17 resultados para vector optimization
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227 págs.
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The aim of this technical report is to present some detailed explanations in order to help to understand and use the Message Passing Interface (MPI) parallel programming for solving several mixed integer optimization problems. We have developed a C++ experimental code that uses the IBM ILOG CPLEX optimizer within the COmputational INfrastructure for Operations Research (COIN-OR) and MPI parallel computing for solving the optimization models under UNIX-like systems. The computational experience illustrates how can we solve 44 optimization problems which are asymmetric with respect to the number of integer and continuous variables and the number of constraints. We also report a comparative with the speedup and efficiency of several strategies implemented for some available number of threads.
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In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.
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In this paper, the influence on corrugation of the most significant track parameters has been examined. After this parametric study, the optimization of the track parameters to minimize the undulatory wear growth has been achieved. Finally, the influence of the dispersion of the track and contact parameters on corrugation growth has been studied. A method has been developed to obtain an optimal solution of the track parameters which minimizes corrugation growth, thus ensuring that this solution remains optimum despite dispersion of track parameters and wheel-rail contact uncertainties. This work is based on the computer application RACING (RAil Corrugation INitiation and Growth) which has been developed by the authors to predict rail corrugation features.
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We present a scheme to generate clusters submodels with stage ordering from a (symmetric or a nonsymmetric one) multistage stochastic mixed integer optimization model using break stage. We consider a stochastic model in compact representation and MPS format with a known scenario tree. The cluster submodels are built by storing first the 0-1 the variables, stage by stage, and then the continuous ones, also stage by stage. A C++ experimental code has been implemented for reordering the stochastic model as well as the cluster decomposition after the relaxation of the non-anticipativiy constraints until the so-called breakstage. The computational experience shows better performance of the stage ordering in terms of elapsed time in a randomly generated testbed of multistage stochastic mixed integer problems.
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[ES]En las sociedades modernas existe una creciente preocupación por el aumento de la incidencia de la enfermedad renal crónica. Debido a la deficiencia de donantes de órganos y al elevado coste del tratamiento de diálisis, existe la necesidad de desarrollar nuevos tratamientos para estos pacientes. La medicina regenerativa basada en la aplicación de células iPS es una opción prometedora para el tratamiento de esta enfermedad. Sin embargo, la falta de conocimientos sobre el estado pluripotencial de las células y sobre su proceso de diferenciación, así como las limitaciones derivadas del propio procedimiento de reprogramación, impiden su aplicación clínica en un futuro inmediato. Para que se convierta en realidad, numerosas investigaciones se están llevando a cabo con el objetivo de mejorar el procedimiento y hacerlo adecuado para su aplicación clínica. En este trabajo se propone un método que permitiría obtener células iPS a partir de células mesangiales mediante la transfección con un vector no integrativo, el virus Sendai, portador de los genes Oct3/4, Sox2, Klf4 y c-Myc. Al tratarse de un vector no integrativo, se minimizaría el efecto del proceso de reprogramación sobre la estabilidad del genoma celular. Además, en este proyecto se estudiará la capacidad de las células iPS obtenidas para diferenciarse en células progenitoras de podocitos que puedan ser aplicadas específicamente en terapias regenerativas para enfermos renales crónicos.
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This study developed a framework for the shape optimization of aerodynamics profiles using computational fluid dynamics (CFD) and genetic algorithms. Agenetic algorithm code and a commercial CFD code were integrated to develop a CFD shape optimization tool. The results obtained demonstrated the effectiveness of the developed tool. The shape optimization of airfoils was studied using different strategies to demonstrate the capacity of this tool with different GA parameter combinations.
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The optimization of solution-processed organic bulk-heterojunction solar cells with the acceptor-substituted quinquethiophene DCV5T-Bu-4 as donor in conjunction with PC61BM as acceptor is described. Power conversion efficiencies up to 3.0% and external quantum efficiencies up to 40% were obtained through the use of 1-chloronaphthalene as solvent additive in the fabrication of the photovoltaic devices. Furthermore, atomic force microscopy investigations of the photoactive layer gave insight into the distribution of donor and acceptor within the blend. The unique combination of solubility and thermal stability of DCV5T-Bu-4 also allows for fabrication of organic solar cells by vacuum deposition. Thus, we were able to perform a rare comparison of the device characteristics of the solution-processed DCV5T-Bu-4:PC61BM solar cell with its vacuum-processed DCV5T-Bu-4:C-60 counterpart. Interestingly in this case, the efficiencies of the small-molecule organic solar cells prepared by using solution techniques are approaching those fabricated by using vacuum technology. This result is significant as vacuum-processed devices typically display much better performances in photovoltaic cells. Keywords
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Modern wind turbines are designed in order to work in variable speed opera-tions. To perform this task, these turbines are provided with adjustable speed generators, like the double feed induction generator (DFIG). One of the main advantages of adjustable speed generators is improving the system efficiency compared with _xed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However, this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. The proposed design also uses the vector oriented control theory in order to simplify the DFIG dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and pa-rameter uncertainties using the Lyapunov stability theory. Finally, the simulated results show on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, which usually appear in real systems.
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[EN] This PhD work started in March 2010 with the support of the University of the Basque Country (UPV/EHU) under the program named “Formación de Personal Investigador” at the Chemical and Environmental Engineering Department in the Faculty of Engineering of Bilbao. The major part of the Thesis work was carried out in the mentioned department, as a member of the Sustainable Process Engineering (SuPrEn) research group. In addition, this PhD Thesis includes the research work developed during a period of 6 months at the Institut für Mikrotechnik Mainz GmbH, IMM, in Germany. During the four years of the Thesis, conventional and microreactor systems were tested for several feedstocks renewable and non-renewable, gases and liquids through several reforming processes in order to produce hydrogen. For this purpose, new catalytic formulations which showed high activity, selectivity and stability were design. As a consequence, the PhD work performed allowed the publication of seven scientific articles in peer-reviewed journals. This PhD Thesis is divided into the following six chapters described below. The opportunity of this work is established on the basis of the transition period needed for moving from a petroleum based energy system to a renewable based new one. Consequently, the present global energy scenario was detailed in Chapter 1, and the role of hydrogen as a real alternative in the future energy system was justified based on several outlooks. Therefore, renewable and non-renewable hydrogen production routes were presented, explaining the corresponding benefits and drawbacks. Then, the raw materials used in this Thesis work were described and the most important issues regarding the processes and the characteristics of the catalytic formulations were explained. The introduction chapter finishes by introducing the concepts of decentralized production and process intensification with the use of microreactors. In addition, a small description of these innovative reaction systems and the benefits that entailed their use were also mentioned. In Chapter 2 the main objectives of this Thesis work are summarized. The development of advanced reaction systems for hydrogen rich mixtures production is the main objective. In addition, the use and comparison between two different reaction systems, (fixed bed reactor (FBR) and microreactor), the processing of renewable raw materials, the development of new, active, selective and stable catalytic formulations, and the optimization of the operating conditions were also established as additional partial objectives. Methane and natural gas (NG) steam reforming experimental results obtained when operated with microreactor and FBR systems are presented in Chapter 3. For these experiments nickel-based (Ni/Al2O3 and Ni/MgO) and noble metal-based (Pd/Al2O3 and Pt/Al2O3) catalysts were prepared by wet impregnation and their catalytic activity was measured at several temperatures, from 973 to 1073 K, different S/C ratios, from 1.0 to 2.0, and atmospheric pressure. The Weight Hourly Space Velocity (WHSV) was maintained constant in order to compare the catalytic activity in both reaction systems. The results obtained showed a better performance of the catalysts operating in microreactors. The Ni/MgO catalyst reached the highest hydrogen production yield at 1073 K and steam-to-carbon ratio (S/C) of 1.5 under Steam methane Reforming (SMR) conditions. In addition, this catalyst also showed good activity and stability under NG reforming at S/C=1.0 and 2.0. The Ni/Al2O3 catalyst also showed high activity and good stability and it was the catalyst reaching the highest methane conversion (72.9 %) and H2out/CH4in ratio (2.4) under SMR conditions at 1073 K and S/C=1.0. However, this catalyst suffered from deactivation when it was tested under NG reforming conditions. Regarding the activity measurements carried out with the noble metal-based catalysts in the microreactor systems, they suffered a very quick deactivation, probably because of the effects attributed to carbon deposition, which was detected by Scanning Electron Microscope (SEM). When the FBR was used no catalytic activity was measured with the catalysts under investigation, probably because they were operated at the same WHSV than the microreactors and these WHSVs were too high for FBR system. In Chapter 4 biogas reforming processes were studied. This chapter starts with an introduction explaining the properties of the biogas and the main production routes. Then, the experimental procedure carried out is detailed giving concrete information about the experimental set-up, defining the parameters measured, specifying the characteristics of the reactors used and describing the characterization techniques utilized. Each following section describes the results obtained from activity testing with the different catalysts prepared, which is subsequently summarized: Section 4.3: Biogas reforming processes using γ-Al2O3 based catalysts The activity results obtained by several Ni-based catalysts and a bimetallic Rh-Ni catalyst supported on magnesia or alumina modified with oxides like CeO2 and ZrO2 are presented in this section. In addition, an alumina-based commercial catalyst was tested in order to compare the activity results measured. Four different biogas reforming processes were studied using a FBR: dry reforming (DR), biogas steam reforming (BSR), biogas oxidative reforming (BOR) and tri-reforming (TR). For the BSR process different steam to carbon ratios (S/C) from 1.0 to 3.0, were tested. In the case of BOR process the oxygen-to-methane (O2/CH4) ratio was varied from 0.125 to 0.50. Finally, for TR processes different S/C ratios from 1.0 to 3.0, and O2/CH4 ratios of 0.25 and 0.50 were studied. Then, the catalysts which achieved high activity and stability were impregnated in a microreactor to explore the viability of process intensification. The operation with microreactors was carried out under the best experimental conditions measured in the FBR. In addition, the physicochemical characterization of the fresh and spent catalysts was carried out by Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), N2 physisorption, H2 chemisorption, Temperature Programmed Reduction (TPR), SEM, X-ray Photoelectron Spectroscopy (XPS) and X-ray powder Diffraction (XRD). Operating with the FBR, conversions close to the ones predicted by thermodynamic calculations were obtained by most of the catalysts tested. The Rh-Ni/Ce-Al2O3 catalyst obtained the highest hydrogen production yield in DR. In BSR process, the Ni/Ce-Al2O3 catalyst achieved the best activity results operating at S/C=1.0. In the case of BOR process, the Ni/Ce-Zr-Al2O3 catalyst showed the highest reactants conversion values operating at O2/CH4=0.25. Finally, in the TR process the Rh-Ni/Ce-Al2O3 catalyst obtained the best results operating at S/C=1.0 and O2/CH4=0.25. Therefore, these three catalysts were selected to be coated onto microchannels in order to test its performance under BOR and TR processes conditions. Although the operation using microreactors was carried out under considerably higher WHSV, similar conversions and yields as the ones measured in FBR were measured. Furthermore, attending to other measurements like Turnover Frequency (TOF) and Hydrogen Productivity (PROD), the values calculated for the catalysts tested in microreactors were one order of magnitude higher. Thus, due to the low dispersion degree measured by H2-chemisorption, the Ni/Ce-Al2O3 catalyst reached the highest TOF and PROD values. Section 4.4: Biogas reforming processes using Zeolites L based catalysts In this section three type of L zeolites, with different morphology and size, were synthesized and used as catalyst support. Then, for each type of L zeolite three nickel monometallic and their homologous Rh-Ni bimetallic catalysts were prepared by the wetness impregnation method. These catalysts were tested using the FBR under DR process and different conditions of BSR (S/C ratio of 1.0 and 2.0), BOR (O2/CH4 ratio of 0.25 and 0.50) and TR processes (at S/C=1.0 and O2/CH4=0.25). The characterization of these catalysts was also carried out by using the same techniques mentioned in the previous section. Very high methane and carbon dioxide conversion values were measured for almost all the catalysts under investigation. The experimental results evidenced the better catalytic behavior of the bimetallic catalysts as compared to the monometallic ones. Comparing the catalysts behavior with regards to their morphology, for the BSR process the Disc catalysts were the most active ones at the lowest S/C ratio tested. On the contrary, the Cylindrical (30–60 nm) catalysts were more active under BOR conditions at O2/CH4=0.25 and TR processes. By the contrary, the Cylindrical (1–3 µm) catalysts showed the worst activity results for both processes. Section 4.5: Biogas reforming processes using Na+ and Cs+ doped Zeolites LTL based catalysts A method for the synthesis of Linde Type L (LTL) zeolite under microwave-assisted hydrothermal conditions and its behavior as a support for heterogeneously catalyzed hydrogen production is described in this section. Then, rhodium and nickel-based bimetallic catalysts were prepared in order to be tested by DR process and BOR process at O2/CH4=0.25. Moreover, the characterization of the catalysts under investigation was also carried out. Higher activities were achieved by the catalysts prepared from the non-doped zeolites, Rh-Ni/D and Rh-Ni/N, as compared to the ones supported on Na+ and Cs+ exchanged supports. However, the differences between them were not very significant. In addition, the Na+ and Cs+ incorporation affected mainly to the Disc catalysts. Comparing the results obtained by these catalysts with the ones studied in the section 4.4, in general worst results were achieved under DR conditions and almost the same results when operated under BOR conditions. In Chapter 5 the ethylene glycol (EG) as feed for syngas production by steam reforming (SR) and oxidative steam reforming (OSR) was studied by using microchannel reactors. The product composition was determined at a S/C of 4.0, reaction temperatures between 625°C and 725°C, atmospheric pressure and Volume Hourly Space Velocities (VHSV) between 100 and 300 NL/(gcath). This work was divided in two sections. The first one corresponds to the introduction of the main and most promising EG production routes. Then, the new experimental procedure is detailed and the information about the experimental set-up and the measured parameters is described. The characterization was carried out using the same techniques as for the previous chapter. Then, the next sections correspond to the catalytic activity and catalysts characterization results. Section 5.3: xRh-cm and xRh-np catalysts for ethylene glycol reforming Initially, catalysts with different rhodium loading, from 1.0 to 5.0 wt. %, and supported on α-Al2O3 were prepared by two different preparation methods (conventional impregnation and separate nanoparticle synthesis). Then, the catalysts were compared regarding their measured activity and selectivity, as well as the characterization results obtained before and after the activity tests carried out. The samples prepared by a conventional impregnation method showed generally higher activity compared to catalysts prepared from Rh nanoparticles. By-product formation of species such as acetaldehyde, ethane and ethylene was detected, regardless if oxygen was added to the feed or not. Among the catalysts tested, the 2.5Rh-cm catalyst was considered the best one. Section 5.4: 2.5Rh-cm catalyst support modification with CeO2 and La2O3 In this part of the Chapter 5, the catalyst showing the best performance in the previous section, the 2.5Rh-Al2O3 catalyst, was selected in order to be improved. Therefore, new Rh based catalysts were designed using α-Al2O3 and being modified this support with different contents of CeO2 or La2O3 oxides. All the catalysts containing additives showed complete conversion and selectivities close to the equilibrium in both SR and OSR processes. In addition, for these catalysts the concentrations measured for the C2H4, CH4, CH3CHO and C2H6 by-products were very low. Finally, the 2.5Rh-20Ce catalyst was selected according to its catalytic activity and characterization results in order to run a stability test, which lasted more than 115 hours under stable operation. The last chapter, Chapter 6, summarizes the main conclusions achieved throughout this Thesis work. Although very high reactant conversions and rich hydrogen mixtures were obtained using a fixed bed reaction system, the use of microreactors improves the key issues, heat and mass transfer limitations, through which the reforming reactions are intensified. Therefore, they seem to be a very interesting and promising alternative for process intensification and decentralized production for remote application.
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138 p.
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The main contribution of this work is to analyze and describe the state of the art performance as regards answer scoring systems from the SemEval- 2013 task, as well as to continue with the development of an answer scoring system (EHU-ALM) developed in the University of the Basque Country. On the overall this master thesis focuses on finding any possible configuration that lets improve the results in the SemEval dataset by using attribute engineering techniques in order to find optimal feature subsets, along with trying different hierarchical configurations in order to analyze its performance against the traditional one versus all approach. Altogether, throughout the work we propose two alternative strategies: on the one hand, to improve the EHU-ALM system without changing the architecture, and, on the other hand, to improve the system adapting it to an hierarchical con- figuration. To build such new models we describe and use distinct attribute engineering, data preprocessing, and machine learning techniques.