872 resultados para Optimisation granulaire
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In the past, the focus of drainage design was on sizing pipes and storages in order to provide sufficient network capacity. This traditional approach, together with computer software and technical guidance, had been successful for many years. However, due to rapid population growth and urbanisation, the requirements of a “good” drainage design have also changed significantly. In addition to water management, other aspects such as environmental impacts, amenity values and carbon footprint have to be considered during the design process. Going forward, we need to address the key sustainability issues carefully and practically. The key challenge of moving from simple objectives (e.g. capacity and costs) to complicated objectives (e.g. capacity, flood risk, environment, amenity etc) is the difficulty to strike a balance between various objectives and to justify potential benefits and compromises. In order to assist decision makers, we developed a new decision support system for drainage design. The system consists of two main components – a multi-criteria evaluation framework for drainage systems and a multi-objective optimisation tool. The evaluation framework is used for the quantification of performance, life-cycle costs and benefits of different drainage systems. The optimisation tool can search for feasible combinations of design parameters such as the sizes, order and type of drainage components that maximise multiple benefits. In this paper, we will discuss real-world application of the decision support system. A number of case studies have been developed based on recent drainage projects in China. We will use the case studies to illustrate how the evaluation framework highlights and compares the pros and cons of various design options. We will also discuss how the design parameters can be optimised based on the preferences of decision makers. The work described here is the output of an EngD project funded by EPSRC and XP Solutions.
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Most of water distribution systems (WDS) need rehabilitation due to aging infrastructure leading to decreasing capacity, increasing leakage and consequently low performance of the WDS. However an appropriate strategy including location and time of pipeline rehabilitation in a WDS with respect to a limited budget is the main challenge which has been addressed frequently by researchers and practitioners. On the other hand, selection of appropriate rehabilitation technique and material types is another main issue which has yet to address properly. The latter can affect the environmental impacts of a rehabilitation strategy meeting the challenges of global warming mitigation and consequent climate change. This paper presents a multi-objective optimization model for rehabilitation strategy in WDS addressing the abovementioned criteria mainly focused on greenhouse gas (GHG) emissions either directly from fossil fuel and electricity or indirectly from embodied energy of materials. Thus, the objective functions are to minimise: (1) the total cost of rehabilitation including capital and operational costs; (2) the leakage amount; (3) GHG emissions. The Pareto optimal front containing optimal solutions is determined using Non-dominated Sorting Genetic Algorithm NSGA-II. Decision variables in this optimisation problem are classified into a number of groups as: (1) percentage proportion of each rehabilitation technique each year; (2) material types of new pipeline for rehabilitation each year. Rehabilitation techniques used here includes replacement, rehabilitation and lining, cleaning, pipe duplication. The developed model is demonstrated through its application to a Mahalat WDS located in central part of Iran. The rehabilitation strategy is analysed for a 40 year planning horizon. A number of conventional techniques for selecting pipes for rehabilitation are analysed in this study. The results show that the optimal rehabilitation strategy considering GHG emissions is able to successfully save the total expenses, efficiently decrease the leakage amount from the WDS whilst meeting environmental criteria.
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This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.
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BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.
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In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.
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The tanning industries are those which transform animal hide or skin into leather. Due to the complexity of the transformation process, greater quantities of chemicals are being used which results in the generation of effluents with residual solids. The chromium in the residual waters generated by tanning tend to be a serious problem to the environment, therefore the recovery of this metal could result in the reduction of manufacturing costs. This metal is usually found in a trivalent form which can be converted into a hexavalent compound under acidic conditions and in the presence of organic matter. The present study was carried out with the objective to recover chromium through an extraction/re-extraction process using micro emulsions. Micro emulsions are transparent and thermodynamically stable system composed of two immiscible liquids, one forming the continuous phase and the other dispersed into micro bubbles, established by an interfacial membrane formed by surface active and co-surface active molecules. The process of recovering the chromium was carried out in two stages. The first, an extraction process, where the chromium was extracted in the micro emulsion phase and the aqueous phase in excess was separated. In the second stage, a concentrated acid was added to the micro emulsion phase rich in chromium in order to obtain a Winsor II system, where the water that formed in the micro emulsion phase separates into a new micro emulsion phase with a higher concentration of chromium, due to the lowering of the hydrophiles as well as the ionisation of the system. During the experimental procedure, a study was initiated with a synthetic solution of chromium sulphate passing onto the effluent. A Morris extractor was used in the extraction process. Tests were carried out according to the plan and the results were analysed by statistical methods in order to optimise the main parameters that influence the process: the total rate of flow (Q), stirring speed (w) and solvent rate (r). The results, after optimization, demonstrated that the best percentuals in relation to the chromium extraction (99 %) were obtained in the following operational conditions: Q= 2,0 l/h, w= 425 rpm and r= 0,375. The re-extraction was carried out at room temperature (28 °C), 40 °C and 50°C using hydrochloric acid (8 and 10 M) and sulphuric acid (8 M) as re-extracting agents. The results obtained demonstrate that the process was efficient enough in relation to the chromium extraction, reaching to re-extraction percentage higher than 95 %.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This study investigates the utilisation of a simplified model in the transient analysis of a thermal cooling process. In such process the external thermal resistance between the surface and the surroundings is high compared to the system internal thermal resistance, so that the first controls the heat transfer process. In this case the Biot number is lower than 0.1. Aluminium reels were utilised, which, with proper internal instrumentation, furnished experimental results for the thermal cooling process. Based on experimental data, a simplified model for the determination of the process film coefficient was used. Subsequently, experimental and theoretical results were compared. The change of the airflow direction was also investigated for the cooling process, aiming at process time optimisation. (C) 2001 Elsevier B.V. Ltd.
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This work aims with an approach for cogeneration plants evaluation based on thermoeconomic functional diagram analysis. The second law of thermodynamics is used to develop a methodology to analyse cogeneration systems, based on exergoeconomics evaluation. The thermoeconomic optimisation method developed is applied to allow a better configuration of the cogeneration plant associated to a university hospital. Also ecological efficiency is evaluated. The method was efficient and contributes for thermoeconomics modelling and analysis and can be applied to any sort of thermal system, especially those with combined heat and power in thermal parity. (C) 2012 Elsevier Ltd. All rights reserved.
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This work describes a methodology developed for determination of costs associated to products generated in a small wastewater treatment station for sanitary wastewater from a university campus. This methodology begins with plant component units identification, relating their fluid and thermodynamics features for each point marked in its process diagram. Following, its functional diagram is developed and its formulation is elaborated, in exergetic base, describing all equations for these points, which are the constraints for exergetic production cost problem and are used in equations to determine the costs associated to products generated in SWTS. This methodology was applied to a hypothetical system based on SWTS former parts and presented consistent results when compared to expected values based on previous exergetic expertise. (C) 2008 Elsevier Ltd. All rights reserved.
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The paper presents an extended genetic algorithm for solving the optimal transmission network expansion planning problem. Two main improvements have been introduced in the genetic algorithm: (a) initial population obtained by conventional optimisation based methods; (b) mutation approach inspired in the simulated annealing technique, the proposed method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Excellent performance is reported in the test results section of the paper for a difficult large-scale real-life problem: a substantial reduction in investment costs has been obtained with regard to previous solutions obtained via conventional optimisation methods and simulated annealing algorithms; statistical comparison procedures have been employed in benchmarking different versions of the genetic algorithm and simulated annealing methods.
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The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)