907 resultados para Computational implementations
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In this paper, a computational tool concerning the computation of flexural and fracture toughness of cement based composites is presented. Firstly, RILEM`s (Reunion Internationale des Laboratoires d`Essais de Materiaux) recommendations related to the analysis of FRC in three-point bend tests are discussed in their relevant aspects regarding the computational implementations. The determination of other mechanical properties such as the Young modulus has been added to the program. Taking this into account, a new formulation based on displacements is used. In the second part of the paper, the determination of fracture properties of concrete, such as the fracture energy, G(F) , and the fracture toughness, K-IC(S), is discussed regarding the computational strategies used in the implementations. Several features whereby anterior data can be reanalyzed, obtained from other standards and recommendations, have been incorporated into the program, therefore allowing comparative studies and back analysis activities.
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The main objective this article is describe a methodology for the calculation of the profile of the electric field in the level soil and proximities originated by electric energy transmission systems real and in operation in the country. It also is commented the equation used and your computational implementation in order to agile and to optimize the studies. The results of simulations were just presented for the transmission system in the voltage class 500 kV for simplify the understanding and space restriction in the article, very although five others types of configurations have also been used in the complete study with very voltages and respective classes. The results were animating and very nearby of values well-known of electric field of other and publications traditional in the area. The graphic exits of program for better visual comprehension and understanding went in accomplished in the plan and in the space © 2010 IEEE.
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This paper presents a new methodology for solving the optimal VAr planning problem in multi-area electric power systems, using the Dantzig-Wolfe decomposition. The original multi-area problem is decomposed into subproblems (one for each area) and a master problem (coordinator). The solution of the VAr planning problem in each area is based on the application of successive linear programming, and the coordination scheme is based on the reactive power marginal costs in the border bus. The aim of the model is to provide coordinated mechanisms to carry out the VAr planning studies maximizing autonomy and confidentiality for each area, assuring global economy to the whole system. Using the mathematical model and computational implementation of the proposed methodology, numerical results are presented for two interconnected systems, each of them composed of three equal subsystems formed by IEEE30 and IEEE118 test systems. © 2011 IEEE.
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This paper outlines the problems found in the parallelization of SPH (Smoothed Particle Hydrodynamics) algorithms using Graphics Processing Units. Different results of some parallel GPU implementations in terms of the speed-up and the scalability compared to the CPU sequential codes are shown. The most problematic stage in the GPU-SPH algorithms is the one responsible for locating neighboring particles and building the vectors where this information is stored, since these specific algorithms raise many dificulties for a data-level parallelization. Because of the fact that the neighbor location using linked lists does not show enough data-level parallelism, two new approaches have been pro- posed to minimize bank conflicts in the writing and subsequent reading of the neighbor lists. The first strategy proposes an efficient coordination between CPU-GPU, using GPU algorithms for those stages that allow a straight forward parallelization, and sequential CPU algorithms for those instructions that involve some kind of vector reduction. This coordination provides a relatively orderly reading of the neighbor lists in the interactions stage, achieving a speed-up factor of x47 in this stage. However, since the construction of the neighbor lists is quite expensive, it is achieved an overall speed-up of x41. The second strategy seeks to maximize the use of the GPU in the neighbor's location process by executing a specific vector sorting algorithm that allows some data-level parallelism. Al- though this strategy has succeeded in improving the speed-up on the stage of neighboring location, the global speed-up on the interactions stage falls, due to inefficient reading of the neighbor vectors. Some changes to these strategies are proposed, aimed at maximizing the computational load of the GPU and using the GPU texture-units, in order to reach the maximum speed-up for such codes. Different practical applications have been added to the mentioned GPU codes. First, the classical dam-break problem is studied. Second, the wave impact of the sloshing fluid contained in LNG vessel tanks is also simulated as a practical example of particle methods
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In this paper we will see how the efficiency of the MBS simulations can be improved in two different ways, by considering both an explicit and implicit semi-recursive formulation. The explicit method is based on a double velocity transformation that involves the solution of a redundant but compatible system of equations. The high computational cost of this operation has been drastically reduced by taking into account the sparsity pattern of the system. Regarding this, the goal of this method is the introduction of MA48, a high performance mathematical library provided by Harwell Subroutine Library. The second method proposed in this paper has the particularity that, depending on the case, between 70 and 85% of the computation time is devoted to the evaluation of forces derivatives with respect to the relative position and velocity vectors. Keeping in mind that evaluating these derivatives can be decomposed into concurrent tasks, the main goal of this paper lies on a successful and straightforward parallel implementation that have led to a substantial improvement with a speedup of 3.2 by keeping all the cores busy in a quad-core processor and distributing the workload between them, achieving on this way a huge time reduction by doing an ideal CPU usage
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This paper presents some brief considerations on the role of Computational Logic in the construction of Artificial Intelligence systems and in programming in general. It does not address how the many problems in AI can be solved but, rather more modestly, tries to point out some advantages of Computational Logic as a tool for the AI scientist in his quest. It addresses the interaction between declarative and procedural views of programs (deduction and action), the impact of the intrinsic limitations of logic, the relationship with other apparently competing computational paradigms, and finally discusses implementation-related issues, such as the efficiency of current implementations and their capability for efficiently exploiting existing and future sequential and parallel hardware. The purpose of the discussion is in no way to present Computational Logic as the unique overall vehicle for the development of intelligent systems (in the firm belief that such a panacea is yet to be found) but rather to stress its strengths in providing reasonable solutions to several aspects of the task.
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El futuro de la energía nuclear de fisión dependerá, entre otros factores, de la capacidad que las nuevas tecnologías demuestren para solventar los principales retos a largo plazo que se plantean. Los principales retos se pueden resumir en los siguientes aspectos: la capacidad de proporcionar una solución final, segura y fiable a los residuos radiactivos; así como dar solución a la limitación de recursos naturales necesarios para alimentar los reactores nucleares; y por último, una mejora robusta en la seguridad de las centrales que en definitiva evite cualquier daño potencial tanto en la población como en el medio ambiente como consecuencia de cualquier escenario imaginable o más allá de lo imaginable. Siguiendo estas motivaciones, la Generación IV de reactores nucleares surge con el compromiso de proporcionar electricidad de forma sostenible, segura, económica y evitando la proliferación de material fisible. Entre los sistemas conceptuales que se consideran para la Gen IV, los reactores rápidos destacan por su capacidad potencial de transmutar actínidos a la vez que permiten una utilización óptima de los recursos naturales. Entre los refrigerantes que se plantean, el sodio parece una de las soluciones más prometedoras. Como consecuencia, esta tesis surgió dentro del marco del proyecto europeo CP-ESFR con el principal objetivo de evaluar la física de núcleo y seguridad de los reactores rápidos refrigerados por sodio, al tiempo que se desarrollaron herramientas apropiadas para dichos análisis. Efectivamente, en una primera parte de la tesis, se abarca el estudio de la física del núcleo de un reactor rápido representativo, incluyendo el análisis detallado de la capacidad de transmutar actínidos minoritarios. Como resultado de dichos análisis, se publicó un artículo en la revista Annals of Nuclear Energy [96]. Por otra parte, a través de un análisis de un hipotético escenario nuclear español, se evalúo la disponibilidad de recursos naturales necesarios en el caso particular de España para alimentar una flota específica de reactores rápidos, siguiendo varios escenarios de demanda, y teniendo en cuenta la capacidad de reproducción de plutonio que tienen estos sistemas. Como resultado de este trabajo también surgió una publicación en otra revista científica de prestigio internacional como es Energy Conversion and Management [97]. Con objeto de realizar esos y otros análisis, se desarrollaron diversos modelos del núcleo del ESFR siguiendo varias configuraciones, y para diferentes códigos. Por otro lado, con objeto de poder realizar análisis de seguridad de reactores rápidos, son necesarias herramientas multidimensionales de alta fidelidad específicas para reactores rápidos. Dichas herramientas deben integrar fenómenos relacionados con la neutrónica y con la termo-hidráulica, entre otros, mediante una aproximación multi-física. Siguiendo este objetivo, se evalúo el código de difusión neutrónica ANDES para su aplicación a reactores rápidos. ANDES es un código de resolución nodal que se encuentra implementado dentro del sistema COBAYA3 y está basado en el método ACMFD. Por lo tanto, el método ACMFD fue sometido a una revisión en profundidad para evaluar su aptitud para la aplicación a reactores rápidos. Durante ese proceso, se identificaron determinadas limitaciones que se discutirán a lo largo de este trabajo, junto con los desarrollos que se han elaborado e implementado para la resolución de dichas dificultades. Por otra parte, se desarrolló satisfactoriamente el acomplamiento del código neutrónico ANDES con un código termo-hidráulico de subcanales llamado SUBCHANFLOW, desarrollado recientemente en el KIT. Como conclusión de esta parte, todos los desarrollos implementados son evaluados y verificados. En paralelo con esos desarrollos, se calcularon para el núcleo del ESFR las secciones eficaces en multigrupos homogeneizadas a nivel nodal, así como otros parámetros neutrónicos, mediante los códigos ERANOS, primero, y SERPENT, después. Dichos parámetros se utilizaron más adelante para realizar cálculos estacionarios con ANDES. Además, como consecuencia de la contribución de la UPM al paquete de seguridad del proyecto CP-ESFR, se calcularon mediante el código SERPENT los parámetros de cinética puntual que se necesitan introducir en los típicos códigos termo-hidráulicos de planta, para estudios de seguridad. En concreto, dichos parámetros sirvieron para el análisis del impacto que tienen los actínidos minoritarios en el comportamiento de transitorios. Concluyendo, la tesis presenta una aproximación sistemática y multidisciplinar aplicada al análisis de seguridad y comportamiento neutrónico de los reactores rápidos de sodio de la Gen-IV, usando herramientas de cálculo existentes y recién desarrolladas ad' hoc para tal aplicación. Se ha empleado una cantidad importante de tiempo en identificar limitaciones de los métodos nodales analíticos en su aplicación en multigrupos a reactores rápidos, y se proponen interesantes soluciones para abordarlas. ABSTRACT The future of nuclear reactors will depend, among other aspects, on the capability to solve the long-term challenges linked to this technology. These are the capability to provide a definite, safe and reliable solution to the nuclear wastes; the limitation of natural resources, needed to fuel the reactors; and last but not least, the improved safety, which would avoid any potential damage on the public and or environment as a consequence of any imaginable and beyond imaginable circumstance. Following these motivations, the IV Generation of nuclear reactors arises, with the aim to provide sustainable, safe, economic and proliferationresistant electricity. Among the systems considered for the Gen IV, fast reactors have a representative role thanks to their potential capacity to transmute actinides together with the optimal usage of natural resources, being the sodium fast reactors the most promising concept. As a consequence, this thesis was born in the framework of the CP-ESFR project with the generic aim of evaluating the core physics and safety of sodium fast reactors, as well as the development of the approppriated tools to perform such analyses. Indeed, in a first part of this thesis work, the main core physics of the representative sodium fast reactor are assessed, including a detailed analysis of the capability to transmute minor actinides. A part of the results obtained have been published in Annals of Nuclear Energy [96]. Moreover, by means of the analysis of a hypothetical Spanish nuclear scenario, the availability of natural resources required to deploy an specific fleet of fast reactor is assessed, taking into account the breeding properties of such systems. This work also led to a publication in Energy Conversion and Management [97]. In order to perform those and other analyses, several models of the ESFR core were created for different codes. On the other hand, in order to perform safety studies of sodium fast reactors, high fidelity multidimensional analysis tools for sodium fast reactors are required. Such tools should integrate neutronic and thermal-hydraulic phenomena in a multi-physics approach. Following this motivation, the neutron diffusion code ANDES is assessed for sodium fast reactor applications. ANDES is the nodal solver implemented inside the multigroup pin-by-pin diffusion COBAYA3 code, and is based on the analytical method ACMFD. Thus, the ACMFD was verified for SFR applications and while doing so, some limitations were encountered, which are discussed through this work. In order to solve those, some new developments are proposed and implemented in ANDES. Moreover, the code was satisfactorily coupled with the thermal-hydraulic code SUBCHANFLOW, recently developed at KIT. Finally, the different implementations are verified. In addition to those developments, the node homogenized multigroup cross sections and other neutron parameters were obtained for the ESFR core using ERANOS and SERPENT codes, and employed afterwards by ANDES to perform steady state calculations. Moreover, as a result of the UPM contribution to the safety package of the CP-ESFR project, the point kinetic parameters required by the typical plant thermal-hydraulic codes were computed for the ESFR core using SERPENT, which final aim was the assessment of the impact of minor actinides in transient behaviour. All in all, the thesis provides a systematic and multi-purpose approach applied to the assessment of safety and performance parameters of Generation-IV SFR, using existing and newly developed analytical tools. An important amount of time was employed in identifying the limitations that the analytical nodal diffusion methods present when applied to fast reactors following a multigroup approach, and interesting solutions are proposed in order to overcome them.
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The visual responses of neurons in the cerebral cortex were first adequately characterized in the 1960s by D. H. Hubel and T. N. Wiesel [(1962) J. Physiol. (London) 160, 106-154; (1968) J. Physiol. (London) 195, 215-243] using qualitative analyses based on simple geometric visual targets. Over the past 30 years, it has become common to consider the properties of these neurons by attempting to make formal descriptions of these transformations they execute on the visual image. Most such models have their roots in linear-systems approaches pioneered in the retina by C. Enroth-Cugell and J. R. Robson [(1966) J. Physiol. (London) 187, 517-552], but it is clear that purely linear models of cortical neurons are inadequate. We present two related models: one designed to account for the responses of simple cells in primary visual cortex (V1) and one designed to account for the responses of pattern direction selective cells in MT (or V5), an extrastriate visual area thought to be involved in the analysis of visual motion. These models share a common structure that operates in the same way on different kinds of input, and instantiate the widely held view that computational strategies are similar throughout the cerebral cortex. Implementations of these models for Macintosh microcomputers are available and can be used to explore the models' properties.
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The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.
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The physical implementation of quantum information processing is one of the major challenges of current research. In the last few years, several theoretical proposals and experimental demonstrations on a small number of qubits have been carried out, but a quantum computing architecture that is straightforwardly scalable, universal, and realizable with state-of-the-art technology is still lacking. In particular, a major ultimate objective is the construction of quantum simulators, yielding massively increased computational power in simulating quantum systems. Here we investigate promising routes towards the actual realization of a quantum computer, based on spin systems. The first one employs molecular nanomagnets with a doublet ground state to encode each qubit and exploits the wide chemical tunability of these systems to obtain the proper topology of inter-qubit interactions. Indeed, recent advances in coordination chemistry allow us to arrange these qubits in chains, with tailored interactions mediated by magnetic linkers. These act as switches of the effective qubit-qubit coupling, thus enabling the implementation of one- and two-qubit gates. Molecular qubits can be controlled either by uniform magnetic pulses, either by local electric fields. We introduce here two different schemes for quantum information processing with either global or local control of the inter-qubit interaction and demonstrate the high performance of these platforms by simulating the system time evolution with state-of-the-art parameters. The second architecture we propose is based on a hybrid spin-photon qubit encoding, which exploits the best characteristic of photons, whose mobility is exploited to efficiently establish long-range entanglement, and spin systems, which ensure long coherence times. The setup consists of spin ensembles coherently coupled to single photons within superconducting coplanar waveguide resonators. The tunability of the resonators frequency is exploited as the only manipulation tool to implement a universal set of quantum gates, by bringing the photons into/out of resonance with the spin transition. The time evolution of the system subject to the pulse sequence used to implement complex quantum algorithms has been simulated by numerically integrating the master equation for the system density matrix, thus including the harmful effects of decoherence. Finally a scheme to overcome the leakage of information due to inhomogeneous broadening of the spin ensemble is pointed out. Both the proposed setups are based on state-of-the-art technological achievements. By extensive numerical experiments we show that their performance is remarkably good, even for the implementation of long sequences of gates used to simulate interesting physical models. Therefore, the here examined systems are really promising buildingblocks of future scalable architectures and can be used for proof-of-principle experiments of quantum information processing and quantum simulation.
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The aim of this thesis is to present numerical investigations of the polarisation mode dispersion (PMD) effect. Outstanding issues on the side of the numerical implementations of PMD are resolved and the proposed methods are further optimized for computational efficiency and physical accuracy. Methods for the mitigation of the PMD effect are taken into account and simulations of transmission system with added PMD are presented. The basic outline of the work focusing on PMD can be divided as follows. At first the widely-used coarse-step method for simulating the PMD phenomenon as well as a method derived from the Manakov-PMD equation are implemented and investigated separately through the distribution of a state of polarisation on the Poincaré sphere, and the evolution of the dispersion of a signal. Next these two methods are statistically examined and compared to well-known analytical models of the probability distribution function (PDF) and the autocorrelation function (ACF) of the PMD phenomenon. Important optimisations are achieved, for each of the aforementioned implementations in the computational level. In addition the ACF of the coarse-step method is considered separately, based on the result which indicates that the numerically produced ACF, exaggerates the value of the correlation between different frequencies. Moreover the mitigation of the PMD phenomenon is considered, in the form of numerically implementing Low-PMD spun fibres. Finally, all the above are combined in simulations that demonstrate the impact of the PMD on the quality factor (Q=factor) of different transmission systems. For this a numerical solver based on the coupled nonlinear Schrödinger equation is created which is otherwise tested against the most important transmission impairments in the early chapters of this thesis.
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This paper presents an up to date review of digital watermarking (WM) from a VLSI designer point of view. The reader is introduced to basic principles and terms in the field of image watermarking. It goes through a brief survey on WM theory, laying out common classification criterions and discussing important design considerations and trade-offs. Elementary WM properties such as robustness, computational complexity and their influence on image quality are discussed. Common attacks and testing benchmarks are also briefly mentioned. It is shown that WM design must take the intended application into account. The difference between software and hardware implementations is explained through the introduction of a general scheme of a WM system and two examples from previous works. A versatile methodology to aid in a reliable and modular design process is suggested. Relating to mixed-signal VLSI design and testing, the proposed methodology allows an efficient development of a CMOS image sensor with WM capabilities.
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This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others.
This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system.
Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity.
Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.
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It is now clear that the concept of a HPC compiler which automatically produces highly efficient parallel implementations is a pipe-dream. Another route is to recognise from the outset that user information is required and to develop tools that embed user interaction in the transformation of code from scalar to parallel form, and then use conventional compilers with a set of communication calls. This represents the key idea underlying the development of the CAPTools software environment. The initial version of CAPTools is focused upon single block structured mesh computational mechanics codes. The capability for unstructured mesh codes is under test now and block structured meshes will be included next. The parallelisation process can be completed rapidly for modest codes and the parallel performance approaches that which is delivered by hand parallelisations.
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Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.