Debonding identification in FRP-plated RC structures using PZT sensors

The application of the Electro-Mechanical Impedance (EMI) method for damage detection in Structural Health Monitoring has noticeable increased in recent years. EMI method utilizes piezoelectric transducers for directly measuring the mechanical properties of the host structure, obtaining the so called impedance measurement, highly influenced by the variations of dynamic parameters of the structure. These measurements usually contain a large number of frequency points, as well as a high number of dimensions, since each frequency range swept can be considered as an independent variable. That makes this kind of data hard to handle, increasing the computational costs and being substantially time-consuming. In that sense, the Principal Component Analysis (PCA)-based data compression has been employed in this work, in order to enhance the analysis capability of the raw data. Furthermore, a Support Vector Machine (SVM), which has been widespread used in machine learning and pattern recognition fields, has been applied in this study in order to model any possible existing pattern in the PCAcompress data, using for that just the first two Principal Components. Different known non-damaged and damaged measurements of an experimental tested beam were used as training input data for the SVM algorithm, using as test input data the same amount of cases measured in beams with unknown structural health conditions. Thus, the purpose of this work is to demonstrate how, with a few impedance measurements of a beam as raw data, its healthy status can be determined based on pattern recognition procedures.

Application of PZT and FBG impedance sensors for structural health monitoring of reinforced concrete beams strengthened with FRP composite materials

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.

The Composition and Drivers of Energy Prices and Costs in Energy-Intensive Industries: The Case of Ceramics, Glass and Chemicals. CEPS Special Report No. 85, 27 March 2014

In May 2013, the European Commission received a mandate from the European Council to “to present an analysis of the composition and drivers of energy prices and costs in Member States, with a particular focus on the impact on households, SMEs and energy intensive industries, and looking more widely at the EU's competitiveness vis-à-vis its global economic counterparts”. Following such mandate and in view of the preparation by the Commission of a Communication and a Staff Working Document, DG Enterprise and Industry commissioned CEPS to carry out a set of studies aimed at providing well-grounded evidence about the evolution and composition of energy prices and costs at plant level within individual industry sectors. A team of CEPS researchers conducted the research, led by Christian Egenhofer and Lorna Schrefler. Vasileios Rizos served as Project Coordinator. Other CEPS researchers contributing to the project included: Fabio Genoese, Andrea Renda, Andrei Marcu, Julian Wieczorkiewicz, Susanna Roth, Federico Infelise, Giacomo Luchetta, Lorenzo Colantoni, Wijnand Stoefs, Jacopo Timini and Felice Simonelli. In addition to an introductory report entitled “About the Study and Cross-Sectoral Analysis”, CEPS prepared five sectoral case studies: two on ceramics (wall and floor tiles and bricks and roof tiles), two on chemicals (ammonia and chlorine) and one on flat glass. Each of these six studies has been consolidated in this single volume for free downloading on the CEPS website. The specific objective was to complement information already available at macro level with a bottom-up perspective on the operating conditions that industry stakeholders need to deal with, in terms of energy prices and costs. The approach chosen was based on case studies for a selected set (sub-)sectors amongst energy-intensive industries. A standard questionnaire was circulated and respondents were sampled according to specified criteria. Data and information collected were finally presented in a structured format in order to guarantee comparability of results between the different (sub-)sectors analysed. The complete set of files can also be downloaded from the European Commission’s website: http://ec.europa.eu/enterprise/newsroom/cf/itemdetail.cfm?item_id=7238&lang=en&title=Study-on-composition-and-drivers-of-energy-prices-and-costs-in-energy-intnsive-industries The results of the studies were presented at a CEPS Conference held on February 26th along with additional evidence from other similar studies. The presentations can be downloaded at: http://www.ceps.eu/event/level-and-drivers-eu-energy-prices-energy-inten...

Summaries of physical research in research in metallurgy, solid state physics and ceramics.

"January 1957 (TISE Issuance Date)."

Summaries of physical research in research in metallurgy, solid state physics and ceramics.

"July 1959 (TIS Issuance Date)."

Summaries of the UDAEC basic research programs in metallurgy, solid state physics and ceramics.

"January 1964 (DTIE Issuance Date)."

Summaries of the UDAEC basic research programs in metallurgy, solid state physics and ceramics : (fiscal year 1964)

"January 1965 (DTIE Issuance Date)."

Asiatic Art, VII century B.C.-XVIII century A.D., including sculpture in bronze & stone, ceramics, miniatures and textiles.

Exhibition and sale at the American Art Galleries, New York.

Summaries of the UDAEC basic research programs in metallurgy, solid state physics and ceramics.

"June 1961 (OIT Issuance Date)."

Transformation toughened ceramics for the Heavy Duty Diesel Engine Technology Program.

Energy Department, Office of Vehicle and Engine Research and Development, Washington, D.C.

Opportunities for advanced ceramics to meet the needs of the industries of the future /

"DOE/ORO 2076."