Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

In this PhD Thesis proposal, the principles of diffusion MRI (dMRI) in its application to the human brain mapping of connectivity are reviewed. The background section covers the fundamentals of dMRI, with special focus on those related to the distortions caused by susceptibility inhomogeneity across tissues. Also, a deep survey of available correction methodologies for this common artifact of dMRI is presented. Two methodological approaches to improved correction are introduced. Finally, the PhD proposal describes its objectives, the research plan, and the necessary resources.

Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.

Extraction of subjective properties in image processing

Most of the present digital images processing methods are related with objective characterization of external properties as shape, form or colour. This information concerns objective characteristics of different bodies and is applied to extract details to perform several different tasks. But in some occasions, some other type of information is needed. This is the case when the image processing system is going to be applied to some operation related with living bodies. In this case, some other type of object information may be useful. As a matter of fact, it may give additional knowledge about its subjective properties. Some of these properties are object symmetry, parallelism between lines and the feeling of size. These types of properties concerns more to internal sensations of living beings when they are related with their environment than to the objective information obtained by artificial systems. This paper presents an elemental system able to detect some of the above-mentioned parameters. A first mathematical model to analyze these situations is reported. This theoretical model will give the possibility to implement a simple working system. The basis of this system is the use of optical logic cells, previously employed in optical computing.

Development of Robotized Laser Welding Applications for Joining Thin Sheets

Laser Welding (LW) is more often used in manufacturing due to its advantages, such as accurate control, good repeatability, less heat input, opportunities for joining of special materials, high speed, capability to join small dimension parts etc. LW is dedicated to robotized manufacturing, and the fabrication cells are using various level of flexibility, from specialized robots to very flexible setups. This paper features several LW applications using two industrially-scaled manufacturing cells at UPM Laser Centre (CLUPM) of Polytechnical University of Madrid (Universidad Politécnica de Madrid). The one dedicated to Remote Laser Welding (RLW) of thin sheets for automotive and other sectors uses a CO2 laser of 3500 W. The second has a high flexibility, is based on a 6-axis ABB robot and a Nd:YAG laser of 3300 W, and is meant for various laser processing methods, including welding. After a short description of each cell, several LW applications experimented at CLUPM and recently implemented in industry are briefly presented: RLW of automotive coated sheets, LW of high strength automotive sheets, LW vs. laser hybrid welding (LHW) of Double Phase steel thin sheets, and LHW of thin sheets of stainless steel and carbon steel (dissimilar joints). The main technological issues overcame and the critical process parameters are pointed out. Conclusions about achievements and trends are provided.

Automatic Adaptation of Airport Surface Surveillance to Sensor Quality

This paper describes a novel method to enhance current airport surveillance systems used in Advanced Surveillance Monitoring Guidance and Control Systems (A-SMGCS). The proposed method allows for the automatic calibration of measurement models and enhanced detection of nonideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the surveillance processing chain and a rule based expert system aimed to change the data processing methods

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillations

Monitoring leafy vegetables through packaging films with

Fresh-cut or minimally processed fruit and vegetables have been physically modified from its original form (by peeling, trimming, washing and cutting) to obtain a 100% edible product that is subsequently packaged (usually under modified atmosphere packaging –MAP) and kept in refrigerated storage. In fresh-cut products, physiological activity and microbiological spoilage, determine their deterioration and shelf-life. The major preservation techniques applied to delay spoilage are chilling storage and MAP, combined with chemical treatments antimicrobial solutions antibrowning, acidulants, antioxidants, etc.). The industry looks for safer alternatives. Consequently, the sector is asking for innovative, fast, cheap and objective techniques to evaluate the overall quality and safety of fresh-cut products in order to obtain decision tools for implementing new packaging materials and procedures. In recent years, hyperspectral imaging technique has been regarded as a tool for analyses conducted for quality evaluation of food products in research, control and industries. The hyperspectral imaging system allows integrating spectroscopic and imaging techniques to enable direct identification of different components or quality characteristics and their spatial distribution in the tested sample. The objective of this work is to develop hyperspectral image processing methods for the supervision through plastic films of changes related to quality deterioration in packed readyto-use leafy vegetables during shelf life. The evolutions of ready-to-use spinach and watercress samples covered with three different common transparent plastic films were studied. Samples were stored at 4 ºC during the monitoring period (until 21 days). More than 60 hyperspectral images (from 400 to 1000 nm) per species were analyzed using ad hoc routines and commercial toolboxes of MatLab®. Besides common spectral treatments for removing additive and multiplicative effects, additional correction, previously to any other correction, was performed in the images of leaves in order to avoid the modification in their spectra due to the presence of the plastic transparent film. Findings from this study suggest that the developed images analysis system is able to deal with the effects caused in the images by the presence of plastic films in the supervision of shelf-life in leafy vegetables, in which different stages of quality has been identified.

Mejoras en el procesamiento de imágenes de TC para el tratamiento con radioterapia adaptativa del cáncer de próstata

El cáncer de próstata es el tipo de cáncer con mayor prevalencia entre los hombres del mundo occidental y, pese a tener una alta tasa de supervivencia relativa, es la segunda mayor causa de muerte por cáncer en este sector de la población. El tratamiento de elección frente al cáncer de próstata es, en la mayoría de los casos, la radioterapia externa. Las técnicas más modernas de radioterapia externa, como la radioterapia modulada en intensidad, permiten incrementar la dosis en el tumor mientras se reduce la dosis en el tejido sano. Sin embargo, la localización del volumen objetivo varía con el día de tratamiento, y se requieren movimientos muy pequeños de los órganos para sacar partes del volumen objetivo fuera de la región terapéutica, o para introducir tejidos sanos críticos dentro. Para evitar esto se han desarrollado técnicas más avanzadas, como la radioterapia guiada por imagen, que se define por un manejo más preciso de los movimientos internos mediante una adaptación de la planificación del tratamiento basada en la información anatómica obtenida de imágenes de tomografía computarizada (TC) previas a la sesión terapéutica. Además, la radioterapia adaptativa añade la información dosimétrica de las fracciones previas a la información anatómica. Uno de los fundamentos de la radioterapia adaptativa es el registro deformable de imágenes, de gran utilidad a la hora de modelar los desplazamientos y deformaciones de los órganos internos. Sin embargo, su utilización conlleva nuevos retos científico-tecnológicos en el procesamiento de imágenes, principalmente asociados a la variabilidad de los órganos, tanto en localización como en apariencia. El objetivo de esta tesis doctoral es mejorar los procesos clínicos de delineación automática de contornos y de cálculo de dosis acumulada para la planificación y monitorización de tratamientos con radioterapia adaptativa, a partir de nuevos métodos de procesamiento de imágenes de TC (1) en presencia de contrastes variables, y (2) cambios de apariencia del recto. Además, se pretende (3) proveer de herramientas para la evaluación de la calidad de los contornos obtenidos en el caso del gross tumor volumen (GTV). Las principales contribuciones de esta tesis doctoral son las siguientes: _ 1. La adaptación, implementación y evaluación de un algoritmo de registro basado en el flujo óptico de la fase de la imagen como herramienta para el cálculo de transformaciones no-rígidas en presencia de cambios de intensidad, y su aplicabilidad a tratamientos de radioterapia adaptativa en cáncer de próstata con uso de agentes de contraste radiológico. Los resultados demuestran que el algoritmo seleccionado presenta mejores resultados cualitativos en presencia de contraste radiológico en la vejiga, y no distorsiona la imagen forzando deformaciones poco realistas. 2. La definición, desarrollo y validación de un nuevo método de enmascaramiento de los contenidos del recto (MER), y la evaluación de su influencia en el procedimiento de radioterapia adaptativa en cáncer de próstata. Las segmentaciones obtenidas mediante el MER para la creación de máscaras homogéneas en las imágenes de sesión permiten mejorar sensiblemente los resultados de los algoritmos de registro en la región rectal. Así, el uso de la metodología propuesta incrementa el índice de volumen solapado entre los contornos manuales y automáticos del recto hasta un valor del 89%, cercano a los resultados obtenidos usando máscaras manuales para el registro de las dos imágenes. De esta manera se pueden corregir tanto el cálculo de los nuevos contornos como el cálculo de la dosis acumulada. 3. La definición de una metodología de evaluación de la calidad de los contornos del GTV, que permite la representación de la distribución espacial del error, adaptándola a volúmenes no-convexos como el formado por la próstata y las vesículas seminales. Dicha metodología de evaluación, basada en un nuevo algoritmo de reconstrucción tridimensional y una nueva métrica de cuantificación, presenta resultados precisos con una gran resolución espacial en un tiempo despreciable frente al tiempo de registro. Esta nueva metodología puede ser una herramienta útil para la comparación de distintos algoritmos de registro deformable orientados a la radioterapia adaptativa en cáncer de próstata. En conclusión, el trabajo realizado en esta tesis doctoral corrobora las hipótesis de investigación postuladas, y pretende servir como cimiento de futuros avances en el procesamiento de imagen médica en los tratamientos de radioterapia adaptativa en cáncer de próstata. Asimismo, se siguen abriendo nuevas líneas de aplicación futura de métodos de procesamiento de imágenes médicas con el fin de mejorar los procesos de radioterapia adaptativa en presencia de cambios de apariencia de los órganos, e incrementar la seguridad del paciente. I.2 Inglés Prostate cancer is the most prevalent cancer amongst men in the Western world and, despite having a relatively high survival rate, is the second leading cause of cancer death in this sector of the population. The treatment of choice against prostate cancer is, in most cases, external beam radiation therapy. The most modern techniques of external radiotherapy, as intensity modulated radiotherapy, allow increasing the dose to the tumor whilst reducing the dose to healthy tissue. However, the location of the target volume varies with the day of treatment, and very small movements of the organs are required to pull out parts of the target volume outside the therapeutic region, or to introduce critical healthy tissues inside. Advanced techniques, such as the image-guided radiotherapy (IGRT), have been developed to avoid this. IGRT is defined by more precise handling of internal movements by adapting treatment planning based on the anatomical information obtained from computed tomography (CT) images prior to the therapy session. Moreover, the adaptive radiotherapy adds dosimetric information of previous fractions to the anatomical information. One of the fundamentals of adaptive radiotherapy is deformable image registration, very useful when modeling the displacements and deformations of the internal organs. However, its use brings new scientific and technological challenges in image processing, mainly associated to the variability of the organs, both in location and appearance. The aim of this thesis is to improve clinical processes of automatic contour delineation and cumulative dose calculation for planning and monitoring of adaptive radiotherapy treatments, based on new methods of CT image processing (1) in the presence of varying contrasts, and (2) rectum appearance changes. It also aims (3) to provide tools for assessing the quality of contours obtained in the case of gross tumor volume (GTV). The main contributions of this PhD thesis are as follows: 1. The adaptation, implementation and evaluation of a registration algorithm based on the optical flow of the image phase as a tool for the calculation of non-rigid transformations in the presence of intensity changes, and its applicability to adaptive radiotherapy treatment in prostate cancer with use of radiological contrast agents. The results demonstrate that the selected algorithm shows better qualitative results in the presence of radiological contrast agents in the urinary bladder, and does not distort the image forcing unrealistic deformations. 2. The definition, development and validation of a new method for masking the contents of the rectum (MER, Spanish acronym), and assessing their impact on the process of adaptive radiotherapy in prostate cancer. The segmentations obtained by the MER for the creation of homogenous masks in the session CT images can improve significantly the results of registration algorithms in the rectal region. Thus, the use of the proposed methodology increases the volume overlap index between manual and automatic contours of the rectum to a value of 89%, close to the results obtained using manual masks for both images. In this way, both the calculation of new contours and the calculation of the accumulated dose can be corrected. 3. The definition of a methodology for assessing the quality of the contours of the GTV, which allows the representation of the spatial distribution of the error, adapting it to non-convex volumes such as that formed by the prostate and seminal vesicles. Said evaluation methodology, based on a new three-dimensional reconstruction algorithm and a new quantification metric, presents accurate results with high spatial resolution in a time negligible compared to the registration time. This new approach may be a useful tool to compare different deformable registration algorithms oriented to adaptive radiotherapy in prostate cancer In conclusion, this PhD thesis corroborates the postulated research hypotheses, and is intended to serve as a foundation for future advances in medical image processing in adaptive radiotherapy treatment in prostate cancer. In addition, it opens new future applications for medical image processing methods aimed at improving the adaptive radiotherapy processes in the presence of organ’s appearance changes, and increase the patient safety.

Transductor óptico-sonoro basado en procesado de imagen

En este proyecto se aborda la transducción óptico-sonora utilizando métodos de tratamiento digital de imagen. Para llevar a cabo el proyecto se consideran únicamente métodos de bajo presupuesto, por lo que para realizar todo el proceso de conversión óptico-sonora se utilizan un ordenador y un escáner doméstico. Como el principal objetivo del proyecto es comprobar si es viable utilizar el tratamiento digital de imagen como conversor no se ha contemplado la utilización de equipamiento profesional. La utilidad de este proyecto está en la restauración del sonido de material fílmico con importantes degradaciones, tales que no sea posible su reproducción en un proyector. Con el prototipo que se propone, realizado con el software de programación Matlab, se consigue digitalizar el audio analógico de las películas en malas condiciones ya que la captura de audio se efectúa de manera óptica sobre las bandas sonoras. Lo conseguido en este proyecto cobra especial importancia si se tiene en cuenta la cantidad de material cinematográfico que hay en películas de celulosa. La conservación de dicho material requiere unas condiciones de almacenamiento muy específicas para que el soporte no se vea afectado, pero con el paso del tiempo es habitual que las bobinas de película presenten deformaciones o incluso ruptura. Aplicando métodos de tratamiento digital de imagen es posible restaurar el audio de fragmentos de película que no puedan ser expuestos a la tensión producida por los rodillos de los proyectores, incluso es posible recuperar el audio de fotogramas concretos ya que la digitalización del audio se realiza capturando la imagen de la forma de onda. Por ello, el procedimiento seguido para digitalizar la película debe ser poco intrusivo para garantizar la conservación del soporte fílmico. Cabe destacar que en este proyecto se ha realizado la conversión óptico-sonora sobre las bandas de sonido analógicas de área variable presentes en la película, pero el procedimiento es aplicable también a las bandas de área variable realizando modificaciones en el prototipo. Esto último queda fuera del objetivo de este proyecto, pero puede ser un trabajo futuro. ABSTRACT This project addresses optical to sound conversion using digital image processing methods. To carry out the project are considered only low-budget methods , so for all optical to sound conversion process using a computer and a home scanner . As the main application of this project is to test the feasibility of using the digital image processing as a converter does not contemplate the use of professional equipment. The main objective of this project is the restoration of sound film material with significant impairments , such is not possible playback on a projector. With the proposed prototype , made with Matlab programming software , you get digitize analog audio bad movies because the audio capture is performed optically on the soundtracks. The achievements in this project is especially important if you consider the amount of film material is in cellulose films . The preservation of such material requires a very specific storage conditions to which the support is not affected , but over time it is common for film reels presenting deformations or even rupture. Applying methods of digital image processing is possible to restore the audio from movie clips that can not be exposed to the tension produced by the rollers of the projectors , it is even possible to retrieve specific frames audio and audio that digitization is done by capturing the image of the waveform. Therefore, the procedure used to digitize the film should be bit intrusive to ensure the conservation of the film medium. Note that in this project was carried out optical to sound conversion on analog variable area soundtracks present in the film, but the procedure is applicable to variable-area bands making changes to the prototype. The latter is beyond the scope of this project, but can be a future work.

Brain injury MRI simulator based on theoretical models of neuroanatomic damage

In order to improve the body of knowledge about brain injury impairment is essential to develop image database with different types of injuries. This paper proposes a new methodology to model three types of brain injury: stroke, tumor and traumatic brain injury; and implements a system to navigate among simulated MRI studies. These studies can be used on research studies, to validate new processing methods and as an educational tool, to show different types of brain injury and how they affect to neuroanatomic structures.

Linear color correction for multiple illumination changes and non-overlapping cameras

Many image processing methods, such as techniques for people re-identification, assume photometric constancy between different images. This study addresses the correction of photometric variations based upon changes in background areas to correct foreground areas. The authors assume a multiple light source model where all light sources can have different colours and will change over time. In training mode, the authors learn per-location relations between foreground and background colour intensities. In correction mode, the authors apply a double linear correction model based on learned relations. This double linear correction includes a dynamic local illumination correction mapping as well as an inter-camera mapping. The authors evaluate their illumination correction by computing the similarity between two images based on the earth mover's distance. The authors compare the results to a representative auto-exposure algorithm found in the recent literature plus a colour correction one based on the inverse-intensity chromaticity. Especially in complex scenarios the authors’ method outperforms these state-of-the-art algorithms.

Implementación de una Support Vector Machine en RVC – CAL para imágenes hiperespectrales

El análisis de imágenes hiperespectrales permite obtener información con una gran resolución espectral: cientos de bandas repartidas desde el espectro infrarrojo hasta el ultravioleta. El uso de dichas imágenes está teniendo un gran impacto en el campo de la medicina y, en concreto, destaca su utilización en la detección de distintos tipos de cáncer. Dentro de este campo, uno de los principales problemas que existen actualmente es el análisis de dichas imágenes en tiempo real ya que, debido al gran volumen de datos que componen estas imágenes, la capacidad de cómputo requerida es muy elevada. Una de las principales líneas de investigación acerca de la reducción de dicho tiempo de procesado se basa en la idea de repartir su análisis en diversos núcleos trabajando en paralelo. En relación a esta línea de investigación, en el presente trabajo se desarrolla una librería para el lenguaje RVC – CAL – lenguaje que está especialmente pensado para aplicaciones multimedia y que permite realizar la paralelización de una manera intuitiva – donde se recogen las funciones necesarias para implementar el clasificador conocido como Support Vector Machine – SVM. Cabe mencionar que este trabajo complementa el realizado en [1] y [2] donde se desarrollaron las funciones necesarias para implementar una cadena de procesado que utiliza el método unmixing para procesar la imagen hiperespectral. En concreto, este trabajo se encuentra dividido en varias partes. La primera de ellas expone razonadamente los motivos que han llevado a comenzar este Trabajo de Investigación y los objetivos que se pretenden conseguir con él. Tras esto, se hace un amplio estudio del estado del arte actual y, en él, se explican tanto las imágenes hiperespectrales como sus métodos de procesado y, en concreto, se detallará el método que utiliza el clasificador SVM. Una vez expuesta la base teórica, nos centraremos en la explicación del método seguido para convertir una versión en Matlab del clasificador SVM optimizado para analizar imágenes hiperespectrales; un punto importante en este apartado es que se desarrolla la versión secuencial del algoritmo y se asientan las bases para una futura paralelización del clasificador. Tras explicar el método utilizado, se exponen los resultados obtenidos primero comparando ambas versiones y, posteriormente, analizando por etapas la versión adaptada al lenguaje RVC – CAL. Por último, se aportan una serie de conclusiones obtenidas tras analizar las dos versiones del clasificador SVM en cuanto a bondad de resultados y tiempos de procesado y se proponen una serie de posibles líneas de actuación futuras relacionadas con dichos resultados. ABSTRACT. Hyperspectral imaging allows us to collect high resolution spectral information: hundred of bands covering from infrared to ultraviolet spectrum. These images have had strong repercussions in the medical field; in particular, we must highlight its use in cancer detection. In this field, the main problem we have to deal with is the real time analysis, because these images have a great data volume and they require a high computational power. One of the main research lines that deals with this problem is related with the analysis of these images using several cores working at the same time. According to this investigation line, this document describes the development of a RVC – CAL library – this language has been widely used for working with multimedia applications and allows an optimized system parallelization –, which joins all the functions needed to implement the Support Vector Machine – SVM - classifier. This research complements the research conducted in [1] and [2] where the necessary functions to implement the unmixing method to analyze hyperspectral images were developed. The document is divided in several chapters. The first of them introduces the motivation of the Master Thesis and the main objectives to achieve. After that, we study the state of the art of some technologies related with this work, like hyperspectral images, their processing methods and, concretely, the SVM classifier. Once we have exposed the theoretical bases, we will explain the followed methodology to translate a Matlab version of the SVM classifier optimized to process an hyperspectral image to RVC – CAL language; one of the most important issues in this chapter is that a sequential implementation is developed and the bases of a future parallelization of the SVM classifier are set. At this point, we will expose the results obtained in the comparative between versions and then, the results of the different steps that compose the SVM in its RVC – CAL version. Finally, we will extract some conclusions related with algorithm behavior and time processing. In the same way, we propose some future research lines according to the results obtained in this document.

Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

Particle methods parallel implementations by GP-GPU strategies

This paper outlines the problems found in the parallelization of SPH (Smoothed Particle Hydrodynamics) algorithms using Graphics Processing Units. Different results of some parallel GPU implementations in terms of the speed-up and the scalability compared to the CPU sequential codes are shown. The most problematic stage in the GPU-SPH algorithms is the one responsible for locating neighboring particles and building the vectors where this information is stored, since these specific algorithms raise many dificulties for a data-level parallelization. Because of the fact that the neighbor location using linked lists does not show enough data-level parallelism, two new approaches have been pro- posed to minimize bank conflicts in the writing and subsequent reading of the neighbor lists. The first strategy proposes an efficient coordination between CPU-GPU, using GPU algorithms for those stages that allow a straight forward parallelization, and sequential CPU algorithms for those instructions that involve some kind of vector reduction. This coordination provides a relatively orderly reading of the neighbor lists in the interactions stage, achieving a speed-up factor of x47 in this stage. However, since the construction of the neighbor lists is quite expensive, it is achieved an overall speed-up of x41. The second strategy seeks to maximize the use of the GPU in the neighbor's location process by executing a specific vector sorting algorithm that allows some data-level parallelism. Al- though this strategy has succeeded in improving the speed-up on the stage of neighboring location, the global speed-up on the interactions stage falls, due to inefficient reading of the neighbor vectors. Some changes to these strategies are proposed, aimed at maximizing the computational load of the GPU and using the GPU texture-units, in order to reach the maximum speed-up for such codes. Different practical applications have been added to the mentioned GPU codes. First, the classical dam-break problem is studied. Second, the wave impact of the sloshing fluid contained in LNG vessel tanks is also simulated as a practical example of particle methods

Improvement of Mechanical Properties and Life Extension of High Reliability Structural Components by Laser Shock Processing

Profiting by the increasing availability of laser sources delivering intensities above 109 W/cm2 with pulse energies in the range of several Joules and pulse widths in the range of nanoseconds, laser shock processing (LSP) is being consolidating as an effective technology for the improvement of surface mechanical and corrosion resistance properties of metals and is being developed as a practical process amenable to production engineering. The main acknowledged advantage of the laser shock processing technique consists on its capability of inducing a relatively deep compression residual stresses field into metallic alloy pieces allowing an improved mechanical behaviour, explicitly, the life improvement of the treated specimens against wear, crack growth and stress corrosion cracking. Following a short description of the theoretical/computational and experimental methods developed by the authors for the predictive assessment and experimental implementation of LSP treatments, experimental results on the residual stress profiles and associated surface properties modification successfully reached in typical materials (specifically Al and Ti alloys) under different LSP irradiation conditions are presented. In particular, the analysis of the residual stress profiles obtained under different irradiation parameters and the evaluation of the corresponding induced surface properties as roughness and wear resistance are presented.