. Several new RTD models for reactors in series are derived, based exclusively on using the binomial probability distribution to describe the passage of a particle through the treatment train with bypassing and stagnation possible at each individual reactor. The proposed RTD models are validated with travel time computer simulation of a large number of particles through the series of reactors. A MSExcel based computer procedure was programmed to obtain the nonideal flow parameters by minimizing the squared sum of the differences between tracer test data and the derived unit’s RTD function. The least squares parameter estimation procedure was used to fit theoretical RTDs to tracer data collected from real water treatment units with different hydraulic behavior at two locations in Mexico.