915 resultados para optimization of electrochemical properties


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An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included.

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The evolution of water content on a sandy soil during the sprinkler irrigation campaign, in the summer of 2010, of a field of sugar beet crop located at Valladolid (Spain) is assessed by a capacitive FDR (Frequency Domain Reflectometry) EnviroScan. This field is one of the experimental sites of the Spanish research center for the sugar beet development (AIMCRA). The objective of the work focus on monitoring the soil water content evolution of consecutive irrigations during the second two weeks of July (from the 12th to the 28th). These measurements will be used to simulate water movement by means of Hydrus-2D. The water probe logged water content readings (m3/m3) at 10, 20, 40 and 60 cm depth every 30 minutes. The probe was placed between two rows in one of the typical 12 x 15 m sprinkler irrigation framework. Furthermore, a texture analysis at the soil profile was also conducted. The irrigation frequency in this farm was set by the own personal farmer 0 s criteria that aiming to minimizing electricity pumping costs, used to irrigate at night and during the weekend i.e. longer irrigation frequency than expected. However, the high evapotranspiration rates and the weekly sugar beet water consumption—up to 50mm/week—clearly determined the need for lower this frequency. Moreover, farmer used to irrigate for six or five hours whilst results from the EnviroScan probe showed the soil profile reaching saturation point after the first three hours. It must be noted that AIMCRA provides to his members with a SMS service regarding weekly sugar beet water requirement; from the use of different meteorological stations and evapotranspiration pans, farmers have an idea of the weekly irrigation needs. Nevertheless, it is the farmer 0 s decision to decide how to irrigate. Thus, in order to minimize water stress and pumping costs, a suitable irrigation time and irrigation frequency was modeled with Hydrus-2D. Results for the period above mentioned showed values of water content ranging from 35 and 30 (m3/m3) for the first 10 and 20cm profile depth (two hours after irrigation) to the minimum 14 and 13 (m3/m3) ( two hours before irrigation). For the 40 and 60 cm profile depth, water content moves steadily across the dates: The greater the root activity the greater the water content variation. According to the results in the EnviroScan probe and the modeling in Hydrus-2D, shorter frequencies and irrigation times are suggested.

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Profiting by the increasing availability of laser sources delivering intensities above 109 W/cm2 with pulse energies in the range of several Joules and pulse widths in the range of nanoseconds, laser shock processing (LSP) is being consolidating as an effective technology for the improvement of surface mechanical and corrosion resistance properties of metals and is being developed as a practical process amenable to production engineering. The main acknowledged advantage of the laser shock processing technique consists on its capability of inducing a relatively deep compression residual stresses field into metallic alloy pieces allowing an improved mechanical behaviour, explicitly, the life improvement of the treated specimens against wear, crack growth and stress corrosion cracking. Following a short description of the theoretical/computational and experimental methods developed by the authors for the predictive assessment and experimental implementation of LSP treatments, experimental results on the residual stress profiles and associated surface properties modification successfully reached in typical materials (specifically Al and Ti alloys) under different LSP irradiation conditions are presented. In particular, the analysis of the residual stress profiles obtained under different irradiation parameters and the evaluation of the corresponding induced surface properties as roughness and wear resistance are presented.

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Profiting by the increasing availability of laser sources delivering intensities above 10 9 W/cm 2 with pulse energies in the range of several Joules and pulse widths in the range of nanoseconds, laser shock processing (LSP) is being consolidating as an effective technology for the improvement of surface mechanical and corrosion resistance properties of metals and is being developed as a practical process amenable to production engineering. The main acknowledged advantage of the laser shock processing technique consists on its capability of inducing a relatively deep compression residual stresses field into metallic alloy pieces allowing an improved mechanical behaviour, explicitly, the life improvement of the treated specimens against wear, crack growth and stress corrosion cracking. Following a short description of the theoretical/computational and experimental methods developed by the authors for the predictive assessment and experimental implementation of LSP treatments, experimental results on the residual stress profiles and associated surface properties modification successfully reached in typical materials (specifically steels and Al and Ti alloys) under different LSP irradiation conditions are presented

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The propagation losses (PL) of lithium niobate optical planar waveguides fabricated by swift heavy-ion irradiation (SHI), an alternative to conventional ion implantation, have been investigated and optimized. For waveguide fabrication, congruently melting LiNbO3 substrates were irradiated with F ions at 20 MeV or 30 MeV and fluences in the range 1013–1014 cm−2. The influence of the temperature and time of post-irradiation annealing treatments has been systematically studied. Optimum propagation losses lower than 0.5 dB/cm have been obtained for both TE and TM modes, after a two-stage annealing treatment at 350 and 375∘C. Possible loss mechanisms are discussed.

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One of the key steps to achieve high efficiencies in amorphous/crystalline silicon photovoltaic structures is to design low-ohmic-resistance backcontacts with good passivation in the rear part of the cell. A well known approach to achieve this goal is to use laser-fired contact (LFC) processes in which a metal layer is fired through the dielectric to define good contacts with the semiconductor. However, and despite the fact that this approach has demonstrated to be extremely successful, there is still enough room for process improvement with an appropriate optimization. In this paper, a study focused on the optimal adjustment of the irradiation parameters to produce laser-fired contacts in a-Si:H/c-Si heterojunctionsolarcells is presented. We used samples consisting of crystalline-silicon (c-Si) wafers together with a passivation layer of intrinsic hydrogenated amorphous silicon (a-Si:H(i)) deposited by plasma-enhanced chemical deposition (PECVD). Then, an aluminum layer was evaporated on both sides, the thickness of this layer varied from 0.2 to 1 μm in order to identify the optimal amount of Al required to create an appropriate contact. A q-switched Nd:YVO4laser source, λ = 532 nm, was used to locally fire the aluminum through the thin a-Si:H(i)-layers to form the LFC. The effects of laser fluences were analyzed using a comprehensive morphological and electrical characterization.

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European cities are essential in the development of Europe as they constitute the living environment of more than 60% of the population in the European Union and are drivers of the European economy – just under 85% of the EU’s gross domestic product is produced in urban areas (EC, 2007a). The car has been one of the main factors of development during the 20th century, but it is at the same time the origin of the key problems cities have to face: traffic increase. This has resulted in chronic congestion with many adverse consequences such as air pollution and noise. This loss of environmental quality is one of the reasons for urban sprawl in European cities during recent decades. But this urban sprawl at the same time worsens the environmental conditions. We must return to the dense city, but clean and competitive, and this implies reducing car use yet provides quality transport alternatives sufficient to recover and maintain the competitiveness of cities (EC, 2007a). Consequently, European cities need to establish an urban transport strategy which helps reduce their environmental problems –mainly emissions and noise – but without decreasing their trip attraction. This aspect is very important because a loss of trip attraction would result in an increase of people moving to more disperse areas, contributing towards worsening the current situation. This thesis is an attempt to contribute solutions to this problem in two ways: 1) The first is to analyze the complementarity and possible synergies of several urban transport measures aimed at improving a modal split to a more sustainable means of transport. This analysis will focus on the three aspects already mentioned: emissions, noise and attractiveness or competitiveness. 2) Once possible synergies and complementarities have been analyzed, the second objective is to propose the best combination of these measures, in terms of level of implementation, to achieve the maximum benefit with respect to the three aspects previously established: emissions, noise and attractiveness or competitiveness. Therefore, within the wide range of measures enhancing sustainable urban transport, three of them have been be selected in this thesis to establish a methodology for achieving these objectives. The analysis will be based on the region of Madrid, which is also the case study selected for this research. Las ciudades europeas son piezas fundamentales para el desarrollo europeo, ya que son el lugar de residencia de más del 60% de la población de la unión europea así como los motores de su economía – casi el 85% del PIB europeo se produce en áreas urbanas (EC, 2007a). El coche ha sido uno de los principales motores de desarrollo de las ciudades durante el siglo XX, pero se ha terminado por convertir a su vez en uno de los principales problemas con los que tiene que lidiar las ciudades: el aumento del tráfico. Esto ha derivado en unos niveles crónicos de congestión, con multitud de efectos adversos, entre los que cabe destacar la contaminación del aire y el ruido. Esta pérdida de calidad ambiental es una de las razones que ha propiciado la dispersión urbana que han experimentado las ciudades europeas en las últimas décadas. Pero esta dispersión urbana a su vez contribuye a empeorar las condiciones ambientales de las ciudades. Debemos retornar a la ciudad densa, pero limpia y competitiva, y esto implica reducir el uso del coche, pero proporcionando alternativas de transporte que permitan recuperar y mantener la competitividad de las ciudades (EC, 2007a). Por lo tanto, las ciudades europeas necesitan encontrar una estrategia de transporte urbano que ayude a reducir sus problemas medio ambientales – principalmente ruido y emisiones – pero sin hacerlas perder atractividad o competitividad. Este aspecto tiene gran importancia porque una pérdida de la misma se traduciría en un aumento de dispersión de la población hacia áreas periféricas, contribuyendo a empeorar la situación actual. Esta tesis contribuye a solucionar este problema de dos maneras: 1) La primera, analizando la complementariedad y posibles sinergias de diferentes medidas de transporte urbano orientadas a promover un reparto modal hacia modos más sostenibles. Este análisis se centrará en los tres aspectos anteriormente citados: emisiones, ruido y atractividad o competitividad. 2) Una vez las posibles sinergias y complementariedades se han analizado, el segundo objetivo es proponer la mejor combinación de estas medidas – en términos de grado de aplicación - para lograr el máximo beneficio en lo que respecta a los tres objetivos previamente establecidos. Para ello, en esta tesis se han seleccionado una serie de medidas que permitan establecer una metodología para alcanzar estos objetivos previamente definidos. El análisis se centra en la ciudad de Madrid y su área metropolitana, la cual se ha escogido como caso de estudio para realizar esta investigación.

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Competitive abstract machines for Prolog are usually large, intricate, and incorpórate sophisticated optimizations. This makes them difñcult to code, optimize, and, especially, maintain and extend. This is partly due to the fact that efñciency considerations make it necessary to use low-level languages in their implementation. Writing the abstract machine (and ancillary code) in a higher-level language can help harness this inherent complexity. In this paper we show how the semantics of basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog which retains much of its semantics. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog the abstract machine descriptions can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of highly-tuned, hand-crafted emulators.

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Abstract is not available.

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Dynamic scheduling increases the expressive power of logic programming languages, but also introduces some overhead. In this paper we present two classes of program transformations designed to reduce this additional overhead, while preserving the operational semantics of the original programs, modulo ordering of literals woken at the same time. The first class of transformations simplifies the delay conditions while the second class moves delayed literals later in the rule body. Application of the program transformations can be automated using information provided by compile-time analysis. We provide experimental results obtained from an implementation of the proposed techniques using the CIAO prototype compiler. Our results show that the techniques can lead to substantial performance improvement.

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In this report we discuss some of the issues involved in the specialization and optimization of constraint logic programs with dynamic scheduling. Dynamic scheduling, as any other form of concurrency, increases the expressive power of constraint logic programs, but also introduces run-time overhead. The objective of the specialization and optimization is to reduce as much as possible such overhead automatically, while preserving the semantics of the original programs. This is done by program transformation based on global analysis. We present implementation techniques for this purpose and report on experimental results obtained from an implementation of the techniques in the context of the CIAO compiler.

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Fundamental research and modelling in plasma atomic physics continue to be essential for providing basic understanding of many different topics relevant to high-energy-density plasmas. The Atomic Physics Group at the Institute of Nuclear Fusion has accumulated experience over the years in developing a collection of computational models and tools for determining the atomic energy structure, ionization balance and radiative properties of, mainly, inertial fusion and laser-produced plasmas in a variety of conditions. In this work, we discuss some of the latest advances and results of our research, with emphasis on inertial fusion and laboratory-astrophysical applications.

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In previous works we demonstrated the benefits of using micro–nano patterning materials to be used as bio-photonic sensing cells (BICELLs), referred as micro–nano photonic structures having immobilized bioreceptors on its surface with the capability of recognizing the molecular binding by optical transduction. Gestrinone/anti-gestrinone and BSA/anti-BSA pairs were proven under different optical configurations to experimentally validate the biosensing capability of these bio-sensitive photonic architectures. Moreover, Three-Dimensional Finite Difference Time Domain (FDTD) models were employed for simulating the optical response of these structures. For this article, we have developed an effective analytical simulation methodology capable of simulating complex biophotonic sensing architectures. This simulation method has been tested and compared with previous experimental results and FDTD models. Moreover, this effective simulation methodology can be used for efficiently design and optimize any structure as BICELL. In particular for this article, six different BICELL's types have been optimized. To carry out this optimization we have considered three figures of merit: optical sensitivity, Q-factor and signal amplitude. The final objective of this paper is not only validating a suitable and efficient optical simulation methodology but also demonstrating the capability of this method for analyzing the performance of a given number of BICELLs for label-free biosensing.

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An aerodynamic optimization of the ICE 2 high-speed train nose in term of front wind action sensitivity is carried out in this paper. The nose is parametrically defined by Be?zier Curves, and a three-dimensional representation of the nose is obtained using thirty one design variables. This implies a more complete parametrization, allowing the representation of a real model. In order to perform this study a genetic algorithm (GA) is used. Using a GA involves a large number of evaluations before finding such optimal. Hence it is proposed the use of metamodels or surrogate models to replace Navier-Stokes solver and speed up the optimization process. Adaptive sampling is considered to optimize surrogate model fitting and minimize computational cost when dealing with a very large number of design parameters. The paper introduces the feasi- bility of using GA in combination with metamodels for real high-speed train geometry optimization.