Genetic algorithms and GIS data for decision making in planning water distribution networks

This thesis is concerned with the optimal design of Water Distribution Networks (WDNs). The design involves finding an acceptable trade-off between cost minimisation and the maximisation of numerous system benefits. The primary design problem involves cost-effective specification of a pipe network layout and pipe sizes in order to satisfy expected consumer water demands within required pressure limits. The design of a WDN has many variable parameters such as position and size of the water sources, position and the size of the pipes and position of the treatment plants. However, the layout is constrained by the location of existing facilities such as streets and buildings and other geographic features. The total costs may consist of the cost of network materials such as pipes, construction works and system operation and maintenance. The problem may be extended to consider the design of additional components, such as reservoirs, tanks, pumps and valves. Practical designs must also cater for the uncertainty of demand, the requirement of surplus capacity for future growth, and the hydraulic reliability of the system under different demand and potential failure conditions. The thesis reviews the literature related to water distribution networks, their design and optimisation. It then presents a Genetic Algorithm (GA) formulation to assist in developing the design of a water distribution network. The main aim of this research is to investigate the possibility of combining GAs and GIS in the design optimisation. A decision mechanism is developed which enables the model to reach a meaningful solution and provide a practical design technique for WDNs. The aim is also to provide an experimental analysis of the combined GA and decision mechanism to solve the problem in hand and to assess the robustness of these techniques when applied to different instances. An initial prototype model is presented for the design of a WDN which is used to determine the necessary features of the 'final' model. These features include the world in which the model will be built, the design of the fitness function, chromosome representation, and GA operators. The research mainly concluded that the initial model prototype was useful to determine the necessary features and to produce the final model which enables a variety of necessary factors to be explicitly included in the design of WDNs. This initial model suggested that the final model should include the decision mechanism, which is a matter of policy management and hydraulics, and hydraulic principles which allowed to compare the behaviour of different parameters and to simulate the functioning of the network under different scenarios. Water allocation and distribution policies can be applied according to the importance of the demand area and the ability of the system to deliver sufficient water amounts. These policies link essential hydraulic and institutional relationships as well as water uses and users and allocation decision-making process. It was also found that the representation of the world layout is important. The world is described in GIS in terms of models that define the concepts and procedures needed to translate real-world features into data. The important aspects in the chromosome representation are the node positions, the links. In this case, a chromosome must contain the three-dimensional node coordinates, the connection between nodes, the head required to pump the water. The best model parameters were extracted to be used in real-life situations. The result of tests on an example world demonstrated that the model was successful, and the potential exists for the use of this formulation in more complex and real-world scenarios

Water Systems towards New Future Challenges

This book comprises components associated with smart water which aims at the exploitation and building of more sustainable and technological water networks towards the water–energy nexus and system efficiency. The implementation of modeling frameworks for measuring the performance based on a set of relevant indicators and data applications and model interfaces provides better support for decisions towards greater sustainability and more flexible and safer solutions. The hydraulic, management, and structural models represent the most effective and viable way to predict the behavior of the water networks under a wide range of conditions of demand and system failures. The knowledge of reliable parameters is crucial to develop approach models and, therefore, positive decisions in real time to be implemented in smart water systems. On the other hand, the models of operation in real-time optimization allow us to extend decisions to smart water systems in order to improve the efficiency of the water network and ensure more reliable and flexible operations, maximizing cost, environmental, and social savings associated with losses or failures. The data obtained in real time instantly update the network model towards digital water models, showing the characteristic parameters of pumps, valves, pressures, and flows, as well as hours of operation towards the lowest operating costs, in order to meet the requirement objectives for an efficient system

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

Advances in Modeling and Management of Urban Water Networks

The Special Issue on Advances in Modeling and Management of Urban Water Networks (UWNs) explores four important topics of research in the context of UWNs: asset management, modeling of demand and hydraulics, energy recovery, and pipe burst identification and leakage reduction. In the first topic, the multi-objective optimization of interventions on the network is presented to find trade-off solutions between costs and efficiency. In the second topic, methodologies are presented to simulate and predict demand and to simulate network behavior in emergency scenarios. In the third topic, a methodology is presented for the multi-objective optimization of pump-as-turbine (PAT) installation sites in transmission mains. In the fourth topic, methodologies for pipe burst identification and leakage reduction are presented. As for the urban drainage systems (UDSs), the two explored topics are asset management, with a system upgrade to reduce flooding, and modeling of flow and water quality, with analyses on the transition from surface to pressurized flow, impact of water use reduction on the operation of UDSs, and sediment transport in pressurized pipes. The Special Issue also includes one paper dealing with the hydraulic modeling of an urban river with a complex cross-section

Multiphase flow modelling for enhanced oil and gas drilling and production

From the exploration to the abandonment of an oil and gas discovery, operators and engineers are constantly faced with the challenge of achieving the best commercial potential of oil fields. Although the petroleum engineering community has significantly contributed towards maximising the potential of discovered prospects, the approach adopted so far has been compartmentalised with little (heuristics-based) or no quality integration. The highly interconnected nature of the decision factors affecting the management of any field requires increased implementation of Computer-Aided Process Engineering (CAPE) methods, thus presenting a task for which chemical engineers have the background to make useful contributions. Drilling and production are the two primary challenging operations of oilfield activities, which span through different time horizons with both fast and slow-paced dynamics. These attributes of these systems make the application of modelling, simulation, and optimisation tasks difficult. This PhD project aims to improve field planning and development decisions from a Process Systems Engineering (PSE) perspective via numerical (fluid dynamics) simulations and modelbased deterministic optimisation of drilling and production operations, respectively. Also demonstrated in this work is the importance of deterministic optimisation as a reliable alternative to classical heuristic methods. From a drilling operation perspective, this project focuses on the application of Computational Fluid Dynamics (CFD) as a tool to understand the intricacies of cuttings transport (during wellbore cleaning) with drilling fluids of non-Newtonian rheology. Simulations of two-phase solid-liquid flows in an annular domain are carried out, with a detailed analysis on the impact of several drilling parameters (drill pipe eccentricity, inclination angle, drill pipe rotation, bit penetration rate, fluid rheology, and particle properties) on the cuttings concentration, pressure drop profiles, axial fluid, and solid velocities. The influence of the flow regime (laminar and turbulent) on cuttings transport efficiency is also examined using the Eulerian-Eulerian and Lagrangian-Eulerian modelling methods. With experimentally validated simulations, this aspect of the PhD project provides new understanding on the interdependence of these parameters; thus facilitating industrial wellbore cleaning operations. The second part of this project applies mathematical optimisation techniques via reduced-order modelling strategies for the enhancement of petroleum recovery under complex constraints that characterise production operations. The motivation for this aspect of the project stems from the observation that previous PSE-based contributions aimed at enhancing field profitability, often apply over-simplifications of the actual process or neglect some key performance indices due to problem complexity. However, this project focuses on a more detailed computational integration and optimisation of the models describing the whole field development process from the reservoir to the surface facilities to ensure optimal field operations. Nonlinear Programs (NLPs), Mixed-Integer Linear Programs (MILPs), and Mixed-Integer Nonlinear Programs (MINLPs) are formulated for this purpose and solved using high-fidelity simulators and algorithms in open-source and commercial solvers. Compared to previous studies, more flow physics are incorporated and rapid computations obtained, thus enabling real-time decision support for enhanced production in the oil and gas industry

Large space structures and systems in the space station era: A bibliography with indexes (supplement 03)

Bibliographies and abstracts are listed for 1221 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1991 and June 30, 1991. Topics covered include large space structures and systems, space stations, extravehicular activity, thermal environments and control, tethering, spacecraft power supplies, structural concepts and control systems, electronics, advanced materials, propulsion, policies and international cooperation, vibration and dynamic controls, robotics and remote operations, data and communication systems, electric power generation, space commercialization, orbital transfer, and human factors engineering

Methodology for the optimal management design of water resources system under hydrologic uncertainty

Un sistema de gestión de sequías apropiado requiere de la anticipación de los posibles efectos que un episodio de este tipo tenga sobre el sistema de recursos hídricos. Esta tarea sin embargo resulta más complicada de lo que parece. En primer lugar, debido al alto grado de incertidumbre existente en la predicción de variables hidrológicas futuras. Y en segundo, debido al riesgo de sobrerreacción en la activación de medidas de mitigación generando falsa sensación de escasez, o sequía artificial. A este respecto, los planes especiales de sequía proveen de herramientas para la gestión eficiente de situaciones con escasez de recursos y la preparación de cara a futuros eventos. De todos modos, las diferentes estrategias de operación seguidas en cada sistema de recursos hídricos hacen que las herramientas que en algunos casos resultaron altamente útiles no lo sean tanto cuando se aplican en sistemas distintos. Debido a la falta de tiempo y/o al exceso de confianza en los trabajos realizados por terceros, con excelentes resultados en sus respectivos casos, a veces se cae en el error de implementar metodologías no del todo apropiadas en sistemas con requisitos completamente distintos. El desarrollo y utilización de metodologías generalizadas aplicables a diferentes sistemas y capaces de proporcionar resultados adaptados a cada caso es, por tanto, muy deseable. Este es el caso de las herramientas de modelación de sistemas de recursos hídricos generalizadas. Estas permiten homogeneizar los procesos mientras siguen siendo los suficientemente adaptables para proporcionar resultados apropiados para cada caso de estudio. Esta tesis presenta una serie de herramientas destinadas a avanzar en el análisis y comprensión de los sistemas de recursos hídricos, haciendo énfasis en la prevención de sequías y la gestión de riesgos. Las herramientas desarrolladas incluyen: un modelo de optimización generalizado para esquemas de recursos hídricos, con capacidad para la representación detallada de cualquier sistema de recursos hídricos, y una metodología de análisis de riesgo basada en la optimización de Monte Carlo con múltiples series sintéticas. Con estas herramientas es posible incluir tanto la componente superficial como la subterránea del sistema estudiado dentro del proceso de optimización. La optimización está basada en la resolución iterativa de redes de flujo. Se probó la consistencia y eficiencia de diferentes algoritmos de resolución para encontrar un balance entre la velocidad de cálculo, el número de iteraciones, y la consistencia de los resultados, aportando recomendaciones para el uso de cada algoritmo dadas las diferencias entre los mismos. Las herramientas desarrolladas se aplican en dos casos de estudio reales en la evaluación y posibilidad de complementación de los sistemas de monitorización y alerta temprana de sequías existentes en los mismos. En el primer caso, se propone un enfoque alternativo para la monitorización de la sequía en el sistema de operación anual del río Órbigo (España), complementándolo con la utilización de la metodología de análisis de riesgo. En el segundo caso, las herramientas se emplean en un sistema con una estrategia de operación completamente distinta. Se estudia como el análisis de riesgo de la gestión óptima puede ayudar a la activación anticipada de los escenarios de sequía en los sistemas de los ríos Júcar y Turia, cuya operación es hiperanual. En esta ocasión, el sistema de indicadores existente goza de una gran confianza por parte de los usuarios. La metodología de análisis de riesgo es, sin embargo, capaz de anticipar los eventos de sequía con mayor alarma, aspecto que es deseable si se quiere evitar que los episodios en desarrollo vayan a más. En ambos casos se muestra como la evaluación anticipada de las posibles situaciones futuras del sistema permiten una definición confiable de los escenarios de sequía con suficiente antelación para la activación efectiva de medidas de prevención y/o mitigación en caso de ser necesarias. La utilización de indicadores provenientes de modelos frente a indicadores basados en datos observados es complementaria y ambos deberían utilizarse de forma conjunta para mejorar la gestión preventiva de los sistemas de recursos hídricos. El empleo de modelos de optimización en situaciones de incertidumbre hidrológica es muy apropiado gracias a la no necesidad de definir reglas de gestión para obtener los mejores resultados del sistema, y teniendo en cuenta que las reglas de operación habituales pueden no ser completamente adecuadas en estas ocasiones.Haro Monteagudo, D. (2014). Methodology for the optimal management design of water resources system under hydrologic uncertainty [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/45996TESI

Relationships between pumping costs and water quality in optimal operation of regional multiquality water distribution systems

The operation of regional multiquality water distribution systems (WDSs) is a complex task involving multiple objectives in order to meet customer water quantity and quality requirements. These objectives, often conflicting, include scheduling of pumps to minimise pumping costs and mixing different quality waters from sources to ensure adequate quality water for customers. Evolutionary algorithms have been successfully applied to optimise operation of regional WDSs. Although a considerable reduction in pumping costs was demonstrated in past studies, other legitimate objectives, for example water quality, were not considered on an equal basis as they were included as a constraint. This single-objective approach precludes the tradeoffs between the objectives being obtained, so any insight on how to operate such a system cannot be provided should pumping costs and water quality be considered on equal basis. A multi-objective approach is applied in this thesis to optimise operation of regional multiquality WDSs considering pumping costs and water quality as legitimate objectives. Two optimisation models with increasing complexity are proposed. The first model considers two objectives, the pumping costs and a general water quality objective. The second model includes three objectives, the pumping costs and two water quality objectives for turbidity and salinity. The optimisation models are applied to three example networks from the literature using numerous scenarios and water quality data from the Wimmera Mallee Pipeline, Australia. A methodology is proposed to find the optimal solution for the multi‐objective optimisation of the WDS, which links a network simulator with a multi-objective genetic algorithm. Prior to optimisation, the performance of algorithm parameters is evaluated and their sensitivity analysed, for which a new methodology is developed. The following results were obtained. For the two-objective optimisation problem, there is a tradeoff with a competing nature between pumping costs and water quality. It means that reduction in pumping costs cannot be achieved without deterioration of water quality delivered to customers and vice versa. For the three-objective optimisation problem, interestingly, there is not a unique type of tradeoff (either competing or non-competing) between a particular pair of objectives. It is dependent on network hydraulics in combination with water quality at sources and customer water quality requirements. General principles behind the tradeoffs are formulated based on new categorisation of sources, so called consistent/inconsistent water quality (CWQ/IWQ) sources, in relation to customer water quality requirements. A practical approach for system operational strategy is developed for the purpose of long-term operational planning. It enables an operator to schedule supply from multiple sources with minimum pumping costs and customer water quality requirements being satisfied as much as possible, for all predicted water quality scenarios in the system.Doctor of Philosoph