926 resultados para Evolutionary particle swarm optimization
Resumo:
This paper presents a technique for performing analog design synthesis at circuit level providing feedback to the designer through the exploration of the Pareto frontier. A modified simulated annealing which is able to perform crossover with past anchor points when a local minimum is found which is used as the optimization algorithm on the initial synthesis procedure. After all specifications are met, the algorithm searches for the extreme points of the Pareto frontier in order to obtain a non-exhaustive exploration of the Pareto front. Finally, multi-objective particle swarm optimization is used to spread the results and to find a more accurate frontier. Piecewise linear functions are used as single-objective cost functions to produce a smooth and equal convergence of all measurements to the desired specifications during the composition of the aggregate objective function. To verify the presented technique two circuits were designed, which are: a Miller amplifier with 96 dB Voltage gain, 15.48 MHz unity gain frequency, slew rate of 19.2 V/mu s with a current supply of 385.15 mu A, and a complementary folded cascode with 104.25 dB Voltage gain, 18.15 MHz of unity gain frequency and a slew rate of 13.370 MV/mu s. These circuits were synthesized using a 0.35 mu m technology. The results show that the method provides a fast approach for good solutions using the modified SA and further good Pareto front exploration through its connection to the particle swarm optimization algorithm.
Resumo:
Two new approaches to quantitatively analyze diffuse diffraction intensities from faulted layer stacking are reported. The parameters of a probability-based growth model are determined with two iterative global optimization methods: a genetic algorithm (GA) and particle swarm optimization (PSO). The results are compared with those from a third global optimization method, a differential evolution (DE) algorithm [Storn & Price (1997). J. Global Optim. 11, 341–359]. The algorithm efficiencies in the early and late stages of iteration are compared. The accuracy of the optimized parameters improves with increasing size of the simulated crystal volume. The wall clock time for computing quite large crystal volumes can be kept within reasonable limits by the parallel calculation of many crystals (clones) generated for each model parameter set on a super- or grid computer. The faulted layer stacking in single crystals of trigonal three-pointedstar- shaped tris(bicylco[2.1.1]hexeno)benzene molecules serves as an example for the numerical computations. Based on numerical values of seven model parameters (reference parameters), nearly noise-free reference intensities of 14 diffuse streaks were simulated from 1280 clones, each consisting of 96 000 layers (reference crystal). The parameters derived from the reference intensities with GA, PSO and DE were compared with the original reference parameters as a function of the simulated total crystal volume. The statistical distribution of structural motifs in the simulated crystals is in good agreement with that in the reference crystal. The results found with the growth model for layer stacking disorder are applicable to other disorder types and modeling techniques, Monte Carlo in particular.
Resumo:
Con el surgir de los problemas irresolubles de forma eficiente en tiempo polinomial en base al dato de entrada, surge la Computación Natural como alternativa a la computación clásica. En esta disciplina se trata de o bien utilizar la naturaleza como base de cómputo o bien, simular su comportamiento para obtener mejores soluciones a los problemas que los encontrados por la computación clásica. Dentro de la computación natural, y como una representación a nivel celular, surge la Computación con Membranas. La primera abstracción de las membranas que se encuentran en las células, da como resultado los P sistemas de transición. Estos sistemas, que podrían ser implementados en medios biológicos o electrónicos, son la base de estudio de esta Tesis. En primer lugar, se estudian las implementaciones que se han realizado, con el fin de centrarse en las implementaciones distribuidas, que son las que pueden aprovechar las características intrínsecas de paralelismo y no determinismo. Tras un correcto estudio del estado actual de las distintas etapas que engloban a la evolución del sistema, se concluye con que las distribuciones que buscan un equilibrio entre las dos etapas (aplicación y comunicación), son las que mejores resultados presentan. Para definir estas distribuciones, es necesario definir completamente el sistema, y cada una de las partes que influyen en su transición. Además de los trabajos de otros investigadores, y junto a ellos, se realizan variaciones a los proxies y arquitecturas de distribución, para tener completamente definidos el comportamiento dinámico de los P sistemas. A partir del conocimiento estático –configuración inicial– del P sistema, se pueden realizar distribuciones de membranas en los procesadores de un clúster para obtener buenos tiempos de evolución, con el fin de que la computación del P sistema sea realizada en el menor tiempo posible. Para realizar estas distribuciones, hay que tener presente las arquitecturas –o forma de conexión– de los procesadores del clúster. La existencia de 4 arquitecturas, hace que el proceso de distribución sea dependiente de la arquitectura a utilizar, y por tanto, aunque con significativas semejanzas, los algoritmos de distribución deben ser realizados también 4 veces. Aunque los propulsores de las arquitecturas han estudiado el tiempo óptimo de cada arquitectura, la inexistencia de distribuciones para estas arquitecturas ha llevado a que en esta Tesis se probaran las 4, hasta que sea posible determinar que en la práctica, ocurre lo mismo que en los estudios teóricos. Para realizar la distribución, no existe ningún algoritmo determinista que consiga una distribución que satisfaga las necesidades de la arquitectura para cualquier P sistema. Por ello, debido a la complejidad de dicho problema, se propone el uso de metaheurísticas de Computación Natural. En primer lugar, se propone utilizar Algoritmos Genéticos, ya que es posible realizar alguna distribución, y basada en la premisa de que con la evolución, los individuos mejoran, con la evolución de dichos algoritmos, las distribuciones también mejorarán obteniéndose tiempos cercanos al óptimo teórico. Para las arquitecturas que preservan la topología arbórea del P sistema, han sido necesarias realizar nuevas representaciones, y nuevos algoritmos de cruzamiento y mutación. A partir de un estudio más detallado de las membranas y las comunicaciones entre procesadores, se ha comprobado que los tiempos totales que se han utilizado para la distribución pueden ser mejorados e individualizados para cada membrana. Así, se han probado los mismos algoritmos, obteniendo otras distribuciones que mejoran los tiempos. De igual forma, se han planteado el uso de Optimización por Enjambres de Partículas y Evolución Gramatical con reescritura de gramáticas (variante de Evolución Gramatical que se presenta en esta Tesis), para resolver el mismo cometido, obteniendo otro tipo de distribuciones, y pudiendo realizar una comparativa de las arquitecturas. Por último, el uso de estimadores para el tiempo de aplicación y comunicación, y las variaciones en la topología de árbol de membranas que pueden producirse de forma no determinista con la evolución del P sistema, hace que se deba de monitorizar el mismo, y en caso necesario, realizar redistribuciones de membranas en procesadores, para seguir obteniendo tiempos de evolución razonables. Se explica, cómo, cuándo y dónde se deben realizar estas modificaciones y redistribuciones; y cómo es posible realizar este recálculo. Abstract Natural Computing is becoming a useful alternative to classical computational models since it its able to solve, in an efficient way, hard problems in polynomial time. This discipline is based on biological behaviour of living organisms, using nature as a basis of computation or simulating nature behaviour to obtain better solutions to problems solved by the classical computational models. Membrane Computing is a sub discipline of Natural Computing in which only the cellular representation and behaviour of nature is taken into account. Transition P Systems are the first abstract representation of membranes belonging to cells. These systems, which can be implemented in biological organisms or in electronic devices, are the main topic studied in this thesis. Implementations developed in this field so far have been studied, just to focus on distributed implementations. Such distributions are really important since they can exploit the intrinsic parallelism and non-determinism behaviour of living cells, only membranes in this case study. After a detailed survey of the current state of the art of membranes evolution and proposed algorithms, this work concludes that best results are obtained using an equal assignment of communication and rules application inside the Transition P System architecture. In order to define such optimal distribution, it is necessary to fully define the system, and each one of the elements that influence in its transition. Some changes have been made in the work of other authors: load distribution architectures, proxies definition, etc., in order to completely define the dynamic behaviour of the Transition P System. Starting from the static representation –initial configuration– of the Transition P System, distributions of membranes in several physical processors of a cluster is algorithmically done in order to get a better performance of evolution so that the computational complexity of the Transition P System is done in less time as possible. To build these distributions, the cluster architecture –or connection links– must be considered. The existence of 4 architectures, makes that the process of distribution depends on the chosen architecture, and therefore, although with significant similarities, the distribution algorithms must be implemented 4 times. Authors who proposed such architectures have studied the optimal time of each one. The non existence of membrane distributions for these architectures has led us to implement a dynamic distribution for the 4. Simulations performed in this work fix with the theoretical studies. There is not any deterministic algorithm that gets a distribution that meets the needs of the architecture for any Transition P System. Therefore, due to the complexity of the problem, the use of meta-heuristics of Natural Computing is proposed. First, Genetic Algorithm heuristic is proposed since it is possible to make a distribution based on the premise that along with evolution the individuals improve, and with the improvement of these individuals, also distributions enhance, obtaining complexity times close to theoretical optimum time. For architectures that preserve the tree topology of the Transition P System, it has been necessary to make new representations of individuals and new algorithms of crossover and mutation operations. From a more detailed study of the membranes and the communications among processors, it has been proof that the total time used for the distribution can be improved and individualized for each membrane. Thus, the same algorithms have been tested, obtaining other distributions that improve the complexity time. In the same way, using Particle Swarm Optimization and Grammatical Evolution by rewriting grammars (Grammatical Evolution variant presented in this thesis), to solve the same distribution task. New types of distributions have been obtained, and a comparison of such genetic and particle architectures has been done. Finally, the use of estimators for the time of rules application and communication, and variations in tree topology of membranes that can occur in a non-deterministic way with evolution of the Transition P System, has been done to monitor the system, and if necessary, perform a membrane redistribution on processors to obtain reasonable evolution time. How, when and where to make these changes and redistributions, and how it can perform this recalculation, is explained.
Resumo:
El auge del "Internet de las Cosas" (IoT, "Internet of Things") y sus tecnologías asociadas han permitido su aplicación en diversos dominios de la aplicación, entre los que se encuentran la monitorización de ecosistemas forestales, la gestión de catástrofes y emergencias, la domótica, la automatización industrial, los servicios para ciudades inteligentes, la eficiencia energética de edificios, la detección de intrusos, la gestión de desastres y emergencias o la monitorización de señales corporales, entre muchas otras. La desventaja de una red IoT es que una vez desplegada, ésta queda desatendida, es decir queda sujeta, entre otras cosas, a condiciones climáticas cambiantes y expuestas a catástrofes naturales, fallos de software o hardware, o ataques maliciosos de terceros, por lo que se puede considerar que dichas redes son propensas a fallos. El principal requisito de los nodos constituyentes de una red IoT es que estos deben ser capaces de seguir funcionando a pesar de sufrir errores en el propio sistema. La capacidad de la red para recuperarse ante fallos internos y externos inesperados es lo que se conoce actualmente como "Resiliencia" de la red. Por tanto, a la hora de diseñar y desplegar aplicaciones o servicios para IoT, se espera que la red sea tolerante a fallos, que sea auto-configurable, auto-adaptable, auto-optimizable con respecto a nuevas condiciones que puedan aparecer durante su ejecución. Esto lleva al análisis de un problema fundamental en el estudio de las redes IoT, el problema de la "Conectividad". Se dice que una red está conectada si todo par de nodos en la red son capaces de encontrar al menos un camino de comunicación entre ambos. Sin embargo, la red puede desconectarse debido a varias razones, como que se agote la batería, que un nodo sea destruido, etc. Por tanto, se hace necesario gestionar la resiliencia de la red con el objeto de mantener la conectividad entre sus nodos, de tal manera que cada nodo IoT sea capaz de proveer servicios continuos, a otros nodos, a otras redes o, a otros servicios y aplicaciones. En este contexto, el objetivo principal de esta tesis doctoral se centra en el estudio del problema de conectividad IoT, más concretamente en el desarrollo de modelos para el análisis y gestión de la Resiliencia, llevado a la práctica a través de las redes WSN, con el fin de mejorar la capacidad la tolerancia a fallos de los nodos que componen la red. Este reto se aborda teniendo en cuenta dos enfoques distintos, por una parte, a diferencia de otro tipo de redes de dispositivos convencionales, los nodos en una red IoT son propensos a perder la conexión, debido a que se despliegan en entornos aislados, o en entornos con condiciones extremas; por otra parte, los nodos suelen ser recursos con bajas capacidades en términos de procesamiento, almacenamiento y batería, entre otros, por lo que requiere que el diseño de la gestión de su resiliencia sea ligero, distribuido y energéticamente eficiente. En este sentido, esta tesis desarrolla técnicas auto-adaptativas que permiten a una red IoT, desde la perspectiva del control de su topología, ser resiliente ante fallos en sus nodos. Para ello, se utilizan técnicas basadas en lógica difusa y técnicas de control proporcional, integral y derivativa (PID - "proportional-integral-derivative"), con el objeto de mejorar la conectividad de la red, teniendo en cuenta que el consumo de energía debe preservarse tanto como sea posible. De igual manera, se ha tenido en cuenta que el algoritmo de control debe ser distribuido debido a que, en general, los enfoques centralizados no suelen ser factibles a despliegues a gran escala. El presente trabajo de tesis implica varios retos que conciernen a la conectividad de red, entre los que se incluyen: la creación y el análisis de modelos matemáticos que describan la red, una propuesta de sistema de control auto-adaptativo en respuesta a fallos en los nodos, la optimización de los parámetros del sistema de control, la validación mediante una implementación siguiendo un enfoque de ingeniería del software y finalmente la evaluación en una aplicación real. Atendiendo a los retos anteriormente mencionados, el presente trabajo justifica, mediante una análisis matemático, la relación existente entre el "grado de un nodo" (definido como el número de nodos en la vecindad del nodo en cuestión) y la conectividad de la red, y prueba la eficacia de varios tipos de controladores que permiten ajustar la potencia de trasmisión de los nodos de red en respuesta a eventuales fallos, teniendo en cuenta el consumo de energía como parte de los objetivos de control. Así mismo, este trabajo realiza una evaluación y comparación con otros algoritmos representativos; en donde se demuestra que el enfoque desarrollado es más tolerante a fallos aleatorios en los nodos de la red, así como en su eficiencia energética. Adicionalmente, el uso de algoritmos bioinspirados ha permitido la optimización de los parámetros de control de redes dinámicas de gran tamaño. Con respecto a la implementación en un sistema real, se han integrado las propuestas de esta tesis en un modelo de programación OSGi ("Open Services Gateway Initiative") con el objeto de crear un middleware auto-adaptativo que mejore la gestión de la resiliencia, especialmente la reconfiguración en tiempo de ejecución de componentes software cuando se ha producido un fallo. Como conclusión, los resultados de esta tesis doctoral contribuyen a la investigación teórica y, a la aplicación práctica del control resiliente de la topología en redes distribuidas de gran tamaño. Los diseños y algoritmos presentados pueden ser vistos como una prueba novedosa de algunas técnicas para la próxima era de IoT. A continuación, se enuncian de forma resumida las principales contribuciones de esta tesis: (1) Se han analizado matemáticamente propiedades relacionadas con la conectividad de la red. Se estudia, por ejemplo, cómo varía la probabilidad de conexión de la red al modificar el alcance de comunicación de los nodos, así como cuál es el mínimo número de nodos que hay que añadir al sistema desconectado para su re-conexión. (2) Se han propuesto sistemas de control basados en lógica difusa para alcanzar el grado de los nodos deseado, manteniendo la conectividad completa de la red. Se han evaluado diferentes tipos de controladores basados en lógica difusa mediante simulaciones, y los resultados se han comparado con otros algoritmos representativos. (3) Se ha investigado más a fondo, dando un enfoque más simple y aplicable, el sistema de control de doble bucle, y sus parámetros de control se han optimizado empleando algoritmos heurísticos como el método de la entropía cruzada (CE, "Cross Entropy"), la optimización por enjambre de partículas (PSO, "Particle Swarm Optimization"), y la evolución diferencial (DE, "Differential Evolution"). (4) Se han evaluado mediante simulación, la mayoría de los diseños aquí presentados; además, parte de los trabajos se han implementado y validado en una aplicación real combinando técnicas de software auto-adaptativo, como por ejemplo las de una arquitectura orientada a servicios (SOA, "Service-Oriented Architecture"). ABSTRACT The advent of the Internet of Things (IoT) enables a tremendous number of applications, such as forest monitoring, disaster management, home automation, factory automation, smart city, etc. However, various kinds of unexpected disturbances may cause node failure in the IoT, for example battery depletion, software/hardware malfunction issues and malicious attacks. So, it can be considered that the IoT is prone to failure. The ability of the network to recover from unexpected internal and external failures is known as "resilience" of the network. Resilience usually serves as an important non-functional requirement when designing IoT, which can further be broken down into "self-*" properties, such as self-adaptive, self-healing, self-configuring, self-optimization, etc. One of the consequences that node failure brings to the IoT is that some nodes may be disconnected from others, such that they are not capable of providing continuous services for other nodes, networks, and applications. In this sense, the main objective of this dissertation focuses on the IoT connectivity problem. A network is regarded as connected if any pair of different nodes can communicate with each other either directly or via a limited number of intermediate nodes. More specifically, this thesis focuses on the development of models for analysis and management of resilience, implemented through the Wireless Sensor Networks (WSNs), which is a challenging task. On the one hand, unlike other conventional network devices, nodes in the IoT are more likely to be disconnected from each other due to their deployment in a hostile or isolated environment. On the other hand, nodes are resource-constrained in terms of limited processing capability, storage and battery capacity, which requires that the design of the resilience management for IoT has to be lightweight, distributed and energy-efficient. In this context, the thesis presents self-adaptive techniques for IoT, with the aim of making the IoT resilient against node failures from the network topology control point of view. The fuzzy-logic and proportional-integral-derivative (PID) control techniques are leveraged to improve the network connectivity of the IoT in response to node failures, meanwhile taking into consideration that energy consumption must be preserved as much as possible. The control algorithm itself is designed to be distributed, because the centralized approaches are usually not feasible in large scale IoT deployments. The thesis involves various aspects concerning network connectivity, including: creation and analysis of mathematical models describing the network, proposing self-adaptive control systems in response to node failures, control system parameter optimization, implementation using the software engineering approach, and evaluation in a real application. This thesis also justifies the relations between the "node degree" (the number of neighbor(s) of a node) and network connectivity through mathematic analysis, and proves the effectiveness of various types of controllers that can adjust power transmission of the IoT nodes in response to node failures. The controllers also take into consideration the energy consumption as part of the control goals. The evaluation is performed and comparison is made with other representative algorithms. The simulation results show that the proposals in this thesis can tolerate more random node failures and save more energy when compared with those representative algorithms. Additionally, the simulations demonstrate that the use of the bio-inspired algorithms allows optimizing the parameters of the controller. With respect to the implementation in a real system, the programming model called OSGi (Open Service Gateway Initiative) is integrated with the proposals in order to create a self-adaptive middleware, especially reconfiguring the software components at runtime when failures occur. The outcomes of this thesis contribute to theoretic research and practical applications of resilient topology control for large and distributed networks. The presented controller designs and optimization algorithms can be viewed as novel trials of the control and optimization techniques for the coming era of the IoT. The contributions of this thesis can be summarized as follows: (1) Mathematically, the fault-tolerant probability of a large-scale stochastic network is analyzed. It is studied how the probability of network connectivity depends on the communication range of the nodes, and what is the minimum number of neighbors to be added for network re-connection. (2) A fuzzy-logic control system is proposed, which obtains the desired node degree and in turn maintains the network connectivity when it is subject to node failures. There are different types of fuzzy-logic controllers evaluated by simulations, and the results demonstrate the improvement of fault-tolerant capability as compared to some other representative algorithms. (3) A simpler but more applicable approach, the two-loop control system is further investigated, and its control parameters are optimized by using some heuristic algorithms such as Cross Entropy (CE), Particle Swarm Optimization (PSO), and Differential Evolution (DE). (4) Most of the designs are evaluated by means of simulations, but part of the proposals are implemented and tested in a real-world application by combining the self-adaptive software technique and the control algorithms which are presented in this thesis.
A simplified spectral approachfor impedance-based damage identification of frp-strengthened rc beams
Resumo:
Hoy en día, el refuerzo y reparación de estructuras de hormigón armado mediante el pegado de bandas de polímeros reforzados con fibras (FRP) se emplea cada vez con más frecuencia a causa de sus numerosas ventajas. Sin embargo, las vigas reforzadas con esta técnica pueden experimentar un modo de fallo frágil a causa del despegue repentino de la banda de FRP a partir de una fisura intermedia. A pesar de su importancia, el número de trabajos que abordan el estudio de este mecanismo de fallo y su monitorización es muy limitado. Por ello, el desarrollo de metodologías capaces de monitorizar a largo plazo la adherencia de este refuerzo a las estructuras de hormigón e identificar cuándo se inicia el despegue de la banda constituyen un importante desafío a abordar. El principal objetivo de esta tesis es la implementación de una metodología fiable y efectiva, capaz de detectar el despegue de una banda de FRP en una viga de hormigón armado a partir de una fisura intermedia. Para alcanzar este objetivo se ha implementado un procedimiento de calibración numérica a partir de ensayos experimentales. Para ello, en primer lugar, se ha desarrollado un modelo numérico unidimensional simple y no costoso representativo del comportamiento de este tipo vigas de hormigón reforzadas con FRP, basado en un modelo de fisura discreta para el hormigón y el método de elementos espectrales. La formación progresiva de fisuras a flexion y el consiguiente despegue en la interface entre el hormigón y el FRP se formulan mediante la introducción de un nuevo elemento capaz de representar ambos fenómenos simultáneamente sin afectar al procedimiento numérico. Además, con el modelo propuesto, se puede obtener de una forma sencilla la respuesta dinámica en altas frecuencias de este tipo de estructuras, lo cual puede hacer muy útil su uso como herramienta de diagnosis y detección del despegue en su fase inicial mediante una monitorización de la variación de las características dinámicas locales de la estructura. Un método de evaluación no destructivo muy prometedor para la monitorización local de las estructuras es el método de la impedancia usando sensores-actuadores piezoeléctricos (PZT). La impedancia eléctrica de los sensores PZT se puede relacionar con la impedancia mecánica de las estructuras donde se encuentran adheridos Ya que la impedancia mecánica de una estructura se verá afectada por su deterioro, se pueden implementar indicadores de daño mediante una comparación del espectro de admitancia (inversa de la impedancia) a lo largo de distintas etapas durante el periodo de servicio de una estructura. Cualquier cambio en el espectro se podría interpretar como una variación en la integridad de la estructura. La impedancia eléctrica se mide a altas frecuencias con lo cual esta metodología debería ser muy sensible a la detección de estados de daño incipiente local, tal como se desea en la aplicación de este trabajo. Se ha implementado un elemento espectral PZT-FRP como extensión del modelo previamente desarrollado, con el objetivo de poder calcular numéricamente la impedancia eléctrica de sensores PZT adheridos a bandas de FRP sobre una viga de hormigón armado. El modelo, combinado con medidas experimentales captadas mediante sensores PZT, se implementa en el marco de una metodología de calibración de modelos para detectar cuantitativamente el despegue en la interfase entre una banda de FRP y una viga de hormigón. El procedimiento de optimización se resuelve empleando el método del enjambre cooperativo con un algoritmo bagging. Los resultados muestran una gran aproximación en la estimación del daño para el problema propuesto. Adicionalmente, se ha desarrollado también un método adaptativo para el mallado de elementos espectrales con el objetivo de localizar las zonas dañadas a partir de los resultados experimentales, el cual contribuye a aumentar la robustez y efectividad del método propuesto a la hora de identificar daños incipientes en su aparición inicial. Finalmente, se ha llevado a cabo un procedimiento de optimización multi-objetivo para detectar el despegue inicial en una viga de hormigón a escala real reforzada con FRP a partir de las impedancias captadas con una red de sensores PZT instrumentada a lo largo de la longitud de la viga. Cada sensor aporta los datos para definir cada una de las funciones objetivo que definen el procedimiento. Combinando el modelo previo de elementos espectrales con un algoritmo PSO multi-objetivo el procedimiento de detección de daño resultante proporciona resultados satisfactorios considerando la escala de la estructura y todas las incertidumbres características ligadas a este proceso. Los resultados obtenidos prueban la viabilidad y capacidad de los métodos antes mencionados y también su potencial en aplicaciones reales. Abstract Nowadays, the external bonding of fibre reinforced polymer (FRP) plates or sheets is increasingly used for the strengthening and retrofitting of reinforced concrete (RC) structures due to its numerous advantages. However, this kind of strengthening often leads to brittle failure modes being the most dominant failure mode the debonding induced by an intermediate crack (IC). In spite of its importance, the number of studies regarding the IC debonding mechanism and bond health monitoring is very limited. Methodologies able to monitor the long-term efficiency of bonding and successfully identify the initiation of FRP debonding constitute a challenge to be met. The main purpose of this thesisis the implementation of a reliable and effective methodology of damage identification able to detect intermediate crack debonding in FRP-strengthened RC beams. To achieve this goal, a model updating procedure based on numerical simulations and experimental tests has been implemented. For it, firstly, a simple and non-expensive one-dimensional model based on the discrete crack approach for concrete and the spectral element method has been developed. The progressive formation of flexural cracks and subsequent concrete-FRP interfacial debonding is formulated by the introduction of a new element able to represent both phenomena simultaneously without perturbing the numerical procedure. Furthermore, with the proposed model, high frequency dynamic response for these kinds of structures can also be obtained in a very simple and non-expensive way, which makes this procedure very useful as a tool for diagnoses and detection of debonding in its initial stage by monitoring the change in local dynamic characteristics. One very promising active non-destructive evaluation method for local monitoring is impedance-based structural health monitoring(SHM)using piezoelectric ceramic (PZT) sensor-actuators. The electrical impedance of the PZT can be directly related to the mechanical impedance of the host structural component where the PZT transducers are attached. Since the structural mechanical impedance will be affected by the presence of structural damage, comparisons of admittance (inverse of impedance) spectra at various times during the service period of the structure can be used as damage indicator. Any change in the spectra might be an indication of a change in the structural integrity. The electrical impedance is measured at high frequencies with which this methodology appears to be very sensitive to incipient damage in structural systems as desired for our application. Abonded-PZT-FRP spectral beam element approach based on an extension of the previous discrete crack approach is implemented in the calculation of the electrical impedance of the PZT transducer bonded to the FRP plates of a RC beam. This approach in conjunction with the experimental measurements of PZT actuator-sensors mounted on the structure is used to present an updating methodology to quantitatively detect interfacial debonding between a FRP strip and the host RC structure. The updating procedure is solved by using an ensemble particle swarm optimization approach with abagging algorithm, and the results demonstrate a big improvement for the performance and accuracy of the damage detection in the proposed problem. Additionally, an adaptive strategy of spectral element mesh has been also developed to detect damage location with experimental results, which shows the robustness and effectiveness of the proposed method to identify initial and incipient damages at its early stage. Lastly, multi-objective optimization has been carried out to detect debonding damage in a real scale FRP-strengthened RC beam by using impedance signatures. A net of PZT sensors is distributed along the beam to construct impedance-based multiple objectives under gradually induced damage scenario. By combining the spectral element model presented previously and an ensemble multi-objective PSO algorithm, the implemented damage detection process yields satisfactory predictions considering the scale and uncertainties of the structure. The obtained results prove the feasibility and capability of the aforementioned methods and also their potentials in real engineering applications.
Resumo:
Esta Tesis tiene como objetivo principal el desarrollo de métodos de identificación del daño que sean robustos y fiables, enfocados a sistemas estructurales experimentales, fundamentalmente a las estructuras de hormigón armado reforzadas externamente con bandas fibras de polímeros reforzados (FRP). El modo de fallo de este tipo de sistema estructural es crítico, pues generalmente es debido a un despegue repentino y frágil de la banda del refuerzo FRP originado en grietas intermedias causadas por la flexión. La detección de este despegue en su fase inicial es fundamental para prevenir fallos futuros, que pueden ser catastróficos. Inicialmente, se lleva a cabo una revisión del método de la Impedancia Electro-Mecánica (EMI), de cara a exponer sus capacidades para la detección de daño. Una vez la tecnología apropiada es seleccionada, lo que incluye un analizador de impedancias así como novedosos sensores PZT para monitorización inteligente, se ha diseñado un procedimiento automático basado en los registros de impedancias de distintas estructuras de laboratorio. Basándonos en el hecho de que las mediciones de impedancias son posibles gracias a una colocación adecuada de una red de sensores PZT, la estimación de la presencia de daño se realiza analizando los resultados de distintos indicadores de daño obtenidos de la literatura. Para que este proceso sea automático y que no sean necesarios conocimientos previos sobre el método EMI para realizar un experimento, se ha diseñado e implementado un Interfaz Gráfico de Usuario, transformando la medición de impedancias en un proceso fácil e intuitivo. Se evalúa entonces el daño a través de los correspondientes índices de daño, intentando estimar no sólo su severidad, sino también su localización aproximada. El desarrollo de estos experimentos en cualquier estructura genera grandes cantidades de datos que han de ser procesados, y algunas veces los índices de daño no son suficientes para una evaluación completa de la integridad de una estructura. En la mayoría de los casos se pueden encontrar patrones de daño en los datos, pero no se tiene información a priori del estado de la estructura. En este punto, se ha hecho una importante investigación en técnicas de reconocimiento de patrones particularmente en aprendizaje no supervisado, encontrando aplicaciones interesantes en el campo de la medicina. De ahí surge una idea creativa e innovadora: detectar y seguir la evolución del daño en distintas estructuras como si se tratase de un cáncer propagándose por el cuerpo humano. En ese sentido, las lecturas de impedancias se emplean como información intrínseca de la salud de la propia estructura, de forma que se pueden aplicar las mismas técnicas que las empleadas en la investigación del cáncer. En este caso, se ha aplicado un algoritmo de clasificación jerárquica dado que ilustra además la clasificación de los datos de forma gráfica, incluyendo información cualitativa y cuantitativa sobre el daño. Se ha investigado la efectividad de este procedimiento a través de tres estructuras de laboratorio, como son una viga de aluminio, una unión atornillada de aluminio y un bloque de hormigón reforzado con FRP. La primera ayuda a mostrar la efectividad del método en sencillos escenarios de daño simple y múltiple, de forma que las conclusiones extraídas se aplican sobre los otros dos, diseñados para simular condiciones de despegue en distintas estructuras. Demostrada la efectividad del método de clasificación jerárquica de lecturas de impedancias, se aplica el procedimiento sobre las estructuras de hormigón armado reforzadas con bandas de FRP objeto de esta tesis, detectando y clasificando cada estado de daño. Finalmente, y como alternativa al anterior procedimiento, se propone un método para la monitorización continua de la interfase FRP-Hormigón, a través de una red de sensores FBG permanentemente instalados en dicha interfase. De esta forma, se obtienen medidas de deformación de la interfase en condiciones de carga continua, para ser implementadas en un modelo de optimización multiobjetivo, cuya solución se haya por medio de una expansión multiobjetivo del método Particle Swarm Optimization (PSO). La fiabilidad de este último método de detección se investiga a través de sendos ejemplos tanto numéricos como experimentales. ABSTRACT This thesis aims to develop robust and reliable damage identification methods focused on experimental structural systems, in particular Reinforced Concrete (RC) structures externally strengthened with Fiber Reinforced Polymers (FRP) strips. The failure mode of this type of structural system is critical, since it is usually due to sudden and brittle debonding of the FRP reinforcement originating from intermediate flexural cracks. Detection of the debonding in its initial stage is essential thus to prevent future failure, which might be catastrophic. Initially, a revision of the Electro-Mechanical Impedance (EMI) method is carried out, in order to expose its capabilities for local damage detection. Once the appropriate technology is selected, which includes impedance analyzer as well as novel PZT sensors for smart monitoring, an automated procedure has been design based on the impedance signatures of several lab-scale structures. On the basis that capturing impedance measurements is possible thanks to an adequately deployed PZT sensor network, the estimation of damage presence is done by analyzing the results of different damage indices obtained from the literature. In order to make this process automatic so that it is not necessary a priori knowledge of the EMI method to carry out an experimental test, a Graphical User Interface has been designed, turning the impedance measurements into an easy and intuitive procedure. Damage is then assessed through the analysis of the corresponding damage indices, trying to estimate not only the damage severity, but also its approximate location. The development of these tests on any kind of structure generates large amounts of data to be processed, and sometimes the information provided by damage indices is not enough to achieve a complete analysis of the structural health condition. In most of the cases, some damage patterns can be found in the data, but none a priori knowledge of the health condition is given for any structure. At this point, an important research on pattern recognition techniques has been carried out, particularly on unsupervised learning techniques, finding interesting applications in the medicine field. From this investigation, a creative and innovative idea arose: to detect and track the evolution of damage in different structures, as if it were a cancer propagating through a human body. In that sense, the impedance signatures are used to give intrinsic information of the health condition of the structure, so that the same clustering algorithms applied in the cancer research can be applied to the problem addressed in this dissertation. Hierarchical clustering is then applied since it also provides a graphical display of the clustered data, including quantitative and qualitative information about damage. The performance of this approach is firstly investigated using three lab-scale structures, such as a simple aluminium beam, a bolt-jointed aluminium beam and an FRP-strengthened concrete specimen. The first one shows the performance of the method on simple single and multiple damage scenarios, so that the first conclusions can be extracted and applied to the other two experimental tests, which are designed to simulate a debonding condition on different structures. Once the performance of the impedance-based hierarchical clustering method is proven to be successful, it is then applied to the structural system studied in this dissertation, the RC structures externally strengthened with FRP strips, where the debonding failure in the interface between the FRP and the concrete is successfully detected and classified, proving thus the feasibility of this method. Finally, as an alternative to the previous approach, a continuous monitoring procedure of the FRP-Concrete interface is proposed, based on an FBGsensors Network permanently deployed within that interface. In this way, strain measurements can be obtained under controlled loading conditions, and then they are used in order to implement a multi-objective model updating method solved by a multi-objective expansion of the Particle Swarm Optimization (PSO) method. The feasibility of this last proposal is investigated and successfully proven on both numerical and experimental RC beams strengthened with FRP.
Resumo:
En la actualidad, cualquier compañía de telecomunicaciones que posea su propia red debe afrontar el problema del mantenimiento de la misma. Ofrecer un mínimo de calidad de servicio a sus clientes debe ser uno de sus objetivos principales. Esta calidad debe mantenerse aunque ocurran incidencias en la red. El presente trabajo pretende resolver el problema de priorizar el orden en que se restauran los cables, caminos y circuitos, dañados por una incidencia, dentro de una red troncal de transporte perteneciente a una operadora de telecomunicaciones. Tras un planteamiento detallado del problema y de todos los factores que influirán en la toma de decisión, en primer lugar se acomete una solución basada en Métodos Multicriterio Discretos, concretamente con el uso de ELECTRE I y AHP. A continuación se realiza una propuesta de solución basada en Redes Neuronales (con dos aproximaciones diferentes al problema). Por último se utiliza un método basado en la Optimización por Enjambre de Partículas (PSO), adaptado a un problema de permutación de enteros (ordenación), y con una forma particular de evaluar la mejor posición global del enjambre. Complementariamente se realiza una exposición de lo que es una empresa Operadora de telecomunicaciones, de sus departamentos y procesos internos, de los servicios que ofrece, de las redes sobre las que se soportan, y de los puntos clave a tener en cuenta en la implementación de sus sistemas informáticos de gestión integral. ABSTRACT: Nowadays, any telecommunications company that owns its own network must face the problem of maintaining it (service assurance). Provide a minimum quality of service to its customers must be one of its main objectives. This quality should be maintained although any incidents happen to occur in the network. This thesis aims to solve the problem of prioritizing the order in which the damaged cables, trails, path and circuits, within a backbone transport network, should be restored. This work begins with a detailed explanation about network maintenance issues and all the factors that influence decision-making problem. First of all, one solution based on Discrete Multicriteria methods is tried (ELECTRE I and AHP algorithms are used). Also, a solution based on neural networks (with two different approaches to the problem) is analyzed. Finally, this thesis proposes an algorithm based on Particle Swarm Optimization (PSO), adapted to a problem of integers permutation, and a particular way of evaluating the best overall position of the swarm method. In addition, there is included an exhibition about telecommunications companies, its departments, internal processes, services offered to clients, physical networks, and key points to consider when implementing its integrated management systems.
Resumo:
La riduzione dei consumi di combustibili fossili e lo sviluppo di tecnologie per il risparmio energetico sono una questione di centrale importanza sia per l’industria che per la ricerca, a causa dei drastici effetti che le emissioni di inquinanti antropogenici stanno avendo sull’ambiente. Mentre un crescente numero di normative e regolamenti vengono emessi per far fronte a questi problemi, la necessità di sviluppare tecnologie a basse emissioni sta guidando la ricerca in numerosi settori industriali. Nonostante la realizzazione di fonti energetiche rinnovabili sia vista come la soluzione più promettente nel lungo periodo, un’efficace e completa integrazione di tali tecnologie risulta ad oggi impraticabile, a causa sia di vincoli tecnici che della vastità della quota di energia prodotta, attualmente soddisfatta da fonti fossili, che le tecnologie alternative dovrebbero andare a coprire. L’ottimizzazione della produzione e della gestione energetica d’altra parte, associata allo sviluppo di tecnologie per la riduzione dei consumi energetici, rappresenta una soluzione adeguata al problema, che può al contempo essere integrata all’interno di orizzonti temporali più brevi. L’obiettivo della presente tesi è quello di investigare, sviluppare ed applicare un insieme di strumenti numerici per ottimizzare la progettazione e la gestione di processi energetici che possa essere usato per ottenere una riduzione dei consumi di combustibile ed un’ottimizzazione dell’efficienza energetica. La metodologia sviluppata si appoggia su un approccio basato sulla modellazione numerica dei sistemi, che sfrutta le capacità predittive, derivanti da una rappresentazione matematica dei processi, per sviluppare delle strategie di ottimizzazione degli stessi, a fronte di condizioni di impiego realistiche. Nello sviluppo di queste procedure, particolare enfasi viene data alla necessità di derivare delle corrette strategie di gestione, che tengano conto delle dinamiche degli impianti analizzati, per poter ottenere le migliori prestazioni durante l’effettiva fase operativa. Durante lo sviluppo della tesi il problema dell’ottimizzazione energetica è stato affrontato in riferimento a tre diverse applicazioni tecnologiche. Nella prima di queste è stato considerato un impianto multi-fonte per la soddisfazione della domanda energetica di un edificio ad uso commerciale. Poiché tale sistema utilizza una serie di molteplici tecnologie per la produzione dell’energia termica ed elettrica richiesta dalle utenze, è necessario identificare la corretta strategia di ripartizione dei carichi, in grado di garantire la massima efficienza energetica dell’impianto. Basandosi su un modello semplificato dell’impianto, il problema è stato risolto applicando un algoritmo di Programmazione Dinamica deterministico, e i risultati ottenuti sono stati comparati con quelli derivanti dall’adozione di una più semplice strategia a regole, provando in tal modo i vantaggi connessi all’adozione di una strategia di controllo ottimale. Nella seconda applicazione è stata investigata la progettazione di una soluzione ibrida per il recupero energetico da uno scavatore idraulico. Poiché diversi layout tecnologici per implementare questa soluzione possono essere concepiti e l’introduzione di componenti aggiuntivi necessita di un corretto dimensionamento, è necessario lo sviluppo di una metodologia che permetta di valutare le massime prestazioni ottenibili da ognuna di tali soluzioni alternative. Il confronto fra i diversi layout è stato perciò condotto sulla base delle prestazioni energetiche del macchinario durante un ciclo di scavo standardizzato, stimate grazie all’ausilio di un dettagliato modello dell’impianto. Poiché l’aggiunta di dispositivi per il recupero energetico introduce gradi di libertà addizionali nel sistema, è stato inoltre necessario determinare la strategia di controllo ottimale dei medesimi, al fine di poter valutare le massime prestazioni ottenibili da ciascun layout. Tale problema è stato di nuovo risolto grazie all’ausilio di un algoritmo di Programmazione Dinamica, che sfrutta un modello semplificato del sistema, ideato per lo scopo. Una volta che le prestazioni ottimali per ogni soluzione progettuale sono state determinate, è stato possibile effettuare un equo confronto fra le diverse alternative. Nella terza ed ultima applicazione è stato analizzato un impianto a ciclo Rankine organico (ORC) per il recupero di cascami termici dai gas di scarico di autovetture. Nonostante gli impianti ORC siano potenzialmente in grado di produrre rilevanti incrementi nel risparmio di combustibile di un veicolo, è necessario per il loro corretto funzionamento lo sviluppo di complesse strategie di controllo, che siano in grado di far fronte alla variabilità della fonte di calore per il processo; inoltre, contemporaneamente alla massimizzazione dei risparmi di combustibile, il sistema deve essere mantenuto in condizioni di funzionamento sicure. Per far fronte al problema, un robusto ed efficace modello dell’impianto è stato realizzato, basandosi sulla Moving Boundary Methodology, per la simulazione delle dinamiche di cambio di fase del fluido organico e la stima delle prestazioni dell’impianto. Tale modello è stato in seguito utilizzato per progettare un controllore predittivo (MPC) in grado di stimare i parametri di controllo ottimali per la gestione del sistema durante il funzionamento transitorio. Per la soluzione del corrispondente problema di ottimizzazione dinamica non lineare, un algoritmo basato sulla Particle Swarm Optimization è stato sviluppato. I risultati ottenuti con l’adozione di tale controllore sono stati confrontati con quelli ottenibili da un classico controllore proporzionale integrale (PI), mostrando nuovamente i vantaggi, da un punto di vista energetico, derivanti dall’adozione di una strategia di controllo ottima.
Resumo:
Measurement and variation control of geometrical Key Characteristics (KCs), such as flatness and gap of joint faces, coaxiality of cabin sections, is the crucial issue in large components assembly from the aerospace industry. Aiming to control geometrical KCs and to attain the best fit of posture, an optimization algorithm based on KCs for large components assembly is proposed. This approach regards the posture best fit, which is a key activity in Measurement Aided Assembly (MAA), as a two-phase optimal problem. In the first phase, the global measurement coordinate system of digital model and shop floor is unified with minimum error based on singular value decomposition, and the current posture of components being assembly is optimally solved in terms of minimum variation of all reference points. In the second phase, the best posture of the movable component is optimally determined by minimizing multiple KCs' variation with the constraints that every KC respectively conforms to its product specification. The optimal models and the process procedures for these two-phase optimal problems based on Particle Swarm Optimization (PSO) are proposed. In each model, every posture to be calculated is modeled as a 6 dimensional particle (three movement and three rotation parameters). Finally, an example that two cabin sections of satellite mainframe structure are being assembled is selected to verify the effectiveness of the proposed approach, models and algorithms. The experiment result shows the approach is promising and will provide a foundation for further study and application. © 2013 The Authors.
Resumo:
The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.
Resumo:
The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.
Resumo:
Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.
Resumo:
Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.
Resumo:
This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.
Resumo:
La tesi presenta un'attività di ottimizzazione per forme di dirigibili non convenzionali al fine di esaltarne alcune prestazioni. Il loop di ottimizzazione implementato comporta il disegno automatico in ambiente CAD del dirigibile, il salvataggio in formato STL, la elaborazione del modello al fine di ridurre il numero di triangoli della mesh, la valutazione delle masse aggiunte della configurazione, la stima approssimata dell'aerodinamica del dirigibile, ed infine il calcolo della prestazione di interesse. Questa tesi presenta inoltre la descrizione di un codice di ottimizzazione euristica (Particle Swarm Optimization) che viene messo in loop con il precedente ciclo di calcolo, e un caso di studio per dimostrare la funzionalità della metodologia.