Repeatability and Two-Dimensionality of Model Scale Sloshing Impacts

Canonical test cases for sloshing wave impact problems are pre-sented and discussed. In these cases the experimental setup has been simpli?ed seeking the highest feasible repeatability; a rectangular tank subjected to harmonic roll motion has been the tested con?guration. Both lateral and roof impacts have been studied, since both cases are relevant in sloshing assessment and show speci?c dynamics. An analysis of the impact pressure of the ?rst four impact events is provided in all cases. It has been found that not in all cases a Gaussian ?tting of each individual peak is feasible. The tests have been conducted with both water and oil in order to obtain high and moderate Reynolds number data; the latter may be useful as simpler test cases to assess the capabilities of CFD codes in simulating sloshing impacts. The re-peatability of impact pressure values increases dramatically when using oil. In addition, a study of the two-dimensionality of the problem using a tank con?guration that can be adjusted to 4 di?erent thicknesses has been carried out. Though the kinemat-ics of the free surface does not change signi cantly in some of the cases, the impact pressure values of the ?rst impact events changes substantially from the small to the large aspect ratios thus meaning that attention has to be paid to this issue when reference data is used for validation of 2D and 3D CFD codes.

Estimating the modal parameters from multiple measurement setups using a joint state space model

Computing the modal parameters of structural systems often requires processing data from multiple non-simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors, which are fixed for all measurements, while the other sensors change their position from one setup to the next. One possibility is to process the setups separately resulting in different modal parameter estimates for each setup. Then, the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global mode shapes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a new state space model that processes all setups at once. The result is that the global mode shapes are obtained automatically, and only a value for the natural frequency and damping ratio of each mode is estimated. We also investigate the estimation of this model using maximum likelihood and the Expectation Maximization algorithm, and apply this technique to simulated and measured data corresponding to different structures.

Using the EM algorithm to estimate the state space model for OMAX

This paper presents a time-domain stochastic system identification method based on Maximum Likelihood Estimation and the Expectation Maximization algorithm that is applied to the estimation of modal parameters from system input and output data. The effectiveness of this structural identification method is evaluated through numerical simulation. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the simulated structure are estimated applying the proposed identification method to a set of 100 simulated cases. The numerical results show that the proposed method estimates the modal parameters with precision in the presence of 20% measurement noise even. Finally, advantages and disadvantages of the method have been discussed.

Competitive exclusion in a two-especies chemotasis model

We consider a mathematical model for the spatio-temporal evolution of two biological species in a competitive situation. Besides diffusing, both species move toward higher concentrations of a chemical substance which is produced by themselves. The resulting system consists of two parabolic equations with Lotka–Volterra-type kinetic terms and chemotactic cross-diffusion, along with an elliptic equation describing the behavior of the chemical. We study the question in how far the phenomenon of competitive exclusion occurs in such a context. We identify parameter regimes for which indeed one of the species dies out asymptotically, whereas the other reaches its carrying capacity in the large time limit.

On a two species chemotaxis model with slow chemical diffucion.

In this paper we consider a system of three parabolic equations modeling the behavior of two biological species moving attracted by a chemical factor. The chemical substance verifies a parabolic equation with slow diffusion. The system contains second order terms in the first two equations modeling the chemotactic effects. We apply an iterative method to obtain the global existence of solutions using that the total mass of the biological species is conserved. The stability of the homogeneous steady states is studied by using an energy method. A final example is presented to illustrate the theoretical results.

Modal contribution and state space order selection in operational modal analysis

The estimation of modal parameters of a structure from ambient measurements has attracted the attention of many researchers in the last years. The procedure is now well established and the use of state space models, stochastic system identification methods and stabilization diagrams allows to identify the modes of the structure. In this paper the contribution of each identified mode to the measured vibration is discussed. This modal contribution is computed using the Kalman filter and it is an indicator of the importance of the modes. Also the variation of the modal contribution with the order of the model is studied. This analysis suggests selecting the order for the state space model as the order that includes the modes with higher contribution. The order obtained using this method is compared to those obtained using other well known methods, like Akaike criteria for time series or the singular values of the weighted projection matrix in the Stochastic Subspace Identification method. Finally, both simulated and measured vibration data are used to show the practicability of the derived technique. Finally, it is important to remark that the method can be used with any identification method working in the state space model.

Diabatic quantum gates

At present, several models for quantum computation have been proposed. Adiabatic quantum computation scheme particularly offers this possibility and is based on a slow enough time evolution of the system, where no transitions take place. In this work, a new strategy for quantum computation is provided from the opposite point of view. The objective is to control the non-adiabatic transitions between some states in order to produce the desired exit states after the evolution. The model is introduced by means of an analogy between the adiabatic quantum computation and an inelastic atomic collision. By means of a simple two-state model, several quantum gates are reproduced, concluding the possibility of diabatic universal faulttolerant quantum computation. Going a step further, a new quantum diabatic computation model is glimpsed, where a carefully chosen Hamiltonian could carry out a non-adiabatic transition between the initial and the sought final state.

Computational Methods for Identification of Vibrating Structures

System identification deals with the problem of building mathematical models of dynamical systems based on observed data from the system" [1]. In the context of civil engineering, the system refers to a large scale structure such as a building, bridge, or an offshore structure, and identification mostly involves the determination of modal parameters (the natural frequencies, damping ratios, and mode shapes). This paper presents some modal identification results obtained using a state-of-the-art time domain system identification method (data-driven stochastic subspace algorithms [2]) applied to the output-only data measured in a steel arch bridge. First, a three dimensional finite element model was developed for the numerical analysis of the structure using ANSYS. Modal analysis was carried out and modal parameters were extracted in the frequency range of interest, 0-10 Hz. The results obtained from the finite element modal analysis were used to determine the location of the sensors. After that, ambient vibration tests were conducted during April 23-24, 2009. The response of the structure was measured using eight accelerometers. Two stations of three sensors were formed (triaxial stations). These sensors were held stationary for reference during the test. The two remaining sensors were placed at the different measurement points along the bridge deck, in which only vertical and transversal measurements were conducted (biaxial stations). Point estimate and interval estimate have been carried out in the state space model using these ambient vibration measurements. In the case of parametric models (like state space), the dynamic behaviour of a system is described using mathematical models. Then, mathematical relationships can be established between modal parameters and estimated point parameters (thus, it is common to use experimental modal analysis as a synonym for system identification). Stable modal parameters are found using a stabilization diagram. Furthermore, this paper proposes a method for assessing the precision of estimates of the parameters of state-space models (confidence interval). This approach employs the nonparametric bootstrap procedure [3] and is applied to subspace parameter estimation algorithm. Using bootstrap results, a plot similar to a stabilization diagram is developed. These graphics differentiate system modes from spurious noise modes for a given order system. Additionally, using the modal assurance criterion, the experimental modes obtained have been compared with those evaluated from a finite element analysis. A quite good agreement between numerical and experimental results is observed.

Maximum likelihood estimation of new state space models for operational modal analysis

The modal analysis of a structural system consists on computing its vibrational modes. The experimental way to estimate these modes requires to excite the system with a measured or known input and then to measure the system output at different points using sensors. Finally, system inputs and outputs are used to compute the modes of vibration. When the system refers to large structures like buildings or bridges, the tests have to be performed in situ, so it is not possible to measure system inputs such as wind, traffic, . . .Even if a known input is applied, the procedure is usually difficult and expensive, and there are still uncontrolled disturbances acting at the time of the test. These facts led to the idea of computing the modes of vibration using only the measured vibrations and regardless of the inputs that originated them, whether they are ambient vibrations (wind, earthquakes, . . . ) or operational loads (traffic, human loading, . . . ). This procedure is usually called Operational Modal Analysis (OMA), and in general consists on to fit a mathematical model to the measured data assuming the unobserved excitations are realizations of a stationary stochastic process (usually white noise processes). Then, the modes of vibration are computed from the estimated model. The first issue investigated in this thesis is the performance of the Expectation- Maximization (EM) algorithm for the maximum likelihood estimation of the state space model in the field of OMA. The algorithm is described in detail and it is analysed how to apply it to vibration data. After that, it is compared to another well known method, the Stochastic Subspace Identification algorithm. The maximum likelihood estimate enjoys some optimal properties from a statistical point of view what makes it very attractive in practice, but the most remarkable property of the EM algorithm is that it can be used to address a wide range of situations in OMA. In this work, three additional state space models are proposed and estimated using the EM algorithm: • The first model is proposed to estimate the modes of vibration when several tests are performed in the same structural system. Instead of analyse record by record and then compute averages, the EM algorithm is extended for the joint estimation of the proposed state space model using all the available data. • The second state space model is used to estimate the modes of vibration when the number of available sensors is lower than the number of points to be tested. In these cases it is usual to perform several tests changing the position of the sensors from one test to the following (multiple setups of sensors). Here, the proposed state space model and the EM algorithm are used to estimate the modal parameters taking into account the data of all setups. • And last, a state space model is proposed to estimate the modes of vibration in the presence of unmeasured inputs that cannot be modelled as white noise processes. In these cases, the frequency components of the inputs cannot be separated from the eigenfrequencies of the system, and spurious modes are obtained in the identification process. The idea is to measure the response of the structure corresponding to different inputs; then, it is assumed that the parameters common to all the data correspond to the structure (modes of vibration), and the parameters found in a specific test correspond to the input in that test. The problem is solved using the proposed state space model and the EM algorithm. Resumen El análisis modal de un sistema estructural consiste en calcular sus modos de vibración. Para estimar estos modos experimentalmente es preciso excitar el sistema con entradas conocidas y registrar las salidas del sistema en diferentes puntos por medio de sensores. Finalmente, los modos de vibración se calculan utilizando las entradas y salidas registradas. Cuando el sistema es una gran estructura como un puente o un edificio, los experimentos tienen que realizarse in situ, por lo que no es posible registrar entradas al sistema tales como viento, tráfico, . . . Incluso si se aplica una entrada conocida, el procedimiento suele ser complicado y caro, y todavía están presentes perturbaciones no controladas que excitan el sistema durante el test. Estos hechos han llevado a la idea de calcular los modos de vibración utilizando sólo las vibraciones registradas en la estructura y sin tener en cuenta las cargas que las originan, ya sean cargas ambientales (viento, terremotos, . . . ) o cargas de explotación (tráfico, cargas humanas, . . . ). Este procedimiento se conoce en la literatura especializada como Análisis Modal Operacional, y en general consiste en ajustar un modelo matemático a los datos registrados adoptando la hipótesis de que las excitaciones no conocidas son realizaciones de un proceso estocástico estacionario (generalmente ruido blanco). Posteriormente, los modos de vibración se calculan a partir del modelo estimado. El primer problema que se ha investigado en esta tesis es la utilización de máxima verosimilitud y el algoritmo EM (Expectation-Maximization) para la estimación del modelo espacio de los estados en el ámbito del Análisis Modal Operacional. El algoritmo se describe en detalle y también se analiza como aplicarlo cuando se dispone de datos de vibraciones de una estructura. A continuación se compara con otro método muy conocido, el método de los Subespacios. Los estimadores máximo verosímiles presentan una serie de propiedades que los hacen óptimos desde un punto de vista estadístico, pero la propiedad más destacable del algoritmo EM es que puede utilizarse para resolver un amplio abanico de situaciones que se presentan en el Análisis Modal Operacional. En este trabajo se proponen y estiman tres modelos en el espacio de los estados: • El primer modelo se utiliza para estimar los modos de vibración cuando se dispone de datos correspondientes a varios experimentos realizados en la misma estructura. En lugar de analizar registro a registro y calcular promedios, se utiliza algoritmo EM para la estimación conjunta del modelo propuesto utilizando todos los datos disponibles. • El segundo modelo en el espacio de los estados propuesto se utiliza para estimar los modos de vibración cuando el número de sensores disponibles es menor que vi Resumen el número de puntos que se quieren analizar en la estructura. En estos casos es usual realizar varios ensayos cambiando la posición de los sensores de un ensayo a otro (múltiples configuraciones de sensores). En este trabajo se utiliza el algoritmo EM para estimar los parámetros modales teniendo en cuenta los datos de todas las configuraciones. • Por último, se propone otro modelo en el espacio de los estados para estimar los modos de vibración en la presencia de entradas al sistema que no pueden modelarse como procesos estocásticos de ruido blanco. En estos casos, las frecuencias de las entradas no se pueden separar de las frecuencias del sistema y se obtienen modos espurios en la fase de identificación. La idea es registrar la respuesta de la estructura correspondiente a diferentes entradas; entonces se adopta la hipótesis de que los parámetros comunes a todos los registros corresponden a la estructura (modos de vibración), y los parámetros encontrados en un registro específico corresponden a la entrada en dicho ensayo. El problema se resuelve utilizando el modelo propuesto y el algoritmo EM.

Modelos para el análisis dinámico y la predicción a corto plazo de los precios de la electricidad en mercados liberalizados

En esta tesis se va a describir y aplicar de forma novedosa la técnica del alisado exponencial multivariante a la predicción a corto plazo, a un día vista, de los precios horarios de la electricidad, un problema que se está estudiando intensivamente en la literatura estadística y económica reciente. Se van a demostrar ciertas propiedades interesantes del alisado exponencial multivariante que permiten reducir el número de parámetros para caracterizar la serie temporal y que al mismo tiempo permiten realizar un análisis dinámico factorial de la serie de precios horarios de la electricidad. En particular, este proceso multivariante de elevada dimensión se estimará descomponiéndolo en un número reducido de procesos univariantes independientes de alisado exponencial caracterizado cada uno por un solo parámetro de suavizado que variará entre cero (proceso de ruido blanco) y uno (paseo aleatorio). Para ello, se utilizará la formulación en el espacio de los estados para la estimación del modelo, ya que ello permite conectar esa secuencia de modelos univariantes más eficientes con el modelo multivariante. De manera novedosa, las relaciones entre los dos modelos se obtienen a partir de un simple tratamiento algebraico sin requerir la aplicación del filtro de Kalman. De este modo, se podrán analizar y poner al descubierto las razones últimas de la dinámica de precios de la electricidad. Por otra parte, la vertiente práctica de esta metodología se pondrá de manifiesto con su aplicación práctica a ciertos mercados eléctricos spot, tales como Omel, Powernext y Nord Pool. En los citados mercados se caracterizará la evolución de los precios horarios y se establecerán sus predicciones comparándolas con las de otras técnicas de predicción. ABSTRACT This thesis describes and applies the multivariate exponential smoothing technique to the day-ahead forecast of the hourly prices of electricity in a whole new way. This problem is being studied intensively in recent statistics and economics literature. It will start by demonstrating some interesting properties of the multivariate exponential smoothing that reduce drastically the number of parameters to characterize the time series and that at the same time allow a dynamic factor analysis of the hourly prices of electricity series. In particular this very complex multivariate process of dimension 24 will be estimated by decomposing a very reduced number of univariate independent of exponentially smoothing processes each characterized by a single smoothing parameter that varies between zero (white noise process) and one (random walk). To this end, the formulation is used in the state space model for the estimation, since this connects the sequence of efficient univariate models to the multivariate model. Through a novel way, relations between the two models are obtained from a simple algebraic treatment without applying the Kalman filter. Thus, we will analyze and expose the ultimate reasons for the dynamics of the electricity price. Moreover, the practical aspect of this methodology will be shown by applying this new technique to certain electricity spot markets such as Omel, Powernext and Nord Pool. In those markets the behavior of prices will be characterized, their predictions will be formulated and the results will be compared with those of other forecasting techniques.

Spawning and habitat management in salmonid populations at the southern edge of their natural ranges = Reproducción y gestión del hábitat en poblaciones de salmónidos en el extremo meridional de sus distribuciones naturales

Las poblaciones de salmónidos en la Península Ibérica (trucha común, Salmo trutta; y salmón atlántico, Salmo salar) se encuentran cerca del límite meridional de sus distribuciones naturales, y por tanto tienen una gran importancia para la conservación de estas especies. En la presente Tesis se han investigado algunos aspectos de la reproducción y de la gestión del hábitat, con el objeto de mejorar el conocimiento acerca de estas poblaciones meridionales de salmónidos. Se ha estudiado la reproducción de la trucha común en el río Castril (Andalucía, sur de España), donde se ha observado que la freza ocurre desde diciembre hasta abril con el máximo de actividad en febrero. Este hecho representa uno de los periodos reproductivos más tardíos y con mayor duración de toda la distribución natural de la especie. Además, actualmente se sabe que el resto de poblaciones andaluzas tienen periodos de reproducción similares (retrasados y extendidos). Análisis en la escala de la distribución natural de la trucha común, han mostrado que la latitud explica parcialmente tanto la fecha media de reproducción (R2 = 62.8%) como la duración del periodo de freza (R2 = 24.4%) mediante relaciones negativas: a menor latitud, la freza ocurre más tarde y durante más tiempo. Es verosímil que un periodo de freza largo suponga una ventaja para la supervivencia de las poblaciones de trucha en hábitats impredecibles, y por tanto se ha propuesto la siguiente hipótesis, que deberá ser comprobada en el futuro: la duración de la freza es mayor en hábitats impredecibles que en aquellos más predecibles. La elevada tasa de solapamiento de frezaderos observada en el río Castril no se explica únicamente por una excesiva densidad de reproductores. Las hembras de trucha eligieron lugares específicos para construir sus frezaderos en vez de dispersarse aleatoriamente dentro del hábitat adecuado para la freza que tenían disponible. Estas observaciones sugieren que las hembras tienen algún tipo de preferencia por solapar sus frezaderos. Además, en ríos calizos como el Castril, las gravas pueden ser muy cohesivas y difíciles de excavar, por lo que el solapamiento de frezaderos puede suponer una ventaja para la hembra, porque la excavación en sustratos que han sido previamente removidos por frezas anteriores requerirá menos gasto de energía que en sustratos con gravas cohesivas que no han sido alteradas. Por tanto, se ha propuesto la siguiente hipótesis, que deberá ser comprobada en el futuro: las hembras tienen una mayor preferencia por solapar sus frezaderos en ríos con sustratos cohesivos que en ríos con sustratos de gravas sueltas. En el marco de la gestión del hábitat, se han empleado dos enfoques diferentes para la evaluación del hábitat físico, con el objeto de cuantificar los cambios potenciales en la disponibilidad de hábitat, antes de la implementación real de determinadas medidas sobre el hábitat. En primer lugar, se ha evaluado el hábitat físico del salmón atlántico en el río Pas (Cantabria, norte de España), en la escala del microhábitat, empleando la metodología IFIM junto con un modelo hidráulico bidimensional (River2D). Se han simulado una serie de acciones de mejora del hábitat y se han cuantificado los cambios en el hábitat bajo estas acciones. Los resultados mostraron un aumento muy pequeño en la disponibilidad de hábitat, por lo que no sería efectivo implementar estas acciones en este tramo fluvial. En segundo lugar, se ha evaluado el hábitat físico de la trucha común en el río Tajuña (Guadalajara, centro de España), en la escala del mesohábitat, empleando la metodología MesoHABSIM. Actualmente, el río Tajuña está alterado por los usos agrícolas de sus riberas, y por tanto se ha diseñado una restauración para mitigar estos impactos y para llevar al río a un estado más natural. Se ha cuantificado la disponibilidad de hábitat tras la restauración planteada, y los resultados han permitido identificar los tramos en los que la restauración resultaría más eficaz. ABSTRACT Salmonid populations in the Iberian Peninsula (brown trout, Salmo trutta; and Atlantic salmon, Salmo salar) are close to the southern limit of their natural ranges, and therefore they are of great importance for the conservation of the species. In the present dissertation, some aspects of spawning and habitat management have been investigated, in order to improve the knowledge on these southern salmonid populations. Brown trout spawning have been studied in the river Castril (Andalusia, southern Spain), and it has been observed that spawning occurs from December until April with the maximum activity in February. This finding represents one of the most belated and protracted spawning periods within the natural range of the species. Furthermore, it is now known that the rest of Andalusian populations show similar (belated and extended) spawning periods. Broad-scale analyses throughout the brown trout natural range showed that latitude partly explained both spawning mean time (R2 = 62.8%) and spawning duration (R2 = 24.4%) by negative relationships: the lower the latitude, the later the spawning time and the longer the spawning period. It is plausible that a long spawning period would be an advantage for survival of trout populations in unpredictable habitats, and thus the following hypothesis has been proposed, which is yet to be tested: spawning duration is longer in unpredictable than in predictable habitats. High rate of redd superimposition observed in the river Castril was not only caused by high density of spawners. Trout females chose specific sites for redd construction instead of randomly dispersing over the suitable spawning habitat. These observations suggest that female spawners have some kind of preference for superimposing redds. Moreover, in limestone streams such as Castril, unused gravels can be very cohesive and hard to dig, and thus redd superimposition may be an advantage for female, because digging may require less energy expenditure in already used redd sites than in cohesive and embedded unused sites. Hence, the following hypothesis has been proposed, which is yet to be tested: females have a higher preference for superimposing redds in streambeds with cohesive and embedded substrates than in rivers with loose gravels. Within the topic of habitat management, two different approaches have been used for physical habitat assessment, in order to quantify the potential change in habitat availability, prior to the actual implementation of proposed habitat measures. Firstly, physical habitat for Atlantic salmon in the river Pas (Cantabria, northern Spain) has been assessed at the microhabitat scale, using the IFIM approach along with a two dimensional hydraulic model (River2D). Proposed habitat enhancement actions have been simulated and potential habitat change has been quantified. Results showed a very small increasing in habitat availability and therefore it is not worth to implement these measures in this stream reach. Secondly, physical habitat for brown trout in the river Tajuña (Guadalajara, central Spain) has been assessed at the mesohabitat scale, using the MesoHABSIM approach. The river Tajuña is currently impacted by surrounding agricultural uses, and thus restoration was designed to mitigate these impacts and to drive the river to a more natural state. Habitat availability after the planned restoration has been quantified, and the results have permitted to identify in which sites the restoration will be more effective.

State space models for multi-setup operational modal analysis

Operational Modal Analysis consists on estimate the modal parameters of a structure (natural frequencies, damping ratios and modal vectors) from output-only vibration measurements. The modal vectors can be only estimated where a sensor is placed, so when the number of available sensors is lower than the number of tested points, it is usual to perform several tests changing the position of the sensors from one test to the following (multiple setups of sensors): some sensors stay at the same position from setup to setup, and the other sensors change the position until all the tested points are covered. The permanent sensors are then used to merge the mode shape estimated at each setup (or partial modal vectors) into global modal vectors. Traditionally, the partial modal vectors are estimated independently setup by setup, and the global modal vectors are obtained in a postprocess phase. In this work we present two state space models that can be used to process all the recorded setups at the same time, and we also present how these models can be estimated using the maximum likelihood method. The result is that the global mode shape of each mode is obtained automatically, and subsequently, a single value for the natural frequency and damping ratio of the mode is computed. Finally, both models are compared using real measured data.

Prediction of bendig load capacity of timber beams by finite element method simulation of knots and grain deviation

A finite element model was used to simulate timberbeams with defects and predict their maximum load in bending. Taking into account the elastoplastic constitutive law of timber, the prediction of fracture load gives information about the mechanisms of timber failure, particularly with regard to the influence of knots, and their local graindeviation, on the fracture. A finite element model was constructed using the ANSYS element Plane42 in a plane stress 2D-analysis, which equates thickness to the width of the section to create a mesh which is as uniform as possible. Three sub-models reproduced the bending test according to UNE EN 408: i) timber with holes caused by knots; ii) timber with adherent knots which have structural continuity with the rest of the beam material; iii) timber with knots but with only partial contact between knot and beam which was artificially simulated by means of contact springs between the two materials. The model was validated using ten 45 × 145 × 3000 mm beams of Pinus sylvestris L. which presented knots and graindeviation. The fracture stress data obtained was compared with the results of numerical simulations, resulting in an adjustment error less of than 9.7%

Prediction of near field overpressure from quarry blasting

This paper investigates the propagation of airblast or pressure waves in air produced by bench blasting (i.e. detonation of the explosive in a row of blastholes, breaking the burden of rock towards the free vertical face of the block). Peak overpressure is calculated as a function of blasting parameters (explosive mass per delay and velocity at which the detonation sequence proceeds along the bench) and the polar coordinates of the position of interest (distance to the source and azimuth with respect to the free face). The model has been fitted to empirical data using linear least squares. The data set is composed of 122 airblast records monitored at distances less than 400 m in 41 production blasts carried out in two quarries. The model is statistically significant and has a determination coefficient of 0.87. The formula is validated from 12 airblast measurements gathered in five additional blasts.

Modelos de métrica para sistemas electrónicos de adquisición de datos y de procesamiento para investigación clínica con dispositivos cardiacos implantables

RESUMEN Las enfermedades cardiovasculares constituyen en la actualidad la principal causa de mortalidad en el mundo y se prevé que sigan siéndolo en un futuro, generando además elevados costes para los sistemas de salud. Los dispositivos cardiacos implantables constituyen una de las opciones para el diagnóstico y el tratamiento de las alteraciones del ritmo cardiaco. La investigación clínica con estos dispositivos alcanza gran relevancia para combatir estas enfermedades que tanto afectan a nuestra sociedad. Tanto la industria farmacéutica y de tecnología médica, como los propios investigadores, cada día se ven involucrados en un mayor número de proyectos de investigación clínica. No sólo el incremento en su volumen, sino el aumento de la complejidad, están generando mayores gastos en las actividades asociadas a la investigación médica. Esto está conduciendo a las compañías del sector sanitario a estudiar nuevas soluciones que les permitan reducir los costes de los estudios clínicos. Las Tecnologías de la Información y las Comunicaciones han facilitado la investigación clínica, especialmente en la última década. Los sistemas y aplicaciones electrónicos han proporcionado nuevas posibilidades en la adquisición, procesamiento y análisis de los datos. Por otro lado, la tecnología web propició la aparición de los primeros sistemas electrónicos de adquisición de datos, que han ido evolucionando a lo largo de los últimos años. Sin embargo, la mejora y perfeccionamiento de estos sistemas sigue siendo crucial para el progreso de la investigación clínica. En otro orden de cosas, la forma tradicional de realizar los estudios clínicos con dispositivos cardiacos implantables precisaba mejorar el tratamiento de los datos almacenados por estos dispositivos, así como para su fusión con los datos clínicos recopilados por investigadores y pacientes. La justificación de este trabajo de investigación se basa en la necesidad de mejorar la eficiencia en la investigación clínica con dispositivos cardiacos implantables, mediante la reducción de costes y tiempos de desarrollo de los proyectos, y el incremento de la calidad de los datos recopilados y el diseño de soluciones que permitan obtener un mayor rendimiento de los datos mediante la fusión de datos de distintas fuentes o estudios. Con este fin se proponen como objetivos específicos de este proyecto de investigación dos nuevos modelos: - Un modelo de recuperación y procesamiento de datos para los estudios clínicos con dispositivos cardiacos implantables, que permita estructurar y estandarizar estos procedimientos, con el fin de reducir tiempos de desarrollo Modelos de Métrica para Sistemas Electrónicos de Adquisición de Datos y de Procesamiento para Investigación Clínica con Dispositivos Cardiacos Implantables de estas tareas, mejorar la calidad del resultado obtenido, disminuyendo en consecuencia los costes. - Un modelo de métrica integrado en un Sistema Electrónico de Adquisición de Datos (EDC) que permita analizar los resultados del proyecto de investigación y, particularmente del rendimiento obtenido del EDC, con el fin de perfeccionar estos sistemas y reducir tiempos y costes de desarrollo del proyecto y mejorar la calidad de los datos clínicos recopilados. Como resultado de esta investigación, el modelo de procesamiento propuesto ha permitido reducir el tiempo medio de procesamiento de los datos en más de un 90%, los costes derivados del mismo en más de un 85% y todo ello, gracias a la automatización de la extracción y almacenamiento de los datos, consiguiendo una mejora de la calidad de los mismos. Por otro lado, el modelo de métrica posibilita el análisis descriptivo detallado de distintos indicadores que caracterizan el rendimiento del proyecto de investigación clínica, haciendo factible además la comparación entre distintos estudios. La conclusión de esta tesis doctoral es que los resultados obtenidos han demostrado que la utilización en estudios clínicos reales de los dos modelos desarrollados ha conducido a una mejora en la eficiencia de los proyectos, reduciendo los costes globales de los mismos, disminuyendo los tiempos de ejecución, e incrementando la calidad de los datos recopilados. Las principales aportaciones de este trabajo de investigación al conocimiento científico son la implementación de un sistema de procesamiento inteligente de los datos almacenados por los dispositivos cardiacos implantables, la integración en el mismo de una base de datos global y optimizada para todos los modelos de dispositivos, la generación automatizada de un repositorio unificado de datos clínicos y datos de dispositivos cardiacos implantables, y el diseño de una métrica aplicada e integrable en los sistemas electrónicos de adquisición de datos para el análisis de resultados de rendimiento de los proyectos de investigación clínica. ABSTRACT Cardiovascular diseases are the main cause of death worldwide and it is expected to continue in the future, generating high costs for health care systems. Implantable cardiac devices have become one of the options for diagnosis and treatment of cardiac rhythm disorders. Clinical research with these devices has acquired great importance to fight against these diseases that affect so many people in our society. Both pharmaceutical and medical technology companies, and also investigators, are involved in an increasingly number of clinical research projects. The growth in volume and the increase in medical research complexity are contributing to raise the expenditure level associated with clinical investigation. This situation is driving health care sector companies to explore new solutions to reduce clinical trial costs. Information and Communication Technologies have facilitated clinical research, mainly in the last decade. Electronic systems and software applications have provided new possibilities in the acquisition, processing and analysis of clinical studies data. On the other hand, web technology contributed to the appearance of the first electronic data capture systems that have evolved during the last years. Nevertheless, improvement of these systems is still a key aspect for the progress of clinical research. On a different matter, the traditional way to develop clinical studies with implantable cardiac devices needed an improvement in the processing of the data stored by these devices, and also in the merging of these data with the data collected by investigators and patients. The rationale of this research is based on the need to improve the efficiency in clinical investigation with implantable cardiac devices, by means of reduction in costs and time of projects development, as well as improvement in the quality of information obtained from the studies and to obtain better performance of data through the merging of data from different sources or trials. The objective of this research project is to develop the next two models: • A model for the retrieval and processing of data for clinical studies with implantable cardiac devices, enabling structure and standardization of these procedures, in order to reduce the time of development of these tasks, to improve the quality of the results, diminish therefore costs. • A model of metric integrated in an Electronic Data Capture system (EDC) that allow to analyze the results of the research project, and particularly the EDC performance, in order to improve those systems and to reduce time and costs of the project, and to get a better quality of the collected clinical data. As a result of this work, the proposed processing model has led to a reduction of the average time for data processing by more than 90 per cent, of related costs by more than 85 per cent, and all of this, through automatic data retrieval and storage, achieving an improvement of quality of data. On the other hand, the model of metrics makes possible a detailed descriptive analysis of a set of indicators that characterize the performance of each research project, allowing inter‐studies comparison. This doctoral thesis results have demonstrated that the application of the two developed models in real clinical trials has led to an improvement in projects efficiency, reducing global costs, diminishing time in execution, and increasing quality of data collected. The main contributions to scientific knowledge of this research work are the implementation of an intelligent processing system for data stored by implantable cardiac devices, the integration in this system of a global and optimized database for all models of devices, the automatic creation of an unified repository of clinical data and data stored by medical devices, and the design of a metric to be applied and integrated in electronic data capture systems to analyze the performance results of clinical research projects.