868 resultados para Statistical models of Box-Jenkins. Artificial neural networks (ANN). Oil flow curve


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Caracterización de los procesos de disipación mecánica basándose en la microestructura de los tejidos blandos. We present a continuous damage model with regularized softening (smeared crack models) for fiber reinforced soft tissues. Material parameters of the continuous model derive from the mesoscopic scale. In the mesoscopic scale continuum is considered as a collagenous fibrilreinforced composite. We want to study the continnumlevel response as a function of the nanoscale properties of the collagen and the adherent forces between the tropocollagen molecules.

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Grouping urban bus routes is necessary when there are evidences of significant differences among them. In Jiménez et al. (2013), a reduced sample of routes was grouped into clusters utilizing kinematic measured data. As a further step, in this paper, the remaining urban bus routes of a city, for which no kinematic measurements are available, are classified. For such purpose we use macroscopic geographical and functional variables to describe each route, while the clustering process is performed by means of a neural network. Limitations caused by reduced training samples are solved using the bootstrap method.

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The choice value and the testing process against the vigilance parameter, characteristic of ART Neural Network, are merged. Only, a single unique test is required to determine if a committed category node can represent the current input or not. Advantages of APT over ART are: 1-Avoid testing every committed category node before deciding to train a committed category node or a new node must be committed, 2-The vigilance parameter is fixed during training, and 3-The choice value parameter is eliminated.

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Social behavior is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks

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En hidrodinámica, el fenómeno de Sloshing se puede definir como el movimiento de la superficie libre de un fluido dentro de un contenedor sometido a fuerzas y perturbaciones externas. El fluido en cuestión experimenta violentos movimientos con importantes deformaciones de su superficie libre. La dinámica del fluido puede llegar a generar cargas hidrodinámicas considerables las cuales pueden afectar la integridad estructural y/o comprometer la estabilidad del vehículo que transporta dicho contenedor. El fenómeno de Sloshing ha sido extensivamente investigado matemática, numérica y experimentalmente, siendo el enfoque experimental el más usado debido a la complejidad del problema, para el cual los modelos matemáticos y de simulación son aun incapaces de predecir con suficiente rapidez y precisión las cargas debidas a dicho fenómeno. El flujo generado por el Sloshing usualmente se caracteriza por la presencia de un fluido multifase (gas-liquido) y turbulencia. Reducir al máximo posible la complejidad del fenómeno de Sloshing sin perder la esencia del problema es el principal reto de esta tesis doctoral, donde un trabajo experimental enfocado en casos canónicos de Sloshing es presentado y documentado con el objetivo de aumentar la comprensión de dicho fenómeno y por tanto intentar proveer información valiosa para validaciones de códigos numéricos. El fenómeno de Sloshing juega un papel importante en la industria del transporte marítimo de gas licuado (LNG). El mercado de LNG en los últimos años ha reportado un crecimiento hasta tres veces mayor al de los mercados de petróleo y gas convencionales. Ingenieros en laboratorios de investigación e ingenieros adscritos a la industria del LNG trabajan continuamente buscando soluciones económicas y seguras para contener, transferir y transportar grandes volúmenes de LNG. Los buques transportadores de LNG (LNGC) han pasado de ser unos pocos buques con capacidad de 75000 m3 hace unos treinta años, a una amplia flota con una capacidad de 140000 m3 actualmente. En creciente número, hoy día se construyen buques con capacidades que oscilan entre 175000 m3 y 250000 m3. Recientemente un nuevo concepto de buque LNG ha salido al mercado y se le conoce como FLNG. Un FLNG es un buque de gran valor añadido que solventa los problemas de extracción, licuefacción y almacenamiento del LNG, ya que cuenta con equipos de extracción y licuefacción a bordo, eliminando por tanto las tareas de transvase de las estaciones de licuefacción en tierra hacia los buques LNGC. EL LNG por tanto puede ser transferido directamente desde el FLNG hacia los buques LNGC en mar abierto. Niveles de llenado intermedios en combinación con oleaje durante las operaciones de trasvase inducen movimientos en los buques que generan por tanto el fenómeno de Sloshing dentro de los tanques de los FLNG y los LNGC. El trabajo de esta tesis doctoral lidia con algunos de los problemas del Sloshing desde un punto de vista experimental y estadístico, para ello una serie de tareas, descritas a continuación, se han llevado a cabo : 1. Un dispositivo experimental de Sloshing ha sido configurado. Dicho dispositivo ha permitido ensayar secciones rectangulares de tanques LNGC a escala con movimientos angulares de un grado de libertad. El dispositivo experimental ha sido instrumentado para realizar mediciones de movimiento, presiones, vibraciones y temperatura, así como la grabación de imágenes y videos. 2. Los impactos de olas generadas dentro de una sección rectangular de un LNGC sujeto a movimientos regulares forzados han sido estudiados mediante la caracterización del fenómeno desde un punto de vista estadístico enfocado en la repetitividad y la ergodicidad del problema. 3. El estudio de los impactos provocados por movimientos regulares ha sido extendido a un escenario más realístico mediante el uso de movimientos irregulares forzados. 4. El acoplamiento del Sloshing generado por el fluido en movimiento dentro del tanque LNGC y la disipación de la energía mecánica de un sistema no forzado de un grado de libertad (movimiento angular) sujeto a una excitación externa ha sido investigado. 5. En la última sección de esta tesis doctoral, la interacción entre el Sloshing generado dentro en una sección rectangular de un tanque LNGC sujeto a una excitación regular y un cuerpo elástico solidario al tanque ha sido estudiado. Dicho estudio corresponde a un problema de interacción fluido-estructura. Abstract In hydrodynamics, we refer to sloshing as the motion of liquids in containers subjected to external forces with large free-surface deformations. The liquid motion dynamics can generate loads which may affect the structural integrity of the container and the stability of the vehicle that carries such container. The prediction of these dynamic loads is a major challenge for engineers around the world working on the design of both the container and the vehicle. The sloshing phenomenon has been extensively investigated mathematically, numerically and experimentally. The latter has been the most fruitful so far, due to the complexity of the problem, for which the numerical and mathematical models are still incapable of accurately predicting the sloshing loads. The sloshing flows are usually characterised by the presence of multiphase interaction and turbulence. Reducing as much as possible the complexity of the sloshing problem without losing its essence is the main challenge of this phd thesis, where experimental work on selected canonical cases are presented and documented in order to better understand the phenomenon and to serve, in some cases, as an useful information for numerical validations. Liquid sloshing plays a key roll in the liquified natural gas (LNG) maritime transportation. The LNG market growth is more than three times the rated growth of the oil and traditional gas markets. Engineers working in research laboratories and companies are continuously looking for efficient and safe ways for containing, transferring and transporting the liquified gas. LNG carrying vessels (LNGC) have evolved from a few 75000 m3 vessels thirty years ago to a huge fleet of ships with a capacity of 140000 m3 nowadays and increasing number of 175000 m3 and 250000 m3 units. The concept of FLNG (Floating Liquified Natural Gas) has appeared recently. A FLNG unit is a high value-added vessel which can solve the problems of production, treatment, liquefaction and storage of the LNG because the vessel is equipped with a extraction and liquefaction facility. The LNG is transferred from the FLNG to the LNGC in open sea. The combination of partial fillings and wave induced motions may generate sloshing flows inside both the LNGC and the FLNG tanks. This work has dealt with sloshing problems from a experimental and statistical point of view. A series of tasks have been carried out: 1. A sloshing rig has been set up. It allows for testing tanks with one degree of freedom angular motion. The rig has been instrumented to measure motions, pressure and conduct video and image recording. 2. Regular motion impacts inside a rectangular section LNGC tank model have been studied, with forced motion tests, in order to characterise the phenomenon from a statistical point of view by assessing the repeatability and practical ergodicity of the problem. 3. The regular motion analysis has been extended to an irregular motion framework in order to reproduce more realistic scenarios. 4. The coupled motion of a single degree of freedom angular motion system excited by an external moment and affected by the fluid moment and the mechanical energy dissipation induced by sloshing inside the tank has been investigated. 5. The last task of the thesis has been to conduct an experimental investigation focused on the strong interaction between a sloshing flow in a rectangular section of a LNGC tank subjected to regular excitation and an elastic body clamped to the tank. It is thus a fluid structure interaction problem.

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El rebase se define como el transporte de una cantidad importante de agua sobre la coronación de una estructura. Por tanto, es el fenómeno que, en general, determina la cota de coronación del dique dependiendo de la cantidad aceptable del mismo, a la vista de condicionantes funcionales y estructurales del dique. En general, la cantidad de rebase que puede tolerar un dique de abrigo desde el punto de vista de su integridad estructural es muy superior a la cantidad permisible desde el punto de vista de su funcionalidad. Por otro lado, el diseño de un dique con una probabilidad de rebase demasiado baja o nula conduciría a diseños incompatibles con consideraciones de otro tipo, como son las estéticas o las económicas. Existen distintas formas de estudiar el rebase producido por el oleaje sobre los espaldones de las obras marítimas. Las más habituales son los ensayos en modelo físico y las formulaciones empíricas o semi-empíricas. Las menos habituales son la instrumentación en prototipo, las redes neuronales y los modelos numéricos. Los ensayos en modelo físico son la herramienta más precisa y fiable para el estudio específico de cada caso, debido a la complejidad del proceso de rebase, con multitud de fenómenos físicos y parámetros involucrados. Los modelos físicos permiten conocer el comportamiento hidráulico y estructural del dique, identificando posibles fallos en el proyecto antes de su ejecución, evaluando diversas alternativas y todo esto con el consiguiente ahorro en costes de construcción mediante la aportación de mejoras al diseño inicial de la estructura. Sin embargo, presentan algunos inconvenientes derivados de los márgenes de error asociados a los ”efectos de escala y de modelo”. Las formulaciones empíricas o semi-empíricas presentan el inconveniente de que su uso está limitado por la aplicabilidad de las fórmulas, ya que éstas sólo son válidas para una casuística de condiciones ambientales y tipologías estructurales limitadas al rango de lo reproducido en los ensayos. El objetivo de la presente Tesis Doctoral es el contrate de las formulaciones desarrolladas por diferentes autores en materia de rebase en distintas tipologías de diques de abrigo. Para ello, se ha realizado en primer lugar la recopilación y el análisis de las formulaciones existentes para estimar la tasa de rebase sobre diques en talud y verticales. Posteriormente, se llevó a cabo el contraste de dichas formulaciones con los resultados obtenidos en una serie de ensayos realizados en el Centro de Estudios de Puertos y Costas. Para finalizar, se aplicó a los ensayos de diques en talud seleccionados la herramienta neuronal NN-OVERTOPPING2, desarrollada en el proyecto europeo de rebases CLASH (“Crest Level Assessment of Coastal Structures by Full Scale Monitoring, Neural Network Prediction and Hazard Analysis on Permissible Wave Overtopping”), contrastando de este modo la tasa de rebase obtenida en los ensayos con este otro método basado en la teoría de las redes neuronales. Posteriormente, se analizó la influencia del viento en el rebase. Para ello se han realizado una serie de ensayos en modelo físico a escala reducida, generando oleaje con y sin viento, sobre la sección vertical del Dique de Levante de Málaga. Finalmente, se presenta el análisis crítico del contraste de cada una de las formulaciones aplicadas a los ensayos seleccionados, que conduce a las conclusiones obtenidas en la presente Tesis Doctoral. Overtopping is defined as the volume of water surpassing the crest of a breakwater and reaching the sheltered area. This phenomenon determines the breakwater’s crest level, depending on the volume of water admissible at the rear because of the sheltered area’s functional and structural conditioning factors. The ways to assess overtopping processes range from those deemed to be most traditional, such as semi-empirical or empirical type equations and physical, reduced scale model tests, to others less usual such as the instrumentation of actual breakwaters (prototypes), artificial neural networks and numerical models. Determining overtopping in reduced scale physical model tests is simple but the values obtained are affected to a greater or lesser degree by the effects of a scale model-prototype such that it can only be considered as an approximation to what actually happens. Nevertheless, physical models are considered to be highly useful for estimating damage that may occur in the area sheltered by the breakwater. Therefore, although physical models present certain problems fundamentally deriving from scale effects, they are still the most accurate, reliable tool for the specific study of each case, especially when large sized models are adopted and wind is generated Empirical expressions obtained from laboratory tests have been developed for calculating the overtopping rate and, therefore, the formulas obtained obviously depend not only on environmental conditions – wave height, wave period and water level – but also on the model’s characteristics and are only applicable in a range of validity of the tests performed in each case. The purpose of this Thesis is to make a comparative analysis of methods for calculating overtopping rates developed by different authors for harbour breakwater overtopping. First, existing equations were compiled and analysed in order to estimate the overtopping rate on sloping and vertical breakwaters. These equations were then compared with the results obtained in a number of tests performed in the Centre for Port and Coastal Studies of the CEDEX. In addition, a neural network model developed in the European CLASH Project (“Crest Level Assessment of Coastal Structures by Full Scale Monitoring, Neural Network Prediction and Hazard Analysis on Permissible Wave Overtopping“) was also tested. Finally, the wind effects on overtopping are evaluated using tests performed with and without wind in the physical model of the Levante Breakwater (Málaga).

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El empleo de refuerzos de FRP en vigas de hormigón armado es cada vez más frecuente por sus numerosas ventajas frente a otros métodos más tradicionales. Durante los últimos años, la técnica FRP-NSM, consistente en introducir barras de FRP sobre el recubrimiento de una viga de hormigón, se ha posicionado como uno de los mejores métodos de refuerzo y rehabilitación de estructuras de hormigón armado, tanto por su facilidad de montaje y mantenimiento, como por su rendimiento para aumentar la capacidad resistente de dichas estructuras. Si bien el refuerzo a flexión ha sido ampliamente desarrollado y estudiado hasta la fecha, no sucede lo mismo con el refuerzo a cortante, debido principalmente a su gran complejidad. Sin embargo, se debería dedicar más estudio a este tipo de refuerzo si se pretenden conservar los criterios de diseño en estructuras de hormigón armado, los cuales están basados en evitar el fallo a cortante por sus consecuencias catastróficas Esta ausencia de información y de normativa es la que justifica esta tesis doctoral. En este pro-yecto se van a desarrollar dos metodologías alternativas, que permiten estimar la capacidad resistente de vigas de hormigón armado, reforzadas a cortante mediante la técnica FRP-NSM. El primer método aplicado consiste en la implementación de una red neuronal artificial capaz de predecir adecuadamente la resistencia a cortante de vigas reforzadas con este método a partir de experimentos anteriores. Asimismo, a partir de la red se han llevado a cabo algunos estudios a fin de comprender mejor la influencia real de algunos parámetros de la viga y del refuerzo sobre la resistencia a cortante con el propósito de lograr diseños más seguros de este tipo de refuerzo. Una configuración óptima de la red requiere discriminar adecuadamente de entre los numerosos parámetros (geométricos y de material) que pueden influir en el compor-tamiento resistente de la viga, para lo cual se han llevado a cabo diversos estudios y pruebas. Mediante el segundo método, se desarrolla una ecuación de proyecto que permite, de forma sencilla, estimar la capacidad de vigas reforzadas a cortante con FRP-NSM, la cual podría ser propuesta para las principales guías de diseño. Para alcanzar este objetivo, se plantea un pro-blema de optimización multiobjetivo a partir de resultados de ensayos experimentales llevados a cabo sobre vigas de hormigón armado con y sin refuerzo de FRP. El problema multiobjetivo se resuelve mediante algoritmos genéticos, en concreto el algoritmo NSGA-II, por ser más apropiado para problemas con varias funciones objetivo que los métodos de optimización clásicos. Mediante una comparativa de las predicciones realizadas con ambos métodos y de los resulta-dos de ensayos experimentales se podrán establecer las ventajas e inconvenientes derivadas de la aplicación de cada una de las dos metodologías. Asimismo, se llevará a cabo un análisis paramétrico con ambos enfoques a fin de intentar determinar la sensibilidad de aquellos pa-rámetros más sensibles a este tipo de refuerzo. Finalmente, se realizará un análisis estadístico de la fiabilidad de las ecuaciones de diseño deri-vadas de la optimización multiobjetivo. Con dicho análisis se puede estimar la capacidad resis-tente de una viga reforzada a cortante con FRP-NSM dentro de un margen de seguridad espe-cificado a priori. ABSTRACT The use of externally bonded (EB) fibre-reinforced polymer (FRP) composites has gained acceptance during the last two decades in the construction engineering community, particularly in the rehabilitation of reinforced concrete (RC) structures. Currently, to increase the shear resistance of RC beams, FRP sheets are externally bonded (EB-FRP) and applied on the external side surface of the beams to be strengthened with different configurations. Of more recent application, the near-surface mounted FRP bar (NSM-FRP) method is another technique successfully used to increase the shear resistance of RC beams. In the NSM method, FRP rods are embedded into grooves intentionally prepared in the concrete cover of the side faces of RC beams. While flexural strengthening has been widely developed and studied so far, the same doesn´t occur to shearing strength mainly due to its great complexity. Nevertheless, if design criteria are to be preserved more research should be done to this sort of strength, which are based on avoiding shear failure and its catastrophic consequences. However, in spite of this, accurately calculating the shear capacity of FRP shear strengthened RC beams remains a complex challenge that has not yet been fully resolved due to the numerous variables involved in the procedure. The objective of this Thesis is to develop methodologies to evaluate the capacity of FRP shear strengthened RC beams by dealing with the problem from a different point of view to the numerical modeling approach by using artificial intelligence techniques. With this purpose two different approaches have been developed: one concerned with the use of artificial neural networks and the other based on the implementation of an optimization approach developed jointly with the use of artificial neural networks (ANNs) and solved with genetic algorithms (GAs). With these approaches some of the difficulties concerned regarding the numerical modeling can be overcome. As an alternative tool to conventional numerical techniques, neural networks do not provide closed form solutions for modeling problems but do, however, offer a complex and accurate solution based on a representative set of historical examples of the relationship. Furthermore, they can adapt solutions over time to include new data. On the other hand, as a second proposal, an optimization approach has also been developed to implement simple yet accurate shear design equations for this kind of strengthening. This approach is developed in a multi-objective framework by considering experimental results of RC beams with and without NSM-FRP. Furthermore, the results obtained with the previous scheme based on ANNs are also used as a filter to choose the parameters to include in the design equations. Genetic algorithms are used to solve the optimization problem since they are especially suitable for solving multi-objective problems when compared to standard optimization methods. The key features of the two proposed procedures are outlined and their performance in predicting the capacity of NSM-FRP shear strengthened RC beams is evaluated by comparison with results from experimental tests and with predictions obtained using a simplified numerical model. A sensitivity study of the predictions of both models for the input parameters is also carried out.

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El desarrollo de nuevas estructuras aeroespaciales optimizadas, utilizan materiales compuestos, para los componentes críticos y subsistemas, principalmente polímeros reforzados con fibra de carbono (CFRP). Un conocimiento profundo del estado de daño por fatiga de estructuras de CFRP avanzado, es esencial para predecir la vida residual y optimizar los intervalos de inspección estructural, reparaciones y/o sustitución de componentes. Las técnicas actuales se basan principalmente en la medición de cargas estructurales a lo largo de la vida útil de la estructura mediante galgas extensométricas eléctricas. Con esos datos, se estima la vida a fatiga utilizando modelos de acumulación de daño. En la presente tesis, se evalúa la metodología convencional para la estimación de la vida a fatiga de un CFRP aeronáutico. Esta metodología está basada en la regla de acumulación de daño lineal de Palmgren-Miner, y es aplicada para determinar la vida a fatiga de estructuras sometidas a cargas de amplitud variable. Se ha realizado una campaña de ensayos con cargas de amplitud constante para caracterizar un CFRP aeronáutico a fatiga, obteniendo las curvas clásicas S-N, en diferentes relaciones de esfuerzo. Se determinaron los diagramas de vida constante, (CLD), también conocidos como diagramas de Goodman, utilizando redes neuronales artificiales debido a la ausencia de modelos coherentes para materiales compuestos. Se ha caracterizado la degradación de la rigidez debido al daño por fatiga. Se ha ensayado un segundo grupo de probetas con secuencias estandarizadas de cargas de amplitud variable, para obtener la vida a fatiga y la degradación de rigidez en condiciones realistas. Las cargas aplicadas son representativas de misiones de aviones de combate (Falstaff), y de aviones de transporte (Twist). La vida a fatiga de las probetas cicladas con cargas de amplitud variable, se comparó con el índice de daño teórico calculado en base a la regla de acumulación de daño lineal convencional. Los resultados obtenidos muestran predicciones no conservativas. Esta tesis también presenta el estudio y desarrollo, de una nueva técnica de no contacto para evaluar el estado de daño por fatiga de estructuras de CFRP por medio de cambios de los parámetros de rugosidad. La rugosidad superficial se puede medir fácilmente en campo con métodos sin contacto, mediante técnicas ópticas tales como speckle y perfilómetros ópticos. En el presente estudio, se han medido parámetros de rugosidad superficial, y el factor de irregularidad de la superficie, a lo largo de la vida de las probetas cicladas con cargas de amplitud constante y variable, Se ha obtenido una buena tendencia de ajuste al correlacionar la magnitud de la rugosidad y el factor de irregularidad de la superficie con la degradación de la rigidez de las probetas fatigadas. Estos resultados sugieren que los cambios en la rugosidad superficial medida en zonas estratégicas de componentes y estructuras hechas de CFRP, podrían ser indicativas del nivel de daño interno debido a cargas de fatiga. Los resultados también sugieren que el método es independiente del tipo de carga de fatiga que ha causado el daño. Esto último hace que esta técnica de medición sea aplicable como inspección para una amplia gama de estructuras de materiales compuestos, desde tanques presurizados con cargas de amplitud constante, estructuras aeronáuticas como alas y colas de aeronaves cicladas con cargas de amplitud variable, hasta aplicaciones industriales como automoción, entre otros. ABSTRACT New optimized aerospace structures use composite materials, mainly carbon fiber reinforced polymer composite (CFRP), for critical components and subsystems. A strong knowledge of the fatigue state of highly advanced (CFRP) structures is essential to predict the residual life and optimize intervals of structural inspection, repairs, and/or replacements. Current techniques are based mostly on measurement of structural loads throughout the service life by electric strain gauge sensors. These sensors are affected by extreme environmental conditions and by fatigue loads in such a way that the sensors and their systems require exhaustive maintenance throughout system life. In the present thesis, the conventional methodology based on linear damage accumulation rules, applied to determine the fatigue life of structures subjected to variable amplitude loads was evaluated for an aeronautical CFRP. A test program with constant amplitude loads has been performed to obtain the classical S-N curves at different stress ratios. Constant life diagrams, CLDs, where determined by means of Artificial Neural Networks due to the absence of consistent models for composites. The stiffness degradation due to fatigue damage has been characterized for coupons under cyclic tensile loads. A second group of coupons have been tested until failure with a standardized sequence of variable amplitude loads, representative of missions for combat aircraft (Falstaff), and representative of commercial flights (Twist), to obtain the fatigue life and the stiffness degradation under realistic conditions. The fatigue life of the coupons cycled with variable amplitude loads were compared to the theoretical damage index calculated based on the conventional linear damage accumulation rule. The obtained results show non-conservative predictions. This thesis also presents the evaluation of a new non-contact technique to evaluate the fatigue damage state of CFRP structures by means of measuring roughness parameters to evaluate changes in the surface topography. Surface roughness can be measured easily on field with non-contact methods by optical techniques such as speckle and optical perfilometers. In the present study, surface roughness parameters, and the surface irregularity factor, have been measured along the life of the coupons cycled with constant and variable amplitude loads of different magnitude. A good agreement has been obtained when correlating the magnitude of the roughness and the surface irregularity factor with the stiffness degradation. These results suggest that the changes on the surface roughness measured in strategic zones of components and structures made of CFRP, could be indicative of the level of internal damage due to fatigue loads. The results also suggest that the method is independent of the type of fatigue load that have caused the damage. It makes this measurement technique applicable for a wide range of inspections of composite materials structures, from pressurized tanks with constant amplitude loads, to variable amplitude loaded aeronautical structures like wings and empennages, up to automotive and other industrial applications.

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SBASE 8.0 is the eighth release of the SBASE library of protein domain sequences that contains 294 898 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to most major sequence databases and sequence pattern collections. The entries are clustered into over 2005 statistically validated domain groups (SBASE-A) and 595 non-validated groups (SBASE-B), provided with several WWW-based search and browsing facilities for online use. A domain-search facility was developed, based on non-parametric pattern recognition methods, including artificial neural networks. SBASE 8.0 is freely available by anonymous ‘ftp’ file transfer from ftp.icgeb.trieste.it. Automated searching of SBASE can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/ and http://sbase.abc.hu/sbase/.

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Estimation of evolutionary distances has always been a major issue in the study of molecular evolution because evolutionary distances are required for estimating the rate of evolution in a gene, the divergence dates between genes or organisms, and the relationships among genes or organisms. Other closely related issues are the estimation of the pattern of nucleotide substitution, the estimation of the degree of rate variation among sites in a DNA sequence, and statistical testing of the molecular clock hypothesis. Mathematical treatments of these problems are considerably simplified by the assumption of a stationary process in which the nucleotide compositions of the sequences under study have remained approximately constant over time, and there now exist fairly extensive studies of stationary models of nucleotide substitution, although some problems remain to be solved. Nonstationary models are much more complex, but significant progress has been recently made by the development of the paralinear and LogDet distances. This paper reviews recent studies on the above issues and reports results on correcting the estimation bias of evolutionary distances, the estimation of the pattern of nucleotide substitution, and the estimation of rate variation among the sites in a sequence.

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Este trabalho apresenta uma nova metodologia para otimizar carteiras de ativos financeiros. A metodologia proposta, baseada em interpoladores universais tais quais as Redes Neurais Artificiais e a Krigagem, permite aproximar a superfície de risco e consequentemente a solução do problema de otimização associado a ela de forma generalizada e aplicável a qualquer medida de risco disponível na literatura. Além disto, a metodologia sugerida permite que sejam relaxadas hipóteses restritivas inerentes às metodologias existentes, simplificando o problema de otimização e permitindo que sejam estimados os erros na aproximação da superfície de risco. Ilustrativamente, aplica-se a metodologia proposta ao problema de composição de carteiras com a Variância (controle), o Valor-em-Risco (VaR) e o Valor-em-Risco Condicional (CVaR) como funções objetivo. Os resultados são comparados àqueles obtidos pelos modelos de Markowitz e Rockafellar, respectivamente.

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3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

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A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.