Comparación de un nuevo método de aceleración de análisis dinámicos con métodos de reducción de modelos

La dinámica estructural estudia la respuesta de una estructura ante cargas o fenómenos variables en el tiempo. En muchos casos, estos fenómenos requieren realizar análisis paramétricos de la estructura considerando una gran cantidad de configuraciones de diseño o modificaciones de la estructura. Estos cambios, ya sean en fases iniciales de diseño o en fases posteriores de rediseño, alteran las propiedades físicas de la estructura y por tanto del modelo empleado para su análisis, cuyo comportamiento dinámico se modifica en consecuencia. Un caso de estudio de este tipo de modificaciones es la supervisión de la integridad estructural, que trata de identificar la presencia de daño estructural y prever el comportamiento de la estructura tras ese daño, como puede ser la variación del comportamiento dinámico de la estructura debida a una delaminación, la aparición o crecimiento de grieta, la debida a la pérdida de pala sufrida por el motor de un avión en vuelo, o la respuesta dinámica de construcciones civiles como puentes o edificios frente a cargas sísmicas. Si a la complejidad de los análisis dinámicos requeridos en el caso de grandes estructuras se añade la variación de determinados parámetros en busca de una respuesta dinámica determinada o para simular la presencia de daños, resulta necesario la búsqueda de medios de simplificación o aceleración del conjunto de análisis que de otra forma parecen inabordables tanto desde el punto de vista del tiempo de computación, como de la capacidad requerida de almacenamiento y manejo de grandes volúmenes de archivos de datos. En la presente tesis doctoral se han revisado los métodos de reducción de elementos .nitos más habituales para análisis dinámicos de grandes estructuras. Se han comparado los resultados de casos de estudio de los métodos más aptos, para el tipo de estructuras y modificaciones descritas, con los resultados de aplicación de un método de reducción reciente. Entre los primeros están el método de condensación estática de Guyan extendido al caso con amortiguamiento no proporcional y posteriores implementaciones de condensaciones dinámicas en diferentes espacios vectoriales. El método de reducción recientemente presentado se denomina en esta tesis DACMAM (Dynamic Analysis in Complex Modal space Acceleration Method), y consiste en el análisis simplificado que proporciona una solución para la respuesta dinámica de una estructura, calculada en el espacio modal complejo y que admite modificaciones estructurales. El método DACMAM permite seleccionar un número reducido de grados de libertad significativos para la dinámica del fenómeno que se quiere estudiar como son los puntos de aplicación de la carga, localizaciones de los cambios estructurales o puntos donde se quiera conocer la respuesta, de forma que al implementar las modificaciones estructurales, se ejecutan los análisis necesarios sólo de dichos grados de libertad sin pérdida de precisión. El método permite considerar alteraciones de masa, rigidez, amortiguamiento y la adición de nuevos grados de libertad. Teniendo en cuenta la dimensión del conjunto de ecuaciones a resolver, la parametrización de los análisis no sólo resulta posible, sino que es también manejable y controlable gracias a la sencilla implementación del procedimiento para los códigos habituales de cálculo mediante elementos .nitos. En el presente trabajo se muestra la bondad y eficiencia del método en comparación con algunos de los métodos de reducción de grandes modelos estructurales, verificando las diferencias entre sí de los resultados obtenidos y respecto a la respuesta real de la estructura, y comprobando los medios empleados en ellos tanto en tiempo de ejecución como en tamaño de ficheros electrónicos. La influencia de los diversos factores que se tienen en cuenta permite identificar los límites y capacidades de aplicación del método y su exhaustiva comparación con los otros procedimientos. ABSTRACT Structural dynamics studies the response of a structure under loads or phenomena which vary over time. In many cases, these phenomena require the use of parametric analyses taking into consideration several design configurations or modifications of the structure. This is a typical need in an engineering o¢ ce, no matter the structural design is in early or final stages. These changes modify the physical properties of the structure, and therefore, the finite element model to analyse it. A case study, that exempli.es this circumstance, is the structural health monitoring to predict the variation of the dynamical behaviour after damage, such as a delaminated structure, a crack onset or growth, an aircraft that suffers a blade loss event or civil structures (buildings or bridges) under seismic loads. Not only large structures require complex analyses to appropriately acquire an accurate solution, but also the variation of certain parameters. There is a need to simplify the analytical process, in order to bring CPU time, data .les, management of solutions to a reasonable size. In the current doctoral thesis, the most common finite element reduction methods for large structures are reviewed. Results of case studies are compared between a recently proposed method, herein named DACMAM (Dynamic Analysis in Complex Modal space Acceleration Method), and different condensation methods, namely static or Guyan condensation and dynamic condensation in different vectorial spaces. All these methods are suitable for considering non-classical damping. The reduction method DACMAM consist of a structural modification in the complex modal domain which provides a dynamic response solution for the reduced models. This process allows the selection of a few degrees of freedom that are relevant for the dynamic response of the system. These d.o.f. are the load application points, relevant structural points or points in which it is important to know the response. Consequently, an analysis with structural modifications implies only the calculation of the dynamic response of the selected degrees of freedom added, but with no loss of information. Therefore, mass, stiffness or damping modifications are easily considered as well as new degrees of freedom. Taking into account the size of the equations to be solved, the parameterization of the dynamic solutions is not only possible, but also manageable and controllable due to the easy implementation of the procedure in the standard finite element solvers. In this thesis, the proposed reduction method for large structural models is compared with other published model order reduction methods. The comparison shows and underlines the efficiency of the new method, and veri.es the differences in the response when compared with the response of the full model. The CPU time, the data files and the scope of the parameterization are also addressed.

Optical sensing of the fatigue damage state of CFRP under realistic aeronautical load sequences

We present an optical sensing methodology to estimate the fatigue damage state of structures made of carbon fiber reinforced polymer (CFRP), by measuring variations on the surface roughness. Variable amplitude loads (VAL), which represent realistic loads during aeronautical missions of fighter aircraft (FALSTAFF) have been applied to coupons until failure. Stiffness degradation and surface roughness variations have been measured during the life of the coupons obtaining a Pearson correlation of 0.75 between both variables. The data were compared with a previous study for Constant Amplitude Load (CAL) obtaining similar results. Conclusions suggest that the surface roughness measured in strategic zones is a useful technique for structural health monitoring of CFRP structures, and that it is independent of the type of load applied. Surface roughness can be measured in the field by optical techniques such as speckle, confocal perfilometers and interferometry, among others.

Visual grading of large cross section structural timber of Pinus sylvestris L. according to UNE 56544:2007 standard

Large cross section structural timber have been used in many structures over long periods of time and still make up an important part of the market due to its mechanical properties. Furthermore, it is frequent its employment in new construction site. It involves the need for a visual grading standard for timber used in construction according to the quality assessment. The material has to satisfy the requirements according to the currently regulations. UNE 56544 is the Spanish visual grading standard for coniferous structural timber. The 2007 version defined a new visual grade in the standard for large section termed Structural Large Timber (MEG). This research checks the new visual grading and consists of 116 structural size specimens of sawn coniferous timber of Scotch pine (Pinus sylvestris L.) from Segovia, Spain. The pieces had a cross section of 150 by 200 mm. They were visually graded according to UNE 56544:2007. Also, mechanical properties have been obtained according to standard EN 408. The results show very low output with an excessive percentage of rejected pieces (33%). The main reasons for the rejection of pieces are fissures and twist

Some advances in extensive bridge monitoring using low cost dynamic characterization

Dynamic measurements will become a standard for bridge monitoring in the near future. This fact will produce an important cost reduction for maintenance. US Administration has a long term intensive research program in order to diminish the estimated current maintenance cost of US$7 billion per year over 20 years. An optimal intervention maintenance program demands a historical dynamical record, as well as an updated mathematical model of the structure to be monitored. In case that a model of the structure is not actually available it is possible to produce it, however this possibility does not exist for missing measurement records from the past. Current acquisition systems to monitor structures can be made more efficient by introducing the following improvements, under development in the Spanish research Project “Low cost bridge health monitoring by ambient vibration tests using wireless sensors”: (a) a complete wireless system to acquire sensor data, (b) a wireless system that permits the localization and the hardware identification of the whole sensor system. The applied localization system has been object of a recent patent, and (c) automatization of the modal identification process, aimed to diminish human intervention. This system is assembled with cheap components and allows the simultaneous use of a large number of sensors at a low placement cost. The engineer’s intervention is limited to the selection of sensor positions, probably based on a preliminary FE analysis. In case of multiple setups, also the position of a number of fixed reference sensors has to be decided. The wireless localization system will obtain the exact coordinates of all these sensors positions. When the selection of optimal positions is difficult, for example because of the lack of a proper FE model, this can be compensated by using a higher number of measuring (also reference) points. The described low cost acquisition system allows the responsible bridge administration to obtain historical dynamic identification records at reasonable costs that will be used in future maintenance programs. Therefore, due to the importance of the baseline monitoring record of a new bridge, a monitoring test just after its construction should be highly recommended, if not compulsory.

Model-Driven Methodology for Rapid Deployment of Smart Spaces based on Resource-Oriented Architectures

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

Integrated luminescent chemical microsensors based on GaN LEDs for security applications using smartphones

Development of PCB-integrateable microsensors for monitoring chemical species is a goal in areas such as lab-on-a-chip analytical devices, diagnostics medicine and electronics for hand-held instruments where the device size is a major issue. Cellular phones have pervaded the world inhabitants and their usefulness has dramatically increased with the introduction of smartphones due to a combination of amazing processing power in a confined space, geolocalization and manifold telecommunication features. Therefore, a number of physical and chemical sensors that add value to the terminal for health monitoring, personal safety (at home, at work) and, eventually, national security have started to be developed, capitalizing also on the huge number of circulating cell phones. The chemical sensor-enabled “super” smartphone provides a unique (bio)sensing platform for monitoring airborne or waterborne hazardous chemicals or microorganisms for both single user and crowdsourcing security applications. Some of the latest ones are illustrated by a few examples. Moreover, we have recently achieved for the first time (covalent) functionalization of p- and n-GaN semiconductor surfaces with tuneable luminescent indicator dyes of the Ru-polypyridyl family, as a key step in the development of innovative microsensors for smartphone applications. Chemical “sensoring” of GaN-based blue LED chips with those indicators has also been achieved by plasma treatment of their surface, and the micrometer-sized devices have been tested to monitor O2 in the gas phase to show their full functionality. Novel strategies to enhance the sensor sensitivity such as changing the length and nature of the siloxane buffer layer are discussed in this paper.

Algoritmos de agrupación para flujos de datos en entornos centralizados y distribuidos

Los avances en el hardware permiten disponer de grandes volúmenes de datos, surgiendo aplicaciones que deben suministrar información en tiempo cuasi-real, la monitorización de pacientes, ej., el seguimiento sanitario de las conducciones de agua, etc. Las necesidades de estas aplicaciones hacen emerger el modelo de flujo de datos (data streaming) frente al modelo almacenar-para-despuésprocesar (store-then-process). Mientras que en el modelo store-then-process, los datos son almacenados para ser posteriormente consultados; en los sistemas de streaming, los datos son procesados a su llegada al sistema, produciendo respuestas continuas sin llegar a almacenarse. Esta nueva visión impone desafíos para el procesamiento de datos al vuelo: 1) las respuestas deben producirse de manera continua cada vez que nuevos datos llegan al sistema; 2) los datos son accedidos solo una vez y, generalmente, no son almacenados en su totalidad; y 3) el tiempo de procesamiento por dato para producir una respuesta debe ser bajo. Aunque existen dos modelos para el cómputo de respuestas continuas, el modelo evolutivo y el de ventana deslizante; éste segundo se ajusta mejor en ciertas aplicaciones al considerar únicamente los datos recibidos más recientemente, en lugar de todo el histórico de datos. En los últimos años, la minería de datos en streaming se ha centrado en el modelo evolutivo. Mientras que, en el modelo de ventana deslizante, el trabajo presentado es más reducido ya que estos algoritmos no sólo deben de ser incrementales si no que deben borrar la información que caduca por el deslizamiento de la ventana manteniendo los anteriores tres desafíos. Una de las tareas fundamentales en minería de datos es la búsqueda de agrupaciones donde, dado un conjunto de datos, el objetivo es encontrar grupos representativos, de manera que se tenga una descripción sintética del conjunto. Estas agrupaciones son fundamentales en aplicaciones como la detección de intrusos en la red o la segmentación de clientes en el marketing y la publicidad. Debido a las cantidades masivas de datos que deben procesarse en este tipo de aplicaciones (millones de eventos por segundo), las soluciones centralizadas puede ser incapaz de hacer frente a las restricciones de tiempo de procesamiento, por lo que deben recurrir a descartar datos durante los picos de carga. Para evitar esta perdida de datos, se impone el procesamiento distribuido de streams, en concreto, los algoritmos de agrupamiento deben ser adaptados para este tipo de entornos, en los que los datos están distribuidos. En streaming, la investigación no solo se centra en el diseño para tareas generales, como la agrupación, sino también en la búsqueda de nuevos enfoques que se adapten mejor a escenarios particulares. Como ejemplo, un mecanismo de agrupación ad-hoc resulta ser más adecuado para la defensa contra la denegación de servicio distribuida (Distributed Denial of Services, DDoS) que el problema tradicional de k-medias. En esta tesis se pretende contribuir en el problema agrupamiento en streaming tanto en entornos centralizados y distribuidos. Hemos diseñado un algoritmo centralizado de clustering mostrando las capacidades para descubrir agrupaciones de alta calidad en bajo tiempo frente a otras soluciones del estado del arte, en una amplia evaluación. Además, se ha trabajado sobre una estructura que reduce notablemente el espacio de memoria necesario, controlando, en todo momento, el error de los cómputos. Nuestro trabajo también proporciona dos protocolos de distribución del cómputo de agrupaciones. Se han analizado dos características fundamentales: el impacto sobre la calidad del clustering al realizar el cómputo distribuido y las condiciones necesarias para la reducción del tiempo de procesamiento frente a la solución centralizada. Finalmente, hemos desarrollado un entorno para la detección de ataques DDoS basado en agrupaciones. En este último caso, se ha caracterizado el tipo de ataques detectados y se ha desarrollado una evaluación sobre la eficiencia y eficacia de la mitigación del impacto del ataque. ABSTRACT Advances in hardware allow to collect huge volumes of data emerging applications that must provide information in near-real time, e.g., patient monitoring, health monitoring of water pipes, etc. The data streaming model emerges to comply with these applications overcoming the traditional store-then-process model. With the store-then-process model, data is stored before being consulted; while, in streaming, data are processed on the fly producing continuous responses. The challenges of streaming for processing data on the fly are the following: 1) responses must be produced continuously whenever new data arrives in the system; 2) data is accessed only once and is generally not maintained in its entirety, and 3) data processing time to produce a response should be low. Two models exist to compute continuous responses: the evolving model and the sliding window model; the latter fits best with applications must be computed over the most recently data rather than all the previous data. In recent years, research in the context of data stream mining has focused mainly on the evolving model. In the sliding window model, the work presented is smaller since these algorithms must be incremental and they must delete the information which expires when the window slides. Clustering is one of the fundamental techniques of data mining and is used to analyze data sets in order to find representative groups that provide a concise description of the data being processed. Clustering is critical in applications such as network intrusion detection or customer segmentation in marketing and advertising. Due to the huge amount of data that must be processed by such applications (up to millions of events per second), centralized solutions are usually unable to cope with timing restrictions and recur to shedding techniques where data is discarded during load peaks. To avoid discarding of data, processing of streams (such as clustering) must be distributed and adapted to environments where information is distributed. In streaming, research does not only focus on designing for general tasks, such as clustering, but also in finding new approaches that fit bests with particular scenarios. As an example, an ad-hoc grouping mechanism turns out to be more adequate than k-means for defense against Distributed Denial of Service (DDoS). This thesis contributes to the data stream mining clustering technique both for centralized and distributed environments. We present a centralized clustering algorithm showing capabilities to discover clusters of high quality in low time and we provide a comparison with existing state of the art solutions. We have worked on a data structure that significantly reduces memory requirements while controlling the error of the clusters statistics. We also provide two distributed clustering protocols. We focus on the analysis of two key features: the impact on the clustering quality when computation is distributed and the requirements for reducing the processing time compared to the centralized solution. Finally, with respect to ad-hoc grouping techniques, we have developed a DDoS detection framework based on clustering.We have characterized the attacks detected and we have evaluated the efficiency and effectiveness of mitigating the attack impact.

Discrimination of AE Signals From Friction and Concrete Cracking in a Reinforced Concrete Frame Subjected to Seismic Trainings

This paper shows the preliminary results of the development and application of a procedure to filter the Acoustic Emission (AE) signals to distinguish between AE signals coming from friction and AE signals coming from concrete cracking. These signals were recorded during the trainings of an experiment carried out on a reinforced concrete frame subjected to dynamic loadings with the shaking table of the University of Granada (Spain). Discrimination between friction and cracking AE signals is the base to develop a successful procedure and damage index based on AE testing for health monitoring of RC structures subjected to earthquakes.

Monitoring maximum peak power density values as a more reliable marker for measurement procedures to elucidate RF EMF health effects: Leganes project

Considering the measurement procedures recommended by the ICNIRP, this communication is a proposal for a measurement procedure based in the maximum peak values of equivalent plane wave power density. This procedure has been included in a project being developed in Leganés, Spain. The project plans to deploy a real time monitoring system for RF to provide the city with a useful tool to adapt the environmental EM conditions to the new regulations approved. A first stage consisting of 105 measurement points has been finished and all the values are under the threshold of the regulation.