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Dissertations / Theses on the topic 'Water Mathematical optimization'
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Greene, James J. "Global optimization of water distribution systems." Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-10062009-020212/.
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Battermann, Astrid. "Mathematical optimization methods for the remediation of ground water contaminations." [S.l.] : [s.n.], 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=963762184.
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Rogalski, Richard Byron. "Mathematical and artificial neural network models for simulation and optimization of chlorine residuals in water distribution systems." access full-text online access from Digital Dissertation Consortium, 2002. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?NQ77034.
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Rogers, Scott W. "Multiobjective optimization of contaminant sensor locations in drinking water distribution systems using nodal importance concepts." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29607.
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Thesis (Ph.D)--Civil and Environmental Engineering, Georgia Institute of Technology, 2009.Committee Chair: Aral, Mustafa; Committee Member: Guan, Jiabao; Committee Member: Jang, Wonyong; Committee Member: Kim, Seong-Hee; Committee Member: Uzer, Turgay. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Abu, Rumman Malek. "Conjunctive Management of Surface Water and Groundwater Resources." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6917.
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Surface water and groundwater systems consist of interconnected reservoirs, rivers, and confined and unconfined aquifers. The integrated management of such resources faces several challenges:
High dimensionality refers to the requirement of the large number of variables that need to be considered in the description of surface water and groundwater systems. As the number of these variables increases, the computational requirements quickly saturate the capabilities of the existing management methods.
Uncertainty relates to the imprecise nature of many system inputs and parameters, including reservoir and tributary inflows, precipitation, evaporation, aquifer parameters (e.g., hydraulic conductivity and storage coefficient), and various boundary and initial conditions. Uncertainty complicates very significantly the development and application of efficient management models.
Nonlinearity is intrinsic to some physical processes and also enters through various facility and operational constraints on reservoir storages, releases, and aquifer drawdown and pumping. Nonlinearities compound the previous difficulties.
Multiple objectives pertain to the process of optimizing the use of the integrated surface and groundwater resources to meet various water demands, generate sufficient energy, maintain adequate instream flows, and protect the environment and the ecosystems. Multi-objective decision models and processes continue to challenge professional practice.
This research draws on several disciplines including groundwater flow modeling, hydrology and water resources systems, uncertainty analysis, estimation theory, stochastic optimization of dynamical systems, and policy assessment. A summary of the research contributions made in this work follows:
1.High dimensionality issues related to groundwater aquifers system have been mitigated by the use of transfer functions and their representation by state space approximations.
2.Aquifer response under uncertainty of inputs and aquifer parameters is addressed by a new statistical procedure that is applicable to regions of relatively few measurements and incorporates management reliability considerations.
3.The conjunctive management problem is formulated in a generally applicable way, taking into consideration all relevant uncertainties and system objectives. This problem is solved via an efficient stochastic optimization method that overcomes dimensionality limitations.
4.The methods developed in this Thesis are applied to the Jordanian water resources system, demonstrating their value for operational planning and management.
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Mann, James Gainey. "Process Integration: Unifying Concepts, Industrial Applications and Software Implementation." Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/29336.
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This dissertation is a complete unifying approach to the fundamentals, industrial applications and software implementation of an important branch of process-engineering principles and practice, called process integration. The latter refers to the system-oriented, thermodynamically-based and integrated approaches to the analysis, synthesis and retrofit of process plants, focusing on integrating the use of materials and energy, and minimizing the generation of emissions and wastes. This work extends process integration to include applications for industrial water reuse and wastewater minimization and presents previous developments in a unified manner.
The basic ideas of process integration are: (1) to consider first the big picture by looking at the entire manufacturing process as an integrated system; (2) to apply process-engineering principles to key process steps to establish a priori targets for the use of materials and energy, and for the generation of emissions and wastes; and (3) to finalize the details of the process design and retrofit later to support the integrated view, particularly in meeting the established targets.
Pinch technology is a set of primarily graphical tools for analyzing a process plant's potential for energy conservation, emission reduction and waste minimization. Here, we identify targets for the minimum consumption of heating and cooling utilities, mass-separating agents, freshwater consumption, wastewater generation and effluent treatment and propose economical grassroots designs and retrofit projects to meet these goals.
An emerging alternative approach to pinch technology, especially when analyzing complex water-using operations and effluent-treatment systems, is mathematical optimization. We solve nonlinear programming problems for simple water-using operations through readily available commercial software. However, more complex, nonconvex problems require sophisticated reformulation techniques to guarantee optimality and are the subject of continuing academic and commercial development.
This work develops the principles and practice of an environmentally significant breakthrough of process integration, called water-pinch technology. The new technology enables the practicing engineers to maximize water reuse, reduce wastewater generation, and minimize effluent treatment through pinch technology and mathematical optimization. It applies the technology in an industrial water-reuse demonstration project in a petrochemical complex in Taiwan, increasing the average water reuse (and thus reducing the wastewater treatment) in the five manufacturing facilities from 18.6% to 37%.
This dissertation presents complete conceptual and software developments to unify the known branches of process integration, such as heat and mass integration, and wastewater minimization, and explores new frontiers of applications to greatly simplify the tools of process integration for practicing engineers.Ph. D.
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Martins, Karlos Roberto da Silva Braga 1981. "Simulação e otimização computacional de diferentes configurações de sistemas de refrigeração por absorção água-amônia tipo GAX : Computational simulation and optimization of different arragements of absorption cooling systems water-ammonia type GAX." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/265953.
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Orientador: José Ricardo FigueiredoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
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Resumo: Neste trabalho foi adaptado um programa computacional para o projeto e simulação numérica de diferentes configurações de ciclos de refrigeração por absorção utilizando a mistura água ¿ amônia como fluido de trabalho, visando aplicações em condicionamento de ar para setores residencial e comercial. Foram estudados os ciclos de simples efeito e duas configurações de modelos com Troca de Calor Gerador-Absorvedor (GAX ¿ Generator-Absorber heat eXchange), uma com absorvedor de dois estágios e gerador de dois estágios e outra com absorvedor de três estágios e gerador de dois. Foram utilizadas equações de conservação da massa total da matéria, do número de moles de amônia e de energia para cada componente relevante da máquina, relações de estado termodinâmico para cada ponto do sistema, bem como, equações de transferência de calor em termos de parâmetro globais, para relacionar a transferência de calor às diferenças efetivas de temperatura, empregando os métodos da Diferença de Temperaturas Média Logarítmica e da Efetividade. As relações de estado termodinâmico da mistura água-amônia são derivadas analiticamente de duas equações representando a energia livre de Gibbs em termos de pressão, temperatura e concentração para as fases de líquido e de vapor. O sistema resultante de equações não lineares foi resolvido pelo método de Substituição-Newton-Raphson. Os resultados de desempenho, de temperaturas e de transferência de calor nos equipamentos que compõem o ciclo foram obtidos a partir da variação de parâmetros operacionais tais como, temperatura do ambiente a ser resfriado, temperatura do ar externo e temperatura do fluido quente na entrada do gerador. Após isso, foi realizado um estudo de otimização do coeficiente de desempenho e efeito frigorífico do ciclo GAX a partir da variação dos parâmetros globais dos trocadores
Abstract: In this work a computer program was adapted for design and numerical simulation of different configurations of absorption refrigeration cycles using the mixture water - ammonia as the working fluid, aiming at applications in air conditioning for residential and commercial sectors. Cycles of single effect, Generator-Absorber Heat eXchange (GAX ¿ Generator-Absorber heat eXchange) with two-stages absorber and two-stages generator and the other with three-stage absorber and two-stages generator were studied. Mass conservation equations of mass and energy of ammonia for each relevant component ratios thermodynamic state for each point in the system were used, as well as heat transfer equations in terms of global heat transfer parameter, relating to heat transfer to the actual temperature difference, using the methods of the logarithmic average temperature difference and effectiveness. The relations of thermodynamic state of the mixture water - ammonia are derived analytically for two equations for the Gibbs free energy in terms of pressure, temperature and concentration for phases of liquid and vapor. The resulting system of nonlinear equations was solved by the substitution method-Newton-Raphson. The results of performance, temperature and heat transfer equipment comprising in the cycle were obtained from the variation of operating parameters such as temperature of the environment to be cooled, the external air temperature and the hot fluid inlet temperature generator. After that, an optimization study of the coefficient of performance and fridge effect was performed for GAX cycle from the variation of the global parameters of the exchangers
Doutorado
Termica e Fluidos
Doutor em Engenharia Mecânica
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Kim, Doo-Il. "Development and application of integrated ozone contactor design and optimization tools." Diss., Available online, Georgia Institute of Technology, 2007, 2007. http://etd.gatech.edu/theses/available/etd-05182007-120642/.
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Thesis (Ph. D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2008.Jae-Hong Kim, Committee Chair ; Philip J.W. Roberts, Committee Member ; E. Michael Perdue, Committee Member ; Sotira Yiacoumi, Committee Member ; Thorsten Stoesser, Committee Member.
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Pavelka, David. "Optimalizace vodovodní sítě města Počátky." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2020. http://www.nusl.cz/ntk/nusl-409705.
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This diploma thesis focuses on the optimization of water supply system in the town of Počátky. It describes the process of creating a mathematical model needed for the hydraulic analysis, which was used to assess the water supply system Počátky. This thesis task is to apprise reader, with a basic distribution in the drinking water supply, how to proceed in collecting data on hydraulic analysis requirements and using tools and means used in hydraulic analysis. Conclusions are processed variants for possible optimization of water supply system Počátky.
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HIPOLITO, FABIO C. "Avaliação das metodologias de análise de sistemas de tubulações de vapor sujeitas a carregamentos do tipo Steam Hammer." reponame:Repositório Institucional do IPEN, 2016. http://repositorio.ipen.br:8080/xmlui/handle/123456789/26938.
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Carregamentos transientes termo hidráulicos do tipo Steam Hammer são eventos comuns em sistemas de tubulações de vapor com grandes potenciais de catástrofes em plantas de geração de energia. Uma vez iniciado o evento, ondas de pressões são geradas com amplitudes, geralmente, de grande magnitude ocasionando altas pressões no sistema, ruídos, deformações, fadiga, com possibilidade de danos materiais e econômicos e em casos extremos fatalidades. Os procedimentos da indústria para análise deste tipo de sistema consistem realização de análises estáticas equivalentes ou análise de espectro de resposta com carregamentos caracterizados por meio de métodos analíticos baseados em hipóteses simplificadoras do fluido e fluxo. Neste trabalho é proposta a analise de sistema de tubulações por meio do método de integração numérica com superposição modal e carregamento caracterizado por método numérico com base no método das características. Comparações foram efetuadas entre os resultados obtidos pela metodologia proposta e os procedimentos da indústria, demonstrando que, dado ao alto grau de conservadorismo, os procedimentos da indústria acarretam em superdimensionamento de estruturas e tubulações ocasionando custos adicionais de projeto, sendo a otimização do projeto obtida aplicando-se a metodologia proposta no trabalho.
Dissertação (Mestrado em Tecnologia Nuclear)
IPEN/D
Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP
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Chen, Chia-Jeng. "Hydro-climatic forecasting using sea surface temperatures." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/48974.
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A key determinant of atmospheric circulation patterns and regional climatic conditions is sea surface temperature (SST). This has been the motivation for the development of various teleconnection methods aiming to forecast hydro-climatic variables. Among such methods are linear projections based on teleconnection gross indices (such as the ENSO, IOD, and NAO) or leading empirical orthogonal functions (EOFs). However, these methods deteriorate drastically if the predefined indices or EOFs cannot account for climatic variability in the region of interest. This study introduces a new hydro-climatic forecasting method that identifies SST predictors in the form of dipole structures. An SST dipole that mimics major teleconnection patterns is defined as a function of average SST anomalies over two oceanic areas of appropriate sizes and geographic locations. The screening process of SST-dipole predictors is based on an optimization algorithm that sifts through all possible dipole configurations (with progressively refined data resolutions) and identifies dipoles with the strongest teleconnection to the external hydro-climatic series. The strength of the teleconnection is measured by the Gerrity Skill Score. The significant dipoles are cross-validated and used to generate ensemble hydro-climatic forecasts. The dipole teleconnection method is applied to the forecasting of seasonal precipitation over the southeastern US and East Africa, and the forecasting of streamflow-related variables in the Yangtze and Congo Rivers. These studies show that the new method is indeed able to identify dipoles related to well-known patterns (e.g., ENSO and IOD) as well as to quantify more prominent predictor-predictand relationships at different lead times. Furthermore, the dipole method compares favorably with existing statistical forecasting schemes. An operational forecasting framework to support better water resources management through coupling with detailed hydrologic and water resources models is also demonstrated.
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Gamot, Ritchie Mae Tonzo. "Modified Intelligent Water Drops with perturbation operators for atomic cluster optimization." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/79690/.
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A modified version of the Intelligent Water Drops algorithm (MIWD) was developed then used to determine the most stable configurations of Lennard-Jones (LJ), Binary Lennard-Jones (BLJ) and Morse Clusters. The algorithm is unbiased in that it uses no a priori cluster geometry information or cluster seeds. Results for LJ clusters show that the algorithm is effective and efficient in rediscovering all clusters up to size N = 104 with better success rates specially on difficult clusters compared to previous best methodologies reported in literature. Results on more difficult systems, such as the Binary Lennard Jones clusters up to size 50 (with 5 different atomic size ratios) and Morse clusters up to size 60 (with 2 interparticle range potentials), also showed the ability of MIWD to handle more complex systems. MIWD was then applied to predict the most stable structures of Janus clusters up to size 50 and on size 100 using a LJ potential model with a modulated angular term suited for two-patched Janus particles. Results show that MIWD is able to find well-structured geometries of Janus clusters. It is believed that this has been the first time that a nature-inspired stochastic algorithm and a variant of the IWD algorithm has been applied to the configurational optimization of Janus clusters.
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Lieb, Anna Marie. "Modeling and optimization of transients in water distribution networks with intermittent supply." Thesis, University of California, Berkeley, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10150911.
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Much of the world's rapidly growing urban population relies upon water distribution systems to provide treated water through networks of pipes. Rather than continuously supplying water to users, many of these distribution systems operate intermittently, with parts of the network frequently losing pressure or emptying altogether. Such intermittent water supply deleteriously impacts water availability, infrastructure, and water quality for hundreds of millions of people around the world. In this work I introduce the problem of intermittent water supply through the lens of applied mathematics. I first introduce a simple descriptive mathematical model that captures some hydraulic features of intermittency not accounted for by existing water distribution system software packages. I then consider the potential uses of such a model in a variety of optimization examples motivated by real-world applications. In simple test networks, I show how to reduce pressure gradients while the network fills by changing either the inflow patterns or the elevation profile. I also show test examples of using measured data to potentially recover unknown information such as initial conditions or boundary outflows. I then use sensitivity analysis to better understand how various parameters control model output, with an eye to figuring out which parameters are worth measuring most carefully in field applications, and also which parameters may be useful in an optimization setting. I lastly demonstrate some progress in descriptively modeling a real network, both through the introduced mathematical model and through a fluid-mechanics-based method for identifying data where the model is most useful.
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Love, David Keith. "Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/311177.
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Stochastic programming is a mathematical technique for decision making under uncertainty using probabilistic statements in the problem objective and constraints. In practice, the distribution of the unknown quantities are often known only through observed or simulated data. This dissertation discusses several methods of using this data to formulate, solve, and evaluate the quality of solutions of stochastic programs. The central contribution of this dissertation is to investigate the use of techniques from simulation and statistics to enable data-driven models and methods for stochastic programming. We begin by extending the method of overlapping batches from simulation to assessing solution quality in stochastic programming. The Multiple Replications Procedure, where multiple stochastic programs are solved using independent batches of samples, has previously been used for assessing solution quality. The Overlapping Multiple Replications Procedure overlaps the batches, thus losing the independence between samples, but reducing the variance of the estimator without affecting its bias. We provide conditions under which the optimality gap estimators are consistent, the variance reduction benefits are obtained, and give a computational illustration of the small-sample behavior. Our second result explores the use of phi-divergences for distributionally robust optimization, also known as ambiguous stochastic programming. The phi-divergences provide a method of measuring distance between probability distributions, are widely used in statistical inference and information theory, and have recently been proposed to formulate data-driven stochastic programs. We provide a novel classification of phi-divergences for stochastic programming and give recommendations for their use. A value of data condition is derived and the asymptotic behavior of the phi-divergence constrained stochastic program is described. Then a decomposition-based solution method is proposed to solve problems computationally. The final portion of this dissertation applies the phi-divergence method to a problem of water allocation in a developing region of Tucson, AZ. In this application, we integrate several sources of uncertainty into a single model, including (1) future population growth in the region, (2) amount of water available from the Colorado River, and (3) the effects of climate variability on water demand. Estimates of the frequency and severity of future water shortages are given and we evaluate the effectiveness of several infrastructure options.
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Bullene, Rachel. "A Case Study of Network Design for Middle East Water Distribution." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2260.
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The Middle Eastern region encompassing Israel, Jordan, and the Palestinian Territories (West Bank and Gaza) is an arid region with fast growing populations. Adequate and equitable access to water for all the people of the region is crucial to the future of Middle East peace. However, the current water distribution system not only fails to provide an adequate and equitable allocation of water, but also results adverse impacts on the environment. This project involves building a mathematical model to aid decision-makers in designing an optimal water distribution network. A new method for incorporating uncertainty in optimization that is based on Bayesian simulation of posterior predictive distributions is used to represent uncertainty in demands and costs. The output of the model is a most-probable least-cost modication to the existing water distribution infrastructure. Additionally, the model output includes the probability that a network component (new desalination plant, new pipe, new canal) is part of a least-cost installation.
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Mkireb, Chouaïb. "Optimisation et gestion des risques pour la valorisation de la flexibilité énergétique : application aux systèmes d’eau potable." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2492/document.
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Dans un contexte de croissance démographique dans lequel certaines ressources naturelles sont de plus en plus limitées, une gestion optimisée et conjointe des réseaux publics de l’eau et de l’électricité s’impose. L’ouverture progressive des marchés de l’électricité à la concurrence et les changements de réglementation dans plusieurs pays ont contribué au développement des mécanismes de la flexibilité de la demande, permettant d’impliquer directement les consommateurs dans la gestion de l’équilibre offre-demande du réseau électrique. Les systèmes d’eau potable, étant de grands consommateurs d’électricité, disposent d’une flexibilité grâce à la présence d’ouvrages de stockage d’eau (bâches et réservoirs) et de pompes à vitesse variable. Cette flexibilité, souvent exploitée uniquement à des fins de sécurisation des demandes en eau, peut être valorisée pour permettre une meilleure gestion de l’équilibre du réseau électrique. L’objectif de cette thèse est l’évaluation des valeurs économiques et écologiques relatives à l’intégration de la flexibilité des systèmes d’eau potable dans la gestion opérationnelle du système électrique français. Une étude de l’architecture des marchés de l’électricité en France est d’abord menée pour identifier les mécanismes de flexibilité de la demande les plus adaptés aux contraintes d’exploitation des systèmes d’eau. Des modèles mathématiques d’optimisation sont ensuite proposés et résolus à travers certaines heuristiques, en intégrant les incertitudes relatives aux consommations d’eau, aux prix des marchés ainsi qu’à la disponibilité des équipements de pompage. Les résultats numériques, discutés en se basant sur trois systèmes d’eau potable réels en France, intègrent les aspects économiques (en considérant les risques associés), opérationnels et écologiques. Des réductions importantes des coûts d’exploitation des systèmes d’eau sont estimées à travers la valorisation de l’énergie non consommée pendant les moments de pointe sur le marché spot de l’électricité. En parallèle, la considération des incertitudes permet de sécuriser l’opération des systèmes d’eau en temps réel, et de maîtriser les risques économiques relatifs à l’équilibrage du réseau électrique. De plus, des réductions importantes des émissions de CO2, estimées à environ 400 tonnes par jour en France, peuvent être réalisées en réduisant les volumes d’électricité issus des sources fossilesIn a context of demographic growth in which natural resources are more and more limited, optimized management of water and power networks is required. Changes in electricity markets regulation in several countries have recently enabled effective integration of Demand Response mechanisms in power systems, making it possible to involve electricity consumers in the real-time balance of the power system. Through its flexible components (variable-speed pumps, tanks), drinking water systems, which are huge electricity consumers, are suitable candidates for energy-efficient Demand Response mechanisms. However, these systems are often managed independently of power system operation, for both economic and operational reasons. In this thesis, the objective is the evaluation of the economic and the ecological values related to the integration of drinking water systems flexibility into power system operation through french demand response mechanisms. An analysis of the architecture of french electricity markets is first conducted, allowing to target the most suitable demand response mechanisms considering water systems operating constraints. Some mathematical models to optimize water systems flexibility are then proposed and solved through original heuristics, integrating uncertainties about water demands, market prices and pumping stations availability. Numerical results, which are discussed using three real water systems in France, integrate the economic aspects inclunding risks, operational and ecological aspects. Significant reductions in water systems operating costs are estimated through the optimization of demand response power bids on the French spot power market during peak times. In parallel, uncertainties consideration secures the operation of water systems in real time, and makes it possible to manage economic risks related to the power grid balancing. In addition, significant savings in CO2 emissions, estimated to around 400 tons per day in France, can be achieved by reducing electricity production from fossil sources
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David, Hélène. "Etude de matrices polymères permettant la libération contrôlée d'agents actifs en agriculture : expérimentation et modélisation des transferts de matière." Saint-Etienne, 1989. http://www.theses.fr/1989STET4004.
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L'agent actif considéré a été l'éthoprophos, principe nématicide utilisé en agrochimie, mais dans un premier temps, l'aniline a été utilisé comme agent simulant. Les processus d'absorption et de désorption dans l'eau, ont été modélisés, dans le cas d'un granulé composé d'EVA pur, à l'aide d'une solution analytique de l'équation de Fick. Un modèle mathématique basé sur une méthode numérique a été construit pour décrire les transferts à travers un granulé composé par un noyau et une enveloppe
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Trémolet, Yannick. "Parallélisation d'algorithmes variationnels d'assimilation de données en météorologie." Grenoble 1, 1995. http://www.theses.fr/1995GRE10211.
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Le probleme de l'assimilation de donnees sous sa forme generale peut se formuler: comment utiliser simultanement un modele theorique et des observations pour obtenir la meilleure prevision meteorologique ou oceanographique ?, sa resolution est tres couteuse, pour la prochaine generation de modeles elle necessitera une puissance de calcul de l'ordre de 10 tflops. A l'heure actuelle, aucun calculateur n'est capable de fournir de telles performances mais cela devrait etre possible dans quelques annees, en particulier grace aux ordinateurs paralleles a memoire distribuee. Mais, la programmation de ces machines reste un processus complique et on ne connait pas de methode generale pour paralleliser de maniere optimale un algorithme donne. Nous tenterons, de repondre au probleme de la parallelisation de l'assimilation de donnees variationnelle, ce qui nous conduira a etudier la parallelisation d'algorithmes numeriques d'optimisation assez generaux. Pour cela, nous etendrons la methodologie de l'ecriture des modeles adjoints au cas ou le modele direct est parallele avec echanges de messages explicites. Nous etudierons les differentes approches possibles pour paralleliser la resolution du probleme de l'assimilation de donnees: au niveau des modeles meteorologiques direct et adjoints, au niveau de l'algorithme d'optimisation ou enfin au niveau du probleme lui-meme. Cela nous conduira a transformer un probleme sequentiel d'optimisation sans contraintes en un ensemble de problemes d'optimisation relativement independants qui pourront etre resolus en parallele. Nous etudierons plusieurs variantes de ces trois approches tres generales et leur utilite dans le cadre du probleme de l'assimilation de donnees. Nous terminerons par l'application des methodes de parallelisation precedentes au modele de shallow water et comparerons leurs performances. Nous presenterons egalement une parallelisation du modele meteorologique arps (advanced regional prediction system)
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Mahfoudhi, Imed. "Problèmes inverses de sources dans des équations de transport à coefficients variables." Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00975168.
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Cette thèse porte sur l'étude de quelques questions liées à l'identifiabilité et l'identification d'un problème inverse non-linéaire de source. Il s'agit de l'identification d'une source ponctuelle dépendante du temps constituant le second membre d'une équation de type advection-dispersion-réaction à coefficients variables. Dans le cas monodimensionnel, la souplesse du modèle stationnaire nous a permis de développer des réponses théoriques concernant le nombre des capteurs nécessaires et leurs emplacements permettant d'identifier la source recherchée d'une façon unique. Ces résultats nous ont beaucoup aidés à définir la ligne de conduite à suivre afin d'apporter des réponses similaires pour le modèle transitoire. Quant au modèle bidimensionnel transitoire, en utilisant quelques résultats de nulle contrôlabilité frontière et des mesures de l'état sur la frontière sortie et de son flux sur la frontière entrée du domaine étudié, nous avons établi un théorème d'identifiabilité et une méthode d'identification permettant de localiser les deux coordonnées de la position de la source recherchée comme étant l'unique solution d'un système non-linéaire de deux équations, et de transformer l'identification de sa fonction de débit en la résolution d'un problème de déconvolution. La dernière partie de cette thèse discute la difficulté principale rencontrée dans ce genre de problèmes inverses à savoir la non identifiabilité d'une source dans sa forme abstraite, propose une alternative permettant de surmonter cette difficulté dans le cas particulier où le but est d'identifier le temps limite à partir duquel la source impliquée a cessé d'émettre, et donc ouvre la porte sur de nouveaux horizons.
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Nezungai, Chiedza Demetria Maputsa. "Superstructure optimisation of a water minimisation network with a embedded multicontaminant electrodialysis model." Thesis, 2016. http://hdl.handle.net/10539/21063.
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A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016The water-energy nexus considers the relationship between water and energy resources. Increases in environmental degradation and social pressures in recent years have necessitated the development of manufacturing processes that are conservative with respect to both these resources, while maintaining financial viability. This can be achieved by process integration (PI); a holistic approach to design which emphasises the unity of processes. Within the realm of PI, water network synthesis (WNS) explores avenues for reuse, recycle and regeneration of effluent in order to minimise freshwater consumption and wastewater production. When regeneration is required, membrane-based treatment processes may be employed. These processes are energy intensive and result in a trade-off between water and energy minimisation, thus creating an avenue for optimisation. Previous work in WNS employed a black box approach to represent regenerators in water minimisation problems. However, this misrepresents the cost of regeneration and underestimates the energy requirements of a system. The aim of the research presented in this dissertation is to develop an integrated water regeneration network synthesis model to simultaneously minimise water and energy in a water network. A novel MINLP model for the design of an electrodialysis (ED) unit that is capable of treating a binary mixture of simple salts was developed from first principles. This ED model was embedded into a water network superstructure optimisation model, where the objective was to minimise freshwater and energy consumption, wastewater productions, and associated costs. The model was applied to a pulp and paper case study, considering several scenarios. Global optimisation of the integrated water network and ED design model, with variable contaminant removal ratios, was found to yield the best results. A total of 38% savings in freshwater, 68% reduction in wastewater production and 55% overall cost reduction were observed when compared with the original design. This model also led to a 80% reduction in regeneration (energy) cost.
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Battermann, Astrid [Verfasser]. "Mathematical optimization methods for the remediation of ground water contaminations / vorgelegt von Astrid Battermann." 2000. http://d-nb.info/963762184/34.
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Buabeng-Baidoo, Esther. "Simultaneous minimisation of water and energy within a water and membrane network superstructure." Thesis, 2016. http://hdl.handle.net/10539/21108.
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A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2015The scarcity of water and strict environmental regulations have made sustainable engineering a prime concern in the process and manufacturing industries. Water minimisation involves the reduction of freshwater use and effluent discharge in chemical plants. This is achieved through water reuse, water recycle and water regeneration. Optimisation of the water network (WN) superstructure considers all possible interconnections between water sources, water sinks and regenerator units (membrane systems). In most published works, membrane systems have been represented using the “black-box” approach, which uses a simplified linear model to represent the membrane systems. This approach does not give an accurate representation of the energy consumption and associated costs of the membrane systems. The work presented in this dissertation therefore looks at the incorporation of a detailed reverse osmosis network (RON) superstructure within a water network superstructure in order to simultaneously minimise water, energy, operating and capital costs. The WN consists of water sources, water sinks and reverse osmosis (RO) units for the partial treatment of the contaminated water. An overall mixed-integer nonlinear programming (MINLP) framework is developed, that simultaneously evaluates both water recycle/reuse and regeneration reuse/recycle opportunities. The solution obtained from optimisation provides the optimal connections between various units in the network arrangement, size and number of RO units, booster pumps as well as energy recovery turbines. The work looks at four cases in order to highlight the importance of including a detailed regeneration network within the water network instead of the traditional “black-box’’ model. The importance of using a variable removal ratio in the model is also highlighted by applying the work to a literature case study, which leads to a 28% reduction in freshwater consumption and 80% reduction in wastewater generation.
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Ikudayisi, Akinola Mayowa. "Optimization of irrigation water in South Africa for sustainable and beneficial use." Thesis, 2017. http://hdl.handle.net/10321/2467.
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Submitted in fulfilment of the requirements of the Degree of Doctor of Engineering, Durban University of Technology, 2017.Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.
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Yusuf, Iskandar Andi. "Wasteload allocation for long-term water quality management of the Upper Citarum River, Indonesia : mathematical modeling and optimization approaches." 1994. http://hdl.handle.net/1993/18600.
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Gibbs, Matthew S. "Real-coded genetic algorithm parameter setting for water distribution system optimisation." 2008. http://hdl.handle.net/2440/49644.
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The management of Water Distribution Systems (WDSs) involves making decisions about various operations in the network, including the scheduling of pump operations and setting of disinfectant dosing rates. There are often conflicting objectives in making these operational decisions, such as minimising costs while maximising the quality of the water supplied. Hence, the operation of WDSs can be very difficult, and there is generally considerable scope to improve the operational efficiency of these systems by improving the associated decision making process. In order to achieve this goal, optimisation methods known as Genetic Algorithms (GAs) have been successfully adopted to assist in determining the best possible solutions to WDS optimisation problems for a number of years. Even though there has been extensive research demonstrating the potential of GAs for improving the design and operation of WDSs, the method has not been widely adopted in practice. There are a number of reasons that may contribute to this lack of uptake, including the following difficulties: (a) developing an appropriate fitness function that is a suitable description of the objective of the optimisation including all constraints, (b) making decisions that are required to select the most appropriate variant of the algorithm, (c) determining the most appropriate parameter settings for the algorithm, and (d) a reluctance of WDS operators to accept new methods and approaches. While these are all important considerations, the correct selection of GA parameter values is addressed in this thesis. Common parameters include population size, probability of crossover, and probability of mutation. Generally, the most suitable GA parameters must be found for each individual optimisation problem, and therefore it might be expected that the best parameter values would be related to the characteristics of the associated fitness function. The result from the work undertaken in this thesis is a complete GA calibration methodology, based on the characteristics of the optimisation problem. The only input required by the user is the time available before a solution is required, which is beneficial in the WDS operation optimisation application considered, as well as many others where computationally demanding model simulations are required. Two methodologies are proposed and evaluated in this thesis, one that considers the selection pressure based on the characteristics of the fitness function, and another that is derived from the time to convergence based on genetic drift, and therefore does not require any information about the fitness function characteristics. The proposed methodologies have been compared against other GA calibration methodologies that have been proposed, as well as typical parameter values to determine the most suitable method to determine the GA parameter values. A suite of test functions has been used for the comparison, including 20 complex mathematical optimisation problems with different characteristics, as well as realistic WDS applications. Two WDS applications have been considered: one that has previously been optimised in the literature, the Cherry Hills-Brushy Plains network; and a real case study located in Sydney, Australia. The optimisation problem for the latter case study is to minimise the pumping costs involved in operating the WDS, subject to constraints on the system, including minimum disinfectant concentrations. Of the GA calibration methods compared, the proposed calibration methodology that considered selection pressure determined the best solution to the problem, producing a 30% reduction in the electricity costs for the water utility operating the WDS. The comparison of the different calibration approaches demonstrates three main results: 1. that the proposed methodology produced the best results out of the different GA calibration methods compared; 2. that the proposed methodology can be applied in practice; and 3. that a correctly calibrated GA is very beneficial when solutions are required in a limited timeframe.http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1325448
Thesis (Ph.D.) - University of Adelaide, School of Civil, Environmental and Mining Engineering, 2008
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Olofintoye, Oluwatosin Onaopemipo. "Real time optimal water allocation in the Orange River catchment in South Africa." 2015. http://hdl.handle.net/10321/2392.
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Submitted in fulfillment of the requirements of the degree of Doctor of Engineering: Civil Engineering, Durban University of Technology. Durban. South Africa, 2015.The planning and management of water resources systems often involve formulation and establishment of optimal operating policies and the study of trade-off between different objectives. Due to the intricate nature of water resources management tasks, several models with varying degrees of complexities have been developed and applied for resolving water resources optimisation and allocation problems. Nevertheless, there still exist uncertainties about finding a generally consistent and trustworthy method that can find solutions which are very close to the global optimum in all scenarios. This study presents the development and application of a new evolutionary multi-objective optimisation algorithm, combined Pareto multi-objective differential evolution (CPMDE). The algorithm combines methods of Pareto ranking and Pareto dominance selections to implement a novel generational selection scheme. The new scheme provides a systematic approach for controlling elitism of the population which results in the simultaneous creation of short solution vectors that are suitable for local search and long vectors suitable for global search. By incorporating combined Pareto procedures, CPMDE is able to adaptively balance exploitation of non-dominated solutions found with exploration of the search space. Thus, it is able to escape all local optima and converge to the global Pareto-optimal front. The performance of CPMDE was compared with 14 state-of-the-art evolutionary multi-objective optimisation algorithms. A total of ten test problems and three real world problems were considered in the benchmark of the algorithm. Findings suggest that the new algorithm presents an improvement in convergence to global Pareto-optimal fronts especially on deceptive multi-modal functions where CPMDE clearly outperformed all other algorithms in convergence and diversity. The convergence metric on this problem was several orders of magnitude better than those of the other algorithms. Competitive results obtained from the benchmark of CPMDE suggest that it is a good alternative for solving real multi-objective optimisation problems. Also, values of a variance statistics further indicate that CPMDE is reliable and stable in finding solutions and converging to Pareto-optimal fronts in multi-objective optimisation problems. CPMDE was applied to resolve water allocation problems in the Orange River catchment in South Africa. Results obtained from the applications of CPMDE suggest it represents an improvement over some existing methods. CPMDE was applied to resolve water allocation problems in the agricultural and power sectors in South Africa. These sectors are strategic in forging economic growth, sustaining technological developments and contributing further to the overall development of the nation. They are also germane in capacitating the South African government’s commitment towards equity and poverty eradication and ensuring food security. Harnessing more hydropower from existing water sources within the frontier of the country is germane in capacitating the South African Government’s commitment to reduction of the countries’ greenhouse gas emissions and transition to a low-carbon economy while meeting a national target of 3 725 megawatts by 2030. Application of CPMDE algorithm in the behavioural analysis of the Vanderkloof reservoir showed an increase of 20 310 MWH in energy generation corresponding to a 3.2 percent increase. On analysis of storage trajectories over the operating period, it was found that the real time analysis incorporating a hybrid between CPMDE and ANN offers a procedure with a high ability to minimize deviation from target storage under the prevailing water stress condition. Overall, the real time analysis provides an improvement of 49.32 percent over the current practice. Further analysis involving starting the simulation with a proposed higher storage volume suggests that 728.53 GWH of annual energy may be generated from the reservoir under medium flow condition without system failure as opposed to 629 GWH produced from current practice. This corresponds to a 13.66 percent increase in energy generation. It was however noted that the water resources of the dam is not in excess. The water in the dam is just enough to meet all current demands. This calls for proper management policies for future operation of the reservoir to guard against excessive storage depletions. The study herein also involved the development of a decision support system for the daily operation of the Vanderkloof reservoir. This provides a low cost solution methodology suitable for the sustainable operation of the Vanderkloof dam in South Africa. Adopting real time optimisation strategies may be beneficial to the operation of reservoirs. Findings from the study herein indicate that the new algorithm represents an improvement over existing methods. Therefore, CPMDE presents a new tool that nations can adapt for the proper management of water resources towards the overall prosperity of their populace.
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Singh, Vidya Bhushan. "User Modeling and Optimization for Environmental Planning System Design." Thesis, 2014. http://hdl.handle.net/1805/6114.
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Indiana University-Purdue University Indianapolis (IUPUI)Environmental planning is very cumbersome work for environmentalists, government agencies like USDA and NRCS, and farmers. There are a number of conflicts and issues involved in such a decision making process. This research is based on the work to provide a common platform for environmental planning called WRESTORE (Watershed Restoration using Spatio-Temporal Optimization of Resources). We have designed a system that can be used to provide the best management practices for environmental planning. A distributed system was designed to combine high performance computing power of clusters/supercomputers in running various environmental model simulations. The system is designed to be a multi-user system just like a multi-user operating system. A number of stakeholders can log-on and run environmental model simulations simultaneously, seamlessly collaborate, and make collective judgments by visualizing their landscapes. In the research, we identified challenges in running such a system and proposed various solutions. One challenge was the lack of fast optimization algorithm. In our research, several algorithms are utilized such as Genetic Algorithm (GA) and Learning Automaton (LA). However, the criticism is that LA has a slow rate of convergence and that both LA and GA have the problem of getting stuck in local optima. We tried to solve the multi-objective problems using LA in batch mode to make the learning faster and accurate. The problems where the evaluation of the fitness functions for optimization is a bottleneck, like running environmental model simulation, evaluation of a number of such models in parallel can give considerable speed-up. In the multi-objective LA, different weight pair solutions were evaluated independently. We created their parallel versions to make them practically faster in computation. Additionally, we extended the parallelism concept with the batch mode learning. Another challenge we faced was in User Modeling. There are a number of User Modeling techniques available. Selection of the best user modeling technique is a hard problem. In this research, we modeled user's preferences and search criteria using an ANN (Artificial Neural Network). Training an ANN with limited data is not always feasible. There are many situations where a simple modeling technique works better if the learning data set is small. We formulated ways to fine tune the ANN in case of limited data and also introduced the concept of Deep Learning in User Modeling for environmental planning system.
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Piemonti, Adriana Debora. "Effect of Stakeholder Attitudes on the Optimization of Watershed Conservation Practices." Thesis, 2013. http://hdl.handle.net/1805/3219.
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Indiana University-Purdue University Indianapolis (IUPUI)Land use alterations have been major drivers for modifying hydrologic cycles in many watersheds nationwide. Imbalances in this cycle have led to unexpected or extreme changes in flood and drought patterns and intensities, severe impairment of rivers and streams due to pollutants, and extensive economic losses to affected communities. Eagle Creek Watershed (ECW) is a typical Midwestern agricultural watershed with a growing urban land-use that has been affected by these problems. Structural solutions, such as ditches and tiles, have helped in the past to reduce the flooding problem in the upland agricultural area. But these structures have led to extensive flooding and water quality problems downstream and loss of moisture storage in the soil upstream. It has been suggested that re-naturalization of watershed hydrology via a spatially-distributed implementation of non-structural and structural conservation practices, such as cover crops, wetlands, riparian buffers, grassed waterways, etc. will help to reduce these problems by improving the upland runoff (storing water temporally as moisture in the soil or in depression storages). However, spatial implementation of these upland storage practices poses hurdles not only due to the large number of possible alternatives offered by physical models, but also by the effect of tenure, social attitudes, and behaviors of landowners that could further add complexities on whether and how these practices are adopted and effectively implemented for benefits. This study investigates (a) how landowner tenure and attitudes can be used to identify promising conservation practices in an agricultural watershed, (b) how the different attitudes and preferences of stakeholders can modify the effectiveness of solutions obtained via classic optimization approaches that do not include the influence of social attitudes in a watershed, and (c) how spatial distribution of landowner tenure affects the spatial optimization of conservation practices on a watershed scale. Results showed two main preferred practices, one for an economic evaluation (filter strips) and one for an environmental perspective (wetlands). A land tenure comparison showed differences in spatial distribution of systems considering all the conservation practices. It also was observed that cash renters selected practices will provide a better cost-revenue relation than the selected optimal solution.