供水管网突发污染事故的应急响应与控制策略

针对我国现阶段供水管网突发污染事故应急响应技术体系尚不成熟完善的现状,在回顾近年来典型突发水源污染事故和局部管网污染事故的基础上,从解决供水管网突发污染事故应急处理的具体措施展开研究,阐述了包括监测点优化布置和污染源追踪定位技术在内的管网突发污染事故的预警及响应研究进展,并系统总结了以应急水处理、污染范围及影响评估、停水或者降压供水、管网冲洗为主要技术控制策略的污染事故响应流程,提出供水管网突发污染事故的应急响应与控制策略。     

Multiobjective optimization of water quality and rechlorination cost in water distribution systems

To comprehensively describe the effect of residual chlorine and disinfection by-products (DBPs) on water quality in water distribution systems (WDS) and optimize rechlorination cost, this study developed a multi-objective optimization model of water quality and rechlorination cost. Firstly, chlorine decay and DBPs formation were simulated using EPANET_MSX. An improved non-dominated sorting genetic algorithm II (NSGA-II) with real code was used to optimize the multiobjective model and Pareto fronts could be obtained under different conditions. The results showed that Pareto fronts obtained by average value were better than those obtained by standard deviation and multiplication. Moreover, with the number of boosters increased, maximum value of water quality increased and rechlorination cost decreased. Wall chlorine decay constants were the most important on Pareto fronts, followed by the number of chlorination nodes, proportional coefficients of trihalomethanes (THMs) generation based on residual chlorine consumption, and THMs concentration.     

Multi-objective maintenance strategy for in-service corroding pipelines using genetic algorithms

Abstract

The multi-objective optimisation technique utilising genetic algorithms is employed to develop the optimal maintenance strategy for corroding oil and gas pipelines. The objective functions of the optimisation are the maximum annual conditional probabilities of small leak and burst, respectively, of all the pipe joints included in the pipeline segment over a predefined time horizon, and the total present-value cost of corrosion repair. The allowable annual probabilities of small leak and burst, and the annual repair budget are treated as constraints in the optimisation. The proposed optimal maintenance strategy is illustrated using a natural gas pipeline segment consisting of 90 corroding pipe joints. The analysis results indicate that a diverse set of solutions are included in the obtained Pareto front, which allow the decision-maker to select the maintenance plan achieving the desired tradeoff between the reliability and cost. The approach presented in this study can be incorporated in the practical optimal maintenance planning of corroding pipelines subjected to safety and resource constraints.     

Multi‐objective Optimization of Sensor and Excitation Layouts for Frequency Response Function‐Based Structural Damage Identification

Abstract: The accuracy of many damage identification methods depends significantly on the quality of measurements collected by sensors, such as accelerometers, concerning the response characteristics of a structure. Often the number of sensors used to collect measurements is limited due to available funds, equipment, and access. In addition, the excitation location can significantly affect a sensor's ability to collect quality measurement information. Therefore, both the location and number of sensors and the location of the excitation must be optimized to maximize the quality of information collected. A multi‐objective optimization approach is presented that minimizes the number of sensors specified while maximizing the sensitivity of the frequency response functions (FRFs) collected at each specified sensor location with respect to all possible damaged structural elements. The multiple Pareto‐optimal sensor/excitation layouts obtained aid in determining the number of sensors required to obtain an effective level of measurement information. The benefit of using Pareto‐optimal sensor/excitation layouts is investigated by using the optimized layouts to collect measurement information for a FRF‐based structural damage identification method. Trial results confirm that an increase in damage identification accuracy and efficiency is achieved when Pareto‐optimal sensor/excitation layouts are used instead of nonoptimal layouts. In addition, the Pareto‐optimal layouts improved damage identification accuracy in noisy measurement environments due to increasing the quality of measurements collected.     

A multi-objective optimisation approach for sustainable pavement management

Addressing the multidimensional challenges involved in advancing the sustainability of pavement systems requires the development of optimisation-based decision support system (DSS) for pavement management with the capability to identify optimally sustainable pavement maintenance and rehabilitations (M&R) strategies. The main objective of this research work is to develop a multi-objective optimisation framework that hosts a comprehensive and integrated pavement life cycle costs–life cycle assessment model that covers the pavement’s whole life cycle, from the extraction and production of materials to construction and maintenance, transportation of materials, work-zone traffic management, usage and end-of-life. The capability of the proposed DSS is analysed in a case study aiming at investigating, from a full life cycle perspective, the extent to which a number of pavement engineering solutions are efficient in improving the environmental and economic aspects of pavement sustainability, when applied in the management of a road pavement section. Multiple bi-objective optimisation analyses considering accordingly agency costs, user costs and greenhouse gas emissions were conducted based on a multi-objective genetic algorithm. Pareto fronts were obtained for each analysis, originating a set of non-dominated maintenance and rehabilitation solutions. Posteriorly, a multi-criteria decision analysis method was used to find the best compromise solution for pavement management.     

A rapid fuzzy optimisation approach to multiple sources water blending problem in water distribution systems

This paper proposes a Fuzzy Response Surface Optimisation (FRSO) approach for the water blending problem of multiple sources to maintain the water quality in water distribution systems. In the proposed approach, instead of the more precise and complicated nonlinear equations, the response surface models are used to describe the harmful reaction kinetics. The objectives of this study are to minimise the harmful reactions in the water network. A fuzzy linear programming using the min-operator approach is applied to handle the multiple objectives. Due to the FRSO only containing quadratic models, this approach is easy to apply and the optimisation is performed rapidly. Hence, the FRSO can be used to dynamically estimate the optimal blending ratios of water coming from multiple sources. Finally, a case study and two comparisons demonstrate the FRSO's advantages as to computational efficiency and simultaneous optimisation.     

Thermodynamic analysis and evolutionary algorithm based on multi-objective optimisation of the Rankine cycle heat engine

This study demonstrates the outcomes of a research implement for the power and efficiency optimisation of a Rankine cycle heat engine employing the non-dominated sorting genetic algorithm (NSGA-II) algorithm. Two objective functions comprising the efficiency and power were included concurrently maximised. To assess this idea, multi-objective optimisation approach founded on NSGA-II method has been utilised in which following variables have been considered as decision variables: (1) the inlet temperatures of a heat source, (2) the inlet temperatures of a heat sink, (3) temperature difference (x), (4) temperature difference (y), (5) heat conductance and (6) heat capacitance. By applying the addressed multi-objective optimisation approach, Pareto optimal frontier was determined and utilising different decision-making techniques that include the LINMAP, TOPSIS and fuzzy Bellman–Zadeh approaches help us to figure out the final optimal solution.     

A state-of-the-art review of an optimal sensor placement for contaminant warning system in a water distribution network

ABSTRACT

Protection of water distribution networks (WDNs) is at the forefront because of the negative implications of the use of the contaminated water on the public health. In order to safeguard the water distribution networks from accidental and intentional attacks, a water quality sensor should be installed across the network. Remarkably, the budget constraints to procure and maintain sensors have limited the number of sensors deployed in networks. These constraints make the optimal sensor placement receive notable attention. Over time, researchers have devised various methodologies to tackle sensor placement in a water distribution network. Investigations have shown that each of the methodologies has a research gap which must be addressed. In this work, a state-of-the-art review of optimal sensor placement in a water distribution network is presented. The review results show technical challenges, possible solutions, and future research directions in this domain.     

Comparison of injection well patterns for remediating benzene‐contaminated groundwater

Ten alternative injection well patterns and a no‐action plan were evaluated for bioremediating benzene‐contaminated groundwater. Evaluations were made for a silty‐sand aquifer using a contaminant fate and transport model. Wells injected water containing 8 mg/L dissolved oxygen. The study's objective was to rank the alternative schemes based upon mass of contaminant removed and area of residual groundwater contamination. Interior configurations with injection wells at areas of high benzene concentration outperformed the other remediation schemes. Interior wells supply oxygen quickly to areas of a plume where it is most needed. Alternative configurations rely upon groundwater to transport the oxygen, an inefficient process. No action was the least effective strategy.     

Concurrent multi-scale modelling and updating of long-span bridges using a multi-objective optimisation technique

This paper aims at developing an innovative technique of concurrent multi-objective optimisation for updating the multi-scale model of long-span bridges. A multi-scale model is established for the purpose of concurrently analysing the global response of the structure and nonlinear local damages in order to assess structural state and local damage evolution or deteriorating, respectively. A multi-objective optimisation technique is proposed in this work for concurrent multi-scale model updating, in which several key issues including the determination of the objective functions and constraint conditions, the multi-objective optimisation algorithm and how to find the optimal solution from many non-inferior solutions are studied. The proposed concurrent multi-objective optimisation technique is applied to update the initial multi-scale model of Runyang Suspension Bridge (RYSB) near Shanghai, and the updated model is validated by the data from the field tests conducted for obtaining the response in global (dynamic properties) and local levels.     

Fast network multi-objective design algorithm combined with an a posteriori procedure for reliability evaluation under various operational scenarios

This paper presents a methodology for the optimal design of water supply networks. It features a multi-objective optimisation (aimed at minimising costs and maximising resilience) and a subsequent ‘retrospective’ evaluation of network reliability under various operational scenarios. The multi-objective optimisation is based on an algorithm specifically developed for the design of real networks which feature a very high number of nodes and pipes. The ‘retrospective’ evaluation of network reliability is assessed considering resilience contrasted with several other indexes adopted to describe the operational performance of the network under critical scenarios such as segment isolation or hydrant activation, and different water demand conditions. In the applications two case studies, made up of a simple benchmark network and a real network respectively, are considered for the multi-objective optimisation; the ‘retrospective’ evaluation of reliability is performed only on the real network. The latter example clearly highlights that the procedure proposed allows reliability and performance to be offset against cost, consenting informed choice of the optimal network configuration.     

Alternative estimate of source distribution in microbial source tracking using posterior probabilities

Microbial source tracking (MST) is a procedure used to determine the relative contributions of humans and animals to fecal microbial contamination of surface waters in a given watershed. Studies of MST methodology have focused on optimizing sampling, laboratory, and statistical analysis methods in order to improve the reliability of determining which sources contributed most to surface water fecal contaminant. The usual approach for estimating a source distribution of microbial contamination is to classify water sample microbial isolates into discrete source categories and calculate the proportion of these isolates in each source category. The set of proportions is an estimate of the contaminant source distribution. In this paper we propose and compare an alternative method for estimating a source distribution—averaging posterior probabilities of source identity across isolates. We conducted a Monte Carlo simulation covering a wide variety of watershed scenarios to compare the two methods. The results show that averaging source posterior probabilities across isolates leads to more accurate source distribution estimates than proportions that follow classification.     

Multi-objective optimization of water distribution networks

Two multi-objective approaches to the consideration of pipe breakage data in water distribution network designs are formulated. Both models are based on the constraint method for multi-objective analysis. One model analyses the relationship between initial capital cost and subsequent repair and maintenance costs. Pipe breakage data is used to restrict the repair costs permitted in the system. The other model examines the relationships between initial pipe costs and the reliability of the pipes within the distribution network. In this second model, both the worst case and average system performance are examined in relation to the cost making model a three-objective approach. The pipe breakage data is used to restrict the expected number of failures allowed in any link. The actual number of expected breaks occurring in each link is then used to develop Poisson-based probabilities of node isolation. Application of the two approaches shows that the information obtained from such multi-objective approaches gives improved understanding into the nature of the issues behind initial cost and repair cost and initial cost and system reliability.     

An unusual and persistent contamination of drinking water by cutting oil

Drinking water contamination by materials, such as cutting oil, used to set up pipelines is an uncommon but possible event. This paper describes the analytical procedures used to identify the components of that contaminant in drinking water. Volatile and semi-volatile chemical species, responsible for an unpleasant taste and odour, were recognised by solid phase microextraction and GC/MS techniques. Among the volatile compounds, the presence of xylenes, bornyl acetate and diphenyl ether was confirmed by certificate standards and quantified in the most contaminated samples.     

Environmental and food contamination with PCB's in Japan

In Japan “Yusho”, i.e., poisoning caused by ingestion of rice oil contaminated with PCB's, broke out in October 1968, and produced more than 1200 officially certified cases. Nevertheless, it was only regarded as a kind of food poisoning and its connection with environmental and biological contamination was only imperfectly taken into consideration.Finally, in the autumn of 1970, two study groups, from the Ehime University and the Kyoto City Hygienic Institute, reported on the PCB contamination of salt water and fresh water fishes in Japan. Subsequently many reports about PCB's as an environmental contaminant have been published by several study groups throughout Japan, and nowadays the PCB polluted state of Japan has become rather clearly recognized.This report will present information on environmental, food and human contamination with PCB's in Japan especially also in some typically contaminated local areas, in addition to summarizing some overall aspects of the PCB problem in Japan (e.g., the production, shipment and use of PCB's).     

基于约束多目标优化算法的盾构隧道设计方法

当前盾构隧道的设计仍主要依托于经验确定设计参数,然后对其安全性进行校核,难以定量的考虑成本和控制指标(收敛变形等)的关系。以衬砌厚度、截面配筋率、横向接头螺栓直径为设计参数,以成本及结构的水平收敛变形为优化目标,结合多目标优化的算法,进行了盾构隧道的横断面设计。采用非支配原理,通过引入约束违反函数,实现了基于NSGA-Ⅱ算法的复杂约束条件处理。最后通过具体算例,完成了满足截面安全性要求的限制条件下,完整Pareto前沿面的获取工作,并与无约束优化结果进行了分析对比,说明了迭代过程的收敛性,阐述了所得Pareto前沿面的价值意义,得到了不同设计条件下的最优解。     

Optimal joint deployment of flow and pressure sensors for leak identification in water distribution networks

ABSTRACT

A multi-objective optimization methodology is proposed herein for accurate identification of leakage in water distribution networks (WDNs) using pressure and flow sensors. We first model leakage at potential nodes using the EPANET software, and then divide WDN into near-homogenous zones using k-means clustering algorithm based on geographic distribution of nodes. Finally, flow and pressure sensors locations are optimized using the NSGA-II algorithm to identify the leakage zone accurately. Novelty of the proposed approach lies in sequential optimization of flow and pressure sensors placement, which helps improve the accuracy of leakage zone identification in WDNs. The objective functions of this study are: 1) maximizing accuracy of identified leakage zone and 2) minimizing number of sensors (and hence operational costs). Simulation results of the Mesopolis WDN corroborate the efficiency and effectiveness of the proposed approach.     

Calibrating a high-fidelity finite element model of a highway bridge using a multi-variable sensitivity-based optimisation approach

This article presents the implementation of a calibration procedure for a finite element (FE) model of a state highway bridge using sensory data measured on the bridge. The objective is to modify the high-fidelity FE model of the bridge so that its dynamic behaviour matches, as closely as possible, that of the bridge under analysis. The bridge under investigation is a steel–concrete composite bridge that is instrumented with a wireless monitoring system to collect its vibration response under ambient vibrations. A detailed three-dimensional FE model of the bridge was developed to represent the bridge as realistically as possible. The detailed modelling can minimise the amount of uncertainty in the model and the number of parameters that require updating. A multi-variable sensitivity-based objective function is used to minimise the error between the experimentally measured and the FE-computed modal characteristics. An iterative optimisation approach has been undertaken to find the optimum structural parameters of the FE model that minimise the selected objective function. It is shown that developing a high-fidelity FE model may help simplify the model calibration process for a large structure, which is contrary to conventional thinking on the subject.     

Pyrolysis kinetics and multi-objective inverse modelling of cellulose at the microscale

The chemistry of pyrolysis, together with heat transfer, drives ignition and flame spread of biomass materials under many fire conditions, but it is poorly understood. Cellulose is the main component of biomass and is often taken as a surrogate for biomass. Its chemistry of pyrolysis is simpler and dominates the pyrolysis of biomass. Many reaction schemes with corresponding kinetic parameters can be found in the literature for the pyrolysis of cellulose, but their appropriateness for fire is unknown. This study investigated inverse modelling and blind predictions of six reaction schemes of different complexities for isothermal and non-isothermal thermogravimetric experiments. We used multi-objective optimisation to simultaneously and separately inverse model the kinetic parameters of each reaction scheme to several experiments. Afterwards we tested these parameters with blind predictions. For the first time, we reveal a set of equally viable solutions for the modelling of pyrolysis chemistry of different experiments. This set of solutions is called a Pareto front, and represents a trade-off between predictions of different experiments. It stems from the uncertainty in the experiments and in the modelling. Parameters derived from non-isothermal experiments compared well with the literature, and performed well in blind predictions of both isothermal and non-isothermal experiments. Complexity beyond the Broido-Shafizadeh scheme with seven parameters proved to be unnecessary to predict the mass loss of cellulose; hence, simple reaction schemes are most appropriate for macroscale fire models. Modellers should, therefore, use simple reaction schemes to model pyrolysis in macroscale fire models.     

Controllability analysis as a pre-selection method for sensor placement in water distribution systems

Detection of contamination events in water distribution systems is a crucial task for maintaining water security. Online monitoring is considered as the most cost-effective technology to protect against the impacts of contaminant intrusions. Optimization methods for sensor placement enable automated sensor layout design based on hydraulic and water quality simulation. However, this approach results in an excessive computational burden. In this paper we outline the application of controllability analysis as preprocessing method for sensor placement. Based on case studies we demonstrate that the method decreases the number of decision variables for subsequent optimization dramatically to app. 30 to 40 percent.