Study of the increase in bending stiffness on timber beams reinforced with composite materials

It is common to find structures that need to be reinforced due to deterioration or because the function of the building changes. The economic cost involved in these forms of interventions is considerable. Therefore, it is interesting to progress in the existing strengthening techniques and the study of new reinforcement systems. This paper analyses the behaviour of timber beams reinforced with carbon and basalt fiber composite materials. The main objective of this study is to test the stiffness increase produced by the carbon and basalt FRP on reinforced beams. The results show the stiffness increase produced by the different types of reinforcement.

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.

Comparison of push-in and push-out tests for measuring interfacial shear strength in nano-reinforced composite materials

The influence of the carbon nanotubes (CNTs) content on the fiber/matrix interfacial shear strength (IFSS) in glass/fiber epoxy composites was measured by means of push-in and push-out tests. Both experimental methodologies provided equivalent values of the IFSS for each material. It was found that the dispersion of CNTs increased in IFSS by 19% in average with respect to the composite without CNTs. This improvement was reached with 0.3 wt.% of CNTs and increasing the CNT content up to 0.8 wt.% did not improve the interface strength.

Determination of optimal parameters in drilling composite materials to minimize the machining temperature using the Taguchi method

Dental implant is used to replace the natural dental root. The process to fix the dental implant in the maxillary bone needs a previous drilling operation. This machining operation involves the increasing of temperature in the drilled region which can reach values higher than 47°C and for this temperature is possible to occur the osseous necrosis [I]. The main goal of this work is to implement an optimization method to define the optimal drilling parameters that could minimize the drilling temperature. The proposal optimization method is the Taguchi method. This method has been used with success in machining processes optimization of metallic materials [2]. However, the Taguchi method is also used in medical applications, namely in dental medicine [3].

Experimental and numerical simulation of the use of fiber reinforced composite materials for road side safety applications /

"May 1997."

Crashworthiness and scaling issues in using composite materials for guardrail applications /

"June 1995."

Impact characteristics of glass fiber-reinforced composite materials for use in roadside safety barriers /

"January 1994."

Impact characteristics of glass fiber-reinforced composite materials for use in roadside safety barriers. Final report.

Federal Highway Administration, McLean Va.

Mechanics of composite materials

Most of the pages of the photocopy, which are in double columns, represent two pages of the original.

Automotive applications of composite materials. Final report.

Corporate-Tech Planning, Inc., Waltham, Mass.

Beryllium research and development in the area of composite materials

"Materials Central, Contract No. AF 33(616)-5912, Project No. 7351."

Some aspects of the microbiological properties of polymers and composite materials

The interaction of microorganisms with glass-reinforced polyester resins(GRP), both under laboratory and simulated operating conditions, has been examined following reports of severl! fungal biodeterioration. Although GRP was not previously associated with substantial microbial growth, small amounts of microbial activity would pose problems for products associated with comestible materials. The microbiology of the raw materials was investigated, two ingredients were supportive to microbial populations whilst five materials were biostatic or inhibitory in their action. Production laminate was not susceptible to microbial deterioration or inhibitory to microbes. Incorporation of zinc stearate, one of the supportive ingredients, at 300% manufacturing level or drastic undercuring produced laminate capable of supporting microbial growth but only after a non-biotic stage of degradation. Study of the long-term population dynamics of cisterns of GRP and competitive materials under conditions simulating in-service conditions, monitoring microbial numbers within the experimental vessels and comparing with the populations of the supply water, suggests that the performance of GRP cisterns is slightly superior to conventional competitive materials. An investigation of the biological performance of GRP cisterns in an isolated area of known microbiological hazard was conducted. Severe biodeterioration had been experienced with Preform GRP articles moulded using different production techniques, but substitution of current GRP articles resulted in no recurrence of the problem. All attempts to establish the fungal isolate responsible for the phenomena in cisterns under controlled conditions failed. Scanning Electron Microscopy of GRP surfaces showed that although differences exist between current and Preform laminates, these could not satisfactorily explain the differences in service behaviour. These results and the results of the British Plastics Federation Expert Working Group interlaboratory study are discussed in relation to the original report of gross fungal biodeterioration and, to the design of future testing programmes for the products of industrial concerns.

Composite materials impact damage detection using neural networks

This thesis considers two basic aspects of impact damage in composite materials, namely damage severity discrimination and impact damage location by using Acoustic Emissions (AE) and Artificial Neural Networks (ANNs). The experimental work embodies a study of such factors as the application of AE as Non-destructive Damage Testing (NDT), and the evaluation of ANNs modelling. ANNs, however, played an important role in modelling implementation. In the first aspect of the study, different impact energies were used to produce different level of damage in two composite materials (T300/914 and T800/5245). The impacts were detected by their acoustic emissions (AE). The AE waveform signals were analysed and modelled using a Back Propagation (BP) neural network model. The Mean Square Error (MSE) from the output was then used as a damage indicator in the damage severity discrimination study. To evaluate the ANN model, a comparison was made of the correlation coefficients of different parameters, such as MSE, AE energy, AE counts, etc. MSE produced an outstanding result based on the best performance of correlation. In the second aspect, a new artificial neural network model was developed to provide impact damage location on a quasi-isotropic composite panel. It was successfully trained to locate impact sites by correlating the relationship between arriving time differences of AE signals at transducers located on the panel and the impact site coordinates. The performance of the ANN model, which was evaluated by calculating the distance deviation between model output and real location coordinates, supports the application of ANN as an impact damage location identifier. In the study, the accuracy of location prediction decreased when approaching the central area of the panel. Further investigation indicated that this is due to the small arrival time differences, which defect the performance of ANN prediction. This research suggested increasing the number of processing neurons in the ANNs as a practical solution.

The mechanical and wear behaviour of B(SiC) fibre-reinforced composite materials

The mechanical properties and wear behaviour of B(SiC) fibre-reinforced metal matrix composites (MMCs) and aluminium alloy (2014) produced by metal infiltration technique were determined. Tensile tests were peliormed at different conditions on both the alloy matrix and its composite, and the tensile fracture surfaces were also examined by Scanning Electron Microscopy (SEM). Dry wear of the composite materials sliding on hardened steel was studied using a pin-on-disc type machine. The effect of fibre orientation on wear rate was studied to provide wear resistance engineering data on the MMCs. Tests were carried out with the wear surface sliding direction set normal, parallel and anti-parallel to the fibre axis. Experiments were perfonned for sliding speeds of 0.6, 1.0 and 1.6 m/s for a load range from 12 N to 60 N. A number of sensitive techniques were used to examine worn surface and debris, i.e: Scanning Electron Microscopy (SEM), Backscattered Electron Microscopy (BSEM) and X-ray Photoelectron Spectroscopy (XPS). Finally, the effect of fibre orientation on the wear rate of the Borsic-reinforced plastic matrix composites (PMCs) produced by hot pressing technique was also investigated under identical test conditions. It was found that the composite had a markedly increased tensile strength compared with the matrix. The wear results also showed that the composite exhibited extremely low wear rates compared to the matrix material and the wear rate increased with increasing sliding speed and normal load. The effect of fibre orientation was marked, the lowest wear rates were obtained by arranging the fibre perpendicular to the sliding surface, while the highest wear was obtained for the parallel orientation. The coefficient of friction was found to be lowest in the parallel orientation than the others. Wear of PMCs were influenced to the greatest extent by these test parameters although similar findings were obtained for both composites. Based on the results of analyses using SEM, BSED and XPS, possible wear mechanisms are suggested to explain the wear of these materials.

Failure in composite materials

The economic and efficient exploitation of composite materials in critical load bearing applications relies on the ability to predict safe operational lives without excessive conservatism. Developing life prediction and monitoring techniques in these complex, inhomogeneous materials requires an understanding of the various failure mechanisms which can take place. This article describes a range of damage mechanisms which are observed in polymer, metal and ceramic matrix composites.