955 resultados para Load flow, Optimization of power systems
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In order to address and resolve the wastewater contamination problem of the Sines refinery with the main objective of optimizing the quality of this stream and reducing the costs charged to the refinery, a dynamic mass balance was developed nd implemented for ammonia and polar oil and grease (O&G) contamination in the wastewater circuit. The inadequate routing of sour gas from the sour water stripping unit and the kerosene caustic washing unit, were identified respectively as the major source of ammonia and polar substances present in the industrial wastewater effluent. For the O&G content, a predictive model was developed for the kerosene caustic washing unit, following the Projection to Latent Structures (PLS) approach. Comparison between analytical data for ammonia and polar O&G concentrations in refinery wastewater originating from the Dissolved Air Flotation (DAF) effluent and the model predictions of the dynamic mass balance calculations are in a very good agreement and highlights the dominant impact of the identified streams for the wastewater contamination levels. The ammonia contamination problem was solved by rerouting the sour gas through an existing clogged line with ammonia salts due to a non-insulated line section, while for the O&G a dynamic mass balance was implemented as an online tool, which allows for prevision of possible contamination situations and taking the required preventive actions, and can also serve as a basis for establishing relationships between the O&G contamination in the refinery wastewater with the properties of the refined crude oils and the process operating conditions. The PLS model developed could be of great asset in both optimizing the existing and designing new refinery wastewater treatment units or reuse schemes. In order to find a possible treatment solution for the spent caustic problem, an on-site pilot plant experiments for NaOH recovery from the refinery kerosene caustic washing unit effluent using an alkaline-resistant nanofiltration (NF) polymeric membrane were performed in order to evaluate its applicability for treating these highly alkaline and contaminated streams. For a constant operating pressure and temperature and adequate operating conditions, 99.9% of oil and grease rejection and 97.7% of chemical oxygen demand (COD) rejection were observed. No noticeable membrane fouling or flux decrease were registered until a volume concentration factor of 3. These results allow for NF permeate reuse instead of fresh caustic and for significant reduction of the wastewater contamination, which can result in savings of 1.5 M€ per year at the current prices for the largest Portuguese oil refinery. The capital investments needed for implementation of the required NF membrane system are less than 10% of those associated with the traditional wet air oxidation solution of the spent caustic problem. The operating costs are very similar, but can be less than half if reusing the NF concentrate in refinery pH control applications. The payback period was estimated to be 1.1 years. Overall, the pilot plant experimental results obtained and the process economic evaluation data indicate a very competitive solution through the proposed NF treatment process, which represents a highly promising alternative to conventional and existing spent caustic treatment units.
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Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.
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Nowadays, a significant number of banks in Portugal are facing a bank-branch restructuring problem, and Millennium BCP is not an exception. The closure of branches is a major component of profit maximization through the reduction in operational and personnel costs but also an opportunity to approach the idea of “baking of future” and start thinking on the benefits of the digital era. This dissertation centers on a current high-impact organizational problem addressed by the company and consists in a proposal of optimization to the model that Millennium BCP uses. Even though measures of performance are usually considered the most important elements in evaluating the viability of branches, there is evidence suggesting that other general factors can be important to assess branch potential, such as the influx on branches, business dimensions of a branch and its location, which will be addressed in this project.
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This study is specifically concerned with the effect of the Enterprise Resource Planning (ERP) on the Business Process Redesign (BPR). Researcher’s experience and the investigation on previous researches imply that BPR and ERP are deeply related to each other and a study to found the mentioned relation further is necessary. In order to elaborate the hypothesis, a case study, in particular Turkish electricity distribution market and the phase of privatization are investigated. Eight companies that have taken part in privatization process and executed BPR serve as cases in this study. During the research, the cases are evaluated through critical success factors on both BPR and ERP. It was seen that combining the ERP Solution features with business processes lead the companies to be successful in ERP and BPR implementation. When the companies’ success and efficiency were compared before and after the ERP implementation, a considerable change was observed in organizational structure. It was spotted that the team composition is important in the success of ERP projects. Additionally, when the ERP is in driver or enabler role, the companies can be considered successful. On the contrary, when the ERP has a neutral role of business processes, the project fails. In conclusion, it can be said that the companies, which have implemented the ERP successfully, have accomplished the goals of the BPR.
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Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.
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This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.
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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores
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Correlations between the elliptic or triangular flow coefficients vm (m=2 or 3) and other flow harmonics vn (n=2 to 5) are measured using sNN−−−−√=2.76 TeV Pb+Pb collision data collected in 2010 by the ATLAS experiment at the LHC, corresponding to an integrated lumonisity of 7 μb−1. The vm-vn correlations are measured in midrapidity as a function of centrality, and, for events within the same centrality interval, as a function of event ellipticity or triangularity defined in a forward rapidity region. For events within the same centrality interval, v3 is found to be anticorrelated with v2 and this anticorrelation is consistent with similar anticorrelations between the corresponding eccentricities ϵ2 and ϵ3. On the other hand, it is observed that v4 increases strongly with v2, and v5 increases strongly with both v2 and v3. The trend and strength of the vm-vn correlations for n=4 and 5 are found to disagree with ϵm-ϵn correlations predicted by initial-geometry models. Instead, these correlations are found to be consistent with the combined effects of a linear contribution to vn and a nonlinear term that is a function of v22 or of v2v3, as predicted by hydrodynamic models. A simple two-component fit is used to separate these two contributions. The extracted linear and nonlinear contributions to v4 and v5 are found to be consistent with previously measured event-plane correlations.
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Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.
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[Excerpt] Bioethanol from lignocellulosic materials (LCM), also called second generation bioethanol, is considered a promising alternative to first generation bioethanol. An efficient production process of lignocellulosic bioethanol involves an effective pretreatment of LCM to improve the accessibility of cellulose and thus enhance the enzymatic saccharification. One interesting approach is to use the whole slurry from treatment, since allows economical and industrial benefits: washing steps are avoided, water consumption is lower and the sugars from liquid phase can be used, increasing ethanol concentration [1]. However, during the pretreatment step some compounds (such as furans, phenolic compounds and weak acids) are produced. These compounds have an inhibitory effect on the microorganisms used for hydrolysate fermentation [2]. To overcome this, the use of a robust industrial strain together with agro-industrial by-products as nutritional supplementation was proposed to increase the ethanol productivities and yields. (...)
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Fluorescence in situ hybridization (FISH) is a molecular technique widely used for the detection and characterization of microbial populations. FISH is affected by a wide variety of abiotic and biotic variables and the way they interact with each other. This is translated into a wide variability of FISH procedures found in the literature. The aim of this work is to systematically study the effects of pH, dextran sulfate and probe concentration in the FISH protocol, using a general peptide nucleic acid (PNA) probe for the Eubacteria domain. For this, response surface methodology was used to optimize these 3 PNA-FISH parameters for Gram-negative (Escherichia coli and Pseudomonas fluorescens) and Gram-positive species (Listeria innocua, Staphylococcus epidermidis and Bacillus cereus). The obtained results show that a probe concentration higher than 300 nM is favorable for both groups. Interestingly, a clear distinction between the two groups regarding the optimal pH and dextran sulfate concentration was found: a high pH (approx. 10), combined with lower dextran sulfate concentration (approx. 2% [w/v]) for Gram-negative species and near-neutral pH (approx. 8), together with higher dextran sulfate concentrations (approx. 10% [w/v]) for Gram-positive species. This behavior seems to result from an interplay between pH and dextran sulfate and their ability to influence probe concentration and diffusion towards the rRNA target. This study shows that, for an optimum hybridization protocol, dextran sulfate and pH should be adjusted according to the target bacteria.
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It has been reported that growth hormone may benefit selected patients with congestive heart failure. A 63-year-old man with refractory congestive heart failure waiting for heart transplantation, depending on intravenous drugs (dobutamine) and presenting with progressive worsening of the clinical status and cachexia, despite standard treatment, received growth hormone replacement (8 units per day) for optimization of congestive heart failure management. Increase in both serum growth hormone levels (from 0.3 to 0.8 mg/l) and serum IGF-1 levels (from 130 to 300ng/ml) was noted, in association with clinical status improvement, better optimization of heart failure treatment and discontinuation of dobutamine infusion. Left ventricular ejection fraction (by MUGA) increased from 13 % to 18 % and to 28 % later, in association with reduction of pulmonary pressures and increase in exercise capacity (rise in peak VO2 to 13.4 and to 16.2ml/kg/min later). The patient was "de-listed" for heart transplantation. Growth hormone may benefit selected patients with refractory heart failure.
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El presente estudio pretende arribar a la construcción de un modelo explicativo del comportamiento político a partir de la contribución que los marcos sociales (norma sociales, normas de ciudadanía, ideología, confianza política) y sociocognitivos (inteligencia afectiva, interés político, eficacia política, conocimiento político, sentimiento de comunidad) mostraron, en términos de relaciones entre las variables, sobre el mismo. Nuestra atención se centra no sólo al comportamiento político de la ciudadanía -que es donde se desarrollaron la mayor parte de los estudios-, sino a las elites de poder constitutivas del sistema político (jueces, legisladores provinciales y representantes de instituciones del gobierno y de organismos no gubernamentales). Asimismo, pretende establecer las diferencias que puedan evidenciarse en torno a la relación de estas variables con el comportamiento político entre los distintos colectivos estudiados en el ámbito de la ciudad de Córdoba. Para ello se realizara una primera etapa de estudio instrumental, con el objeto de analizar las propiedades psicométricas de los instrumentos a utilizar en la operacionalización de las variables. Para ello se tomara una muestra accidental de 250 personas entre 18 y 65 años de edad. Posteriormente, se realizarán dos etapas de estudio ex post facto, con la finalidad de construir los modelos planteados. En la primera de ellas, se trabajará con una muestra accidental de 100 representantes de los grupos de poder estudiados y en la segunda con una muestra probabilística de 500 ciudadanos cordobeses entre 18 y 65 años de edad.
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El objetivo general de este proyecto es el estudio de distintos tipos de sistemas organizados, conocer los factores que determinan la forma de organización y las consecuencias que ésta tiene sobre la reactividad de moléculas que se encuentran en ese entorno organizado. Se pretende realizar, desde la fisicoquímica y la síntesis orgánica, aportes a áreas multidisciplinarias como la nanociencia y la nanotecnología. Se sintetizarán ciclodextrinas anfifílicas y se estudiará su comportamiento en solución y en interfases, sus propiedades de agregación y morfología. Se estudiará también la termodinámica de los procesos y la capacidad catalítica de estas ciclodextrinas anfifílicas en superficies bidimensionales en reacciones de hidrólisis de ésteres. Las ciclodextrinas anfifílicas sintetizadas en el laboratorio se utilizarán también en mezclas con otros surfactantes, con el objetivo de generar medios eficientes respecto a la solubilización y extracción de contaminantes orgánicos desde suelos. Se espera encontrar sistemas que presenten efectos sinérgicos. Se determinará el efecto de la formación de complejos con ciclodextrina sobre las propiedades fisicoquímicas y la reactividad de pesticidas de amplio uso en agricultura, en particular de compuestos organofosforados. Se investigarán ciclodextrinas que permitan controlar la liberación del agroquímico y se realizarán estudios de la reactividad de los pesticidas en solución y en medios que simulen el suelo determinando si la inclusión en las ciclodextrinas modifica la velocidad de descomposición. En la búsqueda de nuevos sistemas microheterogéneos se sintetizarán surfactantes gémini con una cadena hidrocarbonada y una perfluorada y se determinarán sus propiedades. Luego de su caracterización, estos surfactantes se aplicarán en estudios de reactividad de compuestos insolubles en agua.Se estudiará la formación de complejos de ciclodextrina con metales de transición y los mismos se utilizarán como catalizadores en reacciones de oxidación de sulfuros y de alquenos en medios acuosos y no acuosos buscando condiciones donde se logre inducción quiral. Se sintetizarán compuestos azufrados polifuncionales con los cuales se modificarán superficies de nanopartículas por quimioadsorción de los mismos. Dado que se pretende obtener compuestos con propiedades específicas que dependen de su estructura, se llevará a cabo el modelado computacional de las distintas moléculas en estudio, ya que esto podría aportar datos relevantes acerca de qué modificaciones estructurales podrían intensificar la propiedad o propiedades buscadas. En una etapa posterior se correlacionarán las propiedades predichas a través de cálculos teóricos con las observadas experimentalmente, lo que intrínsecamente conlleva a un mayor conocimiento del sistema.Los estudios propuestos en este proyecto permitirán avanzar en la comprensión de los factores supramoleculares que controlan y modulan la interacción de ligandos con sus receptores en interfases y la ocurrencia de reacciones hidrolíticas en interfases autoorganizadas.