Curing, defects and mechanical performance of fiber-reinforced composites

Tradicionalmente, la fabricación de materiales compuestos de altas prestaciones se lleva a cabo en autoclave mediante la consolidación de preimpregnados a través de la aplicación simultánea de altas presiones y temperatura. Las elevadas presiones empleadas en autoclave reducen la porosidad de los componentes garantizando unas buenas propiedades mecánicas. Sin embargo, este sistema de fabricación conlleva tiempos de producción largos y grandes inversiones en equipamiento lo que restringe su aplicación a otros sectores alejados del sector aeronáutico. Este hecho ha generado una creciente demanda de sistemas de fabricación alternativos al autoclave. Aunque estos sistemas son capaces de reducir los tiempos de producción y el gasto energético, por lo general, dan lugar a materiales con menores prestaciones mecánicas debido a que se reduce la compactación del material al aplicar presiones mas bajas y, por tanto, la fracción volumétrica de fibras, y disminuye el control de la porosidad durante el proceso. Los modelos numéricos existentes permiten conocer los fundamentos de los mecanismos de crecimiento de poros durante la fabricación de materiales compuestos de matriz polimérica mediante autoclave. Dichos modelos analizan el comportamiento de pequeños poros esféricos embebidos en una resina viscosa. Su validez no ha sido probada, sin embargo, para la morfología típica observada en materiales compuestos fabricados fuera de autoclave, consistente en poros cilíndricos y alargados embebidos en resina y rodeados de fibras continuas. Por otro lado, aunque existe una clara evidencia experimental del efecto pernicioso de la porosidad en las prestaciones mecánicas de los materiales compuestos, no existe información detallada sobre la influencia de las condiciones de procesado en la forma, fracción volumétrica y distribución espacial de los poros en los materiales compuestos. Las técnicas de análisis convencionales para la caracterización microestructural de los materiales compuestos proporcionan información en dos dimensiones (2D) (microscopía óptica y electrónica, radiografía de rayos X, ultrasonidos, emisión acústica) y sólo algunas son adecuadas para el análisis de la porosidad. En esta tesis, se ha analizado el efecto de ciclo de curado en el desarrollo de los poros durante la consolidación de preimpregnados Hexply AS4/8552 a bajas presiones mediante moldeo por compresión, en paneles unidireccionales y multiaxiales utilizando tres ciclos de curado diferentes. Dichos ciclos fueron cuidadosamente diseñados de acuerdo a la caracterización térmica y reológica de los preimpregnados. La fracción volumétrica de poros, su forma y distribución espacial se analizaron en detalle mediante tomografía de rayos X. Esta técnica no destructiva ha demostrado su capacidad para analizar la microestructura de materiales compuestos. Se observó, que la porosidad depende en gran medida de la evolución de la viscosidad dinámica a lo largo del ciclo y que la mayoría de la porosidad inicial procedía del aire atrapado durante el apilamiento de las láminas de preimpregnado. En el caso de los laminados multiaxiales, la porosidad también se vio afectada por la secuencia de apilamiento. En general, los poros tenían forma cilíndrica y se estaban orientados en la dirección de las fibras. Además, la proyección de la población de poros a lo largo de la dirección de la fibra reveló la existencia de una estructura celular de un diámetro aproximado de 1 mm. Las paredes de las celdas correspondían con regiones con mayor densidad de fibra mientras que los poros se concentraban en el interior de las celdas. Esta distribución de la porosidad es el resultado de una consolidación no homogenea. Toda esta información es crítica a la hora de optimizar las condiciones de procesado y proporcionar datos de partida para desarrollar herramientas de simulación de los procesos de fabricación de materiales compuestos fuera de autoclave. Adicionalmente, se determinaron ciertas propiedades mecánicas dependientes de la matriz termoestable con objeto de establecer la relación entre condiciones de procesado y las prestaciones mecánicas. En el caso de los laminados unidireccionales, la resistencia interlaminar depende de la porosidad para fracciones volumétricas de poros superiores 1%. Las mismas tendencias se observaron en el caso de GIIc mientras GIc no se vio afectada por la porosidad. En el caso de los laminados multiaxiales se evaluó la influencia de la porosidad en la resistencia a compresión, la resistencia a impacto a baja velocidad y la resistencia a copresión después de impacto. La resistencia a compresión se redujo con el contenido en poros, pero éste no influyó significativamente en la resistencia a compresión despues de impacto ya que quedó enmascarada por otros factores como la secuencia de apilamiento o la magnitud del daño generado tras el impacto. Finalmente, el efecto de las condiciones de fabricación en el proceso de compactación mediante moldeo por compresión en laminados unidireccionales fue simulado mediante el método de los elementos finitos en una primera aproximación para simular la fabricación de materiales compuestos fuera de autoclave. Los parámetros del modelo se obtuvieron mediante experimentos térmicos y reológicos del preimpregnado Hexply AS4/8552. Los resultados obtenidos en la predicción de la reducción de espesor durante el proceso de consolidación concordaron razonablemente con los resultados experimentales. Manufacturing of high performance polymer-matrix composites is normally carried out by means of autoclave using prepreg tapes stacked and consolidated under the simultaneous application of pressure and temperature. High autoclave pressures reduce the porosity in the laminate and ensure excellent mechanical properties. However, this manufacturing route is expensive in terms of capital investment and processing time, hindering its application in many industrial sectors. This fact has driven the demand of alternative out-of-autoclave processing routes. These techniques claim to produce composite parts faster and at lower cost but the mechanical performance is also reduced due to the lower fiber content and to the higher porosity. Corrient numerical models are able to simulate the mechanisms of void growth in polymer-matrix composites processed in autoclave. However these models are restricted to small spherical voids surrounded by a viscous resin. Their validity is not proved for long cylindrical voids in a viscous matrix surrounded by aligned fibers, the standard morphology observed in out-of-autoclave composites. In addition, there is an experimental evidence of the detrimental effect of voids on the mechanical performance of composites but, there is detailed information regarding the influence of curing conditions on the actual volume fraction, shape and spatial distribution of voids within the laminate. The standard techniques of microstructural characterization of composites (optical or electron microscopy, X-ray radiography, ultrasonics) provide information in two dimensions and are not always suitable to determine the porosity or void population. Moreover, they can not provide 3D information. The effect of curing cycle on the development of voids during consolidation of AS4/8552 prepregs at low pressure by compression molding was studied in unidirectional and multiaxial panels. They were manufactured using three different curing cycles carefully designed following the rheological and thermal analysis of the raw prepregs. The void volume fraction, shape and spatial distribution were analyzed in detail by means of X-ray computed microtomography, which has demonstrated its potential for analyzing the microstructural features of composites. It was demonstrated that the final void volume fraction depended on the evolution of the dynamic viscosity throughout the cycle. Most of the initial voids were the result of air entrapment and wrinkles created during lay-up. Differences in the final void volume fraction depended on the processing conditions for unidirectional and multiaxial panels. Voids were rod-like shaped and were oriented parallel to the fibers and concentrated in channels along the fiber orientation. X-ray computer tomography analysis of voids along the fiber direction showed a cellular structure with an approximate cell diameter of 1 mm. The cell walls were fiber-rich regions and porosity was localized at the center of the cells. This porosity distribution within the laminate was the result of inhomogeneous consolidation. This information is critical to optimize processing parameters and to provide inputs for virtual testing and virtual processing tools. In addition, the matrix-controlled mechanical properties of the panels were measured in order to establish the relationship between processing conditions and mechanical performance. The interlaminar shear strength (ILSS) and the interlaminar toughness (GIc and GIIc) were selected to evaluate the effect of porosity on the mechanical performance of unidirectional panels. The ILSS was strongly affected by the porosity when the void contents was higher than 1%. The same trends were observed in the case of GIIc while GIc was insensitive to the void volume fraction. Additionally, the mechanical performance of multiaxial panels in compression, low velocity impact and compression after impact (CAI) was measured to address the effect of processing conditions. The compressive strength decreased with porosity and ply-clustering. However, the porosity did not influence the impact resistance and the coompression after impact strength because the effect of porosity was masked by other factors as the damage due to impact or the laminate lay-up. Finally, the effect of the processing conditions on the compaction behavior of unidirectional AS4/8552 panels manufactured by compression moulding was simulated using the finite element method, as a first approximation to more complex and accurate models for out-of autoclave curing and consolidation of composite laminates. The model parameters were obtained from rheological and thermo-mechanical experiments carried out in raw prepreg samples. The predictions of the thickness change during consolidation were in reasonable agreement with the experimental results.

Optimization of logic programs with dynamic scheduling

Dynamic scheduling increases the expressive power of logic programming languages, but also introduces some overhead. In this paper we present two classes of program transformations designed to reduce this additional overhead, while preserving the operational semantics of the original programs, modulo ordering of literals woken at the same time. The first class of transformations simplifies the delay conditions while the second class moves delayed literals later in the rule body. Application of the program transformations can be automated using information provided by compile-time analysis. We provide experimental results obtained from an implementation of the proposed techniques using the CIAO prototype compiler. Our results show that the techniques can lead to substantial performance improvement.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

A technique for dynamic term size computation via program transformation

Knowing the size of the terms to which program variables are bound at run-time in logic programs is required in a class of applications related to program optimization such as, for example, granularity analysis and selection among different algorithms or control rules whose performance may be dependent on such size. Such size is difficult to even approximate at compile time and is thus generally computed at run-time by using (possibly predefined) predicates which traverse the terms involved. We propose a technique based on program transformation which has the potential of performing this computation much more efficiently. The technique is based on finding program procedures which are called before those in which knowledge regarding term sizes is needed and which traverse the terms whose size is to be determined, and transforming such procedures so that they compute term sizes "on the fly". We present a systematic way of determining whether a given program can be transformed in order to compute a given term size at a given program point without additional term traversal. Also, if several such transformations are possible our approach allows finding minimal transformations under certain criteria. We also discuss the advantages and applications of our technique and present some performance results.

Dynamic stiffness analysis of bridge abutments

Strong motion records obtained in instrumented short-span bridges show the importance of the abutments in the dynamic response of the structure. Existing models study the pier foundation influence but not the abutment performance. This work proposes two and three dimensional boundary element models in the frequency domain and studies the dimensionless dynamic stiffness of standard bridge abutments.

Performance of pressure control valves and flow meters precision in operational irrigation-water balance accuracy

In pressure irrigation-water distribution networks, pressure regulating devices for controlling the discharged flow rate by irrigation units are needed due to the variability of flow rate. In addition, applied water volume is used controlled operating the valve during a calculated time interval, and assuming constant flow rate. In general, a pressure regulating valve PRV is the commonly used pressure regulating device in a hydrant, which, also, executes the open and close function. A hydrant feeds several irrigation units, requiring a wide range in flow rate. In addition, some flow meters are also available, one as a component of the hydrant and the rest are placed downstream. Every land owner has one flow meter for each group of field plots downstream the hydrant. Its lecture could be used for refining the water balance but its accuracy must be taken into account. Ideal PRV performance would maintain a constant downstream pressure. However, the true performance depends on both upstream pressure and the discharged flow rate. The objective of this work is to asses the influence of the performance on the applied volume during the whole irrigation events in a year. The results of the study have been obtained introducing the flow rate into a PRV model. Variations on flow rate are simulated by taking into account the consequences of variations on climate conditions and also decisions in irrigation operation, such us duration and frequency application. The model comprises continuity, dynamic and energy equations of the components of the PRV.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

Mining recurring concepts in a dynamic feature space

Most data stream classification techniques assume that the underlying feature space is static. However, in real-world applications the set of features and their relevance to the target concept may change over time. In addition, when the underlying concepts reappear, reusing previously learnt models can enhance the learning process in terms of accuracy and processing time at the expense of manageable memory consumption. In this paper, we propose mining recurring concepts in a dynamic feature space (MReC-DFS), a data stream classification system to address the challenges of learning recurring concepts in a dynamic feature space while simultaneously reducing the memory cost associated with storing past models. MReC-DFS is able to detect and adapt to concept changes using the performance of the learning process and contextual information. To handle recurring concepts, stored models are combined in a dynamically weighted ensemble. Incremental feature selection is performed to reduce the combined feature space. This contribution allows MReC-DFS to store only the features most relevant to the learnt concepts, which in turn increases the memory efficiency of the technique. In addition, an incremental feature selection method is proposed that dynamically determines the threshold between relevant and irrelevant features. Experimental results demonstrating the high accuracy of MReC-DFS compared with state-of-the-art techniques on a variety of real datasets are presented. The results also show the superior memory efficiency of MReC-DFS.

A Monitoring Infrastructure for FPGA Self-Awareness and Dynamic Adaptation

Variabilities associated with CMOS evolution affect the yield and performance of current digital designs. FPGAs, which are widely used for fast prototyping and implementation of digital circuits, also suffer from these issues. Proactive approaches start to appear to achieve self-awareness and dynamic adaptation of these devices. To support these techniques we propose the employment of a multi-purpose sensor network. This infrastructure, through adequate use of configuration and automation tools, is able to obtain relevant data along the life cycle of an FPGA. This is realised at a very reduced cost, not only in terms of area or other limited resources, but also regarding the design effort required to define and deploy the measuring infrastructure. Our proposal has been validated by measuring inter-die and intra-die variability in different FPGA families.

AUTOFLY-Aid: Flight Deck Automation Support with Dynamic 4D Trajectory Management for Responsive and Adaptive Airborne Collision Avoidance

AUTOFLY-Aid Project aims to develop and demonstrate novel automation support algorithms and tools to the flight crew for flight critical collision avoidance using “dynamic 4D trajectory management”. The automation support system is envisioned to improve the primary shortcomings of TCAS, and to aid the pilot through add-on avionics/head-up displays and reality augmentation devices in dynamically evolving collision avoidance scenarios. The main theoretical innovative and novel concepts to be developed by AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck’s perspective, as seen/measured/informed by the aircraft flying in SESAR 2020, b) design and development of a dynamic trajectory planning algorithm that can generate at real-time (on the order of seconds) flyable (i.e. dynamically and performance-wise feasible) alternative trajectories across the evolving stochastic composite airspace picture (which includes new conflicts, blunder risks, terrain and weather limitations) and c) development and testing of the Collision Avoidance Automation Support System on a Boeing 737 NG FNPT II Flight Simulator with synthetic vision and reality augmentation while providing the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures.

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions.

Predicting academic performance with learning analytics in virtual learning environments: A comparative study of three interaction classifications

Learning analytics is the analysis of static and dynamic data extracted from virtual learning environments, in order to understand and optimize the learning process. Generally, this dynamic data is generated by the interactions which take place in the virtual learning environment. At the present time, many implementations for grouping of data have been proposed, but there is no consensus yet on which interactions and groups must be measured and analyzed. There is also no agreement on what is the influence of these interactions, if any, on learning outcomes, academic performance or student success. This study presents three different extant interaction typologies in e-learning and analyzes the relation of their components with students? academic performance. The three different classifications are based on the agents involved in the learning process, the frequency of use and the participation mode, respectively. The main findings from the research are: a) that agent-based classifications offer a better explanation of student academic performance; b) that at least one component in each typology predicts academic performance; and c) that student-teacher and student-student, evaluating students, and active interactions, respectively, have a significant impact on academic performance, while the other interaction types are not significantly related to academic performance.

Measuring dynamic effects on underpasses of high-speed railway lines

Underpasses are common in modern railway lines. Wildlife corridors and drainage conduits often fall into this category of partially buried structures. Their dynamic behaviour has received far less attention than that of other structures such as bridges, but their large number makes their study an interesting challenge in order to achieve safe and cost-effective structures. As ballast operations are a key life cycle cost, and excessive vibrations increase the need of ballast regulation in order to ensure track geometry, special attention is paid to accelerations, the values of which should be limited to avoid track instability according to Eurocode. In this paper, the data obtained during on site measurements on culverts belonging to a Spanish high-speed train line are presented. A set of six rectangular-shaped, closed-frame underpasses were monitored under traffic loading. Acceleration records at different points of the structures are presented and discussed. They reveal a non-uniform dynamic response of the roof-slab, with the highest observed values below the occupied track. Also, they indicate that the dynamic response is important up to frequencies higher than those usually observed for standard simply supported bridges. Finally, they are used to obtain a heuristic rule to estimate acceleration levels on the roof-slab.

Dynamic Soil-Structure Interaction in Bridge Abutments

Strong motion obtained in instrumental short-span bridges show the importance of the abutments in the dynamic response of the whole structure. Many models have been used in order to take into account the influence of pier foundations although no reliable ones have been used to analyse the abutment performance. In this work three-dimensional Boundary Element models in frequency domain have been proposed and dimensionless dynamic stiffness of standard bridge abutments have been obtained.

On the dynamic adaptation of language models based on dialogue information

We present an approach to adapt dynamically the language models (LMs) used by a speech recognizer that is part of a spoken dialogue system. We have developed a grammar generation strategy that automatically adapts the LMs using the semantic information that the user provides (represented as dialogue concepts), together with the information regarding the intentions of the speaker (inferred by the dialogue manager, and represented as dialogue goals). We carry out the adaptation as a linear interpolation between a background LM, and one or more of the LMs associated to the dialogue elements (concepts or goals) addressed by the user. The interpolation weights between those models are automatically estimated on each dialogue turn, using measures such as the posterior probabilities of concepts and goals, estimated as part of the inference procedure to determine the actions to be carried out. We propose two approaches to handle the LMs related to concepts and goals. Whereas in the first one we estimate a LM for each one of them, in the second one we apply several clustering strategies to group together those elements that share some common properties, and estimate a LM for each cluster. Our evaluation shows how the system can estimate a dynamic model adapted to each dialogue turn, which helps to improve the performance of the speech recognition (up to a 14.82% of relative improvement), which leads to an improvement in both the language understanding and the dialogue management tasks.