Operational Modal Analysis on laminated glass beams

Laminated glass is a sandwich element consisting of two or more glass sheets, with one or more interlayers of polyvinyl butyral (PVB). The dynamic response of laminated glass beams and plates can be predicted using analytical or numerical models in which the glass and the PVB are usually modelled as linear-elastic and linear viscoelastic materials, respectively. In this work the dynamic behavior of laminated glass beams are predicted using a finite element model and the analytical model of Ross-Kerwin-Ungar. The numerical and analytical results are compared with those obtained by operational modal analysis performed at different temperatures.

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

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.

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.

Operational characterisation of a Micro-SME producing farmhouse cheese in the south of Venezuela

A piece of research is presented that was conducted on the Guayanes Farmhouse Telita Cheese Producers Network located in the Piar and Padre Chien rural municipalities of Bolivar state in Venezuela. Guayanes telita cheese is a regional dairy product. The producers are to be found in a rural area with a high potential for marketing the label in the Southern Common Market (MERCOSUR). This market is the focal point of the strategic importance of this study for the Region and the Country. The research is of a descriptive scope conducted in the field. A questionnaire based on good food production practice was used as a data gathering technique. The final sample comprised 30 production units. Statistical processing was performed with version 15.2 of the STATGRAPHICS Centurion computational tool. The results would appear to confirm previous studies that point to the existence of factors that prevent these Micro-SMEs from guaranteeing the food safety of the product. The results indicate that new lines of research need to be opened up. These are oriented towards formulating strategies for the continuous improvement of these micro-SMEs, including quality control indicators.

Learning Analytics and Interactions in Virtual Learning Environments. A Comparative Study of Typologies and their Relationship with Academic Performance

Analysis of learning data (learning analytics) is a new research field with high growth potential. The main objective of Learning analytics is the analysis of data (interactions being the basic data unit) generated in virtual learning environments, in order to maximize the outcomes of the learning process; however, a consensus has not been reached yet on which interactions must be measured and what is their influence on learning outcomes. This research is grounded on the study of e-learning interaction typologies and their relationship with students? academic performance, by means of a comparative study between different interaction typologies (based on the agents involved, frequency of use and participation mode). The main conclusions are a) that classifications based on agents offer a better explanation of academic performance; and b) that each of the three typologies are able to explain academic performance in terms of some of their components (student-teacher and student-student interactions, evaluating students interactions and active interactions, respectively), with the other components being nonrelevant.

Latest developments in data analysis tools for disruption prediction and for the exploration of multimachine operational spaces.

In the last years significant efforts have been devoted to the development of advanced data analysis tools to both predict the occurrence of disruptions and to investigate the operational spaces of devices, with the long term goal of advancing the understanding of the physics of these events and to prepare for ITER. On JET the latest generation of the disruption predictor called APODIS has been deployed in the real time network during the last campaigns with the new metallic wall. Even if it was trained only with discharges with the carbon wall, it has reached very good performance, with both missed alarms and false alarms in the order of a few percent (and strategies to improve the performance have already been identified). Since for the optimisation of the mitigation measures, predicting also the type of disruption is considered to be also very important, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been developed. This technique allows automatic classification of an incoming disruption with a success rate of better than 85%. Various other manifold learning tools, particularly Principal Component Analysis and Self Organised Maps, are also producing very interesting results in the comparative analysis of JET and ASDEX Upgrade (AUG) operational spaces, on the route to developing predictors capable of extrapolating from one device to another.

Qualitative operational risk software -development of a software tool for determining the root of operational risk

This article shows software that allows determining the statistical behavior of qualitative data originating surveys previously transformed with a Likert’s scale to quantitative data. The main intention is offer to users a useful tool to know statistics' characteristics and forecasts of financial risks in a fast and simple way. Additionally,this paper presents the definition of operational risk. On the other hand, the article explains different techniques to do surveys with a Likert’s scale (Avila, 2008) to know expert’s opinion with the transformation of qualitative data to quantitative data. In addition, this paper will show how is very easy to distinguish an expert’s opinion related to risk, but when users have a lot of surveys and matrices is very difficult to obtain results because is necessary to compare common data. On the other hand, statistical value representative must be extracted from common data to get weight of each risk. In the end, this article exposes the development of “Qualitative Operational Risk Software” or QORS by its acronym, which has been designed to determine the root of risks in organizations and its value at operational risk OpVaR (Jorion, 2008; Chernobai et al, 2008) when input data comes from expert’s opinion and their associated matrices.

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.

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.

VISIONS Vehicular communication Improvement : solution based on IMS Operational Nodes and Services

Digital services and communications in vehicular scenarios provide the essential assets to improve road transport in several ways like reducing accidents, improving traffic efficiency and optimizing the transport of goods and people. Vehicular communications typically rely on VANET (Vehicular Ad hoc Networks). In these networks vehicles communicate with each other without the need of infrastructure. VANET are mainly oriented to disseminate information to the vehicles in certain geographic area for time critical services like safety warnings but present very challenging requirements that have not been successfully fulfilled nowadays. Some of these challenges are; channel saturation due to simultaneous radio access of many vehicles, routing protocols in topologies that vary rapidly, minimum quality of service assurance and security mechanisms to efficiently detect and neutralize malicious attacks. Vehicular services can be classified in four important groups: Safety, Efficiency, Sustainability and Infotainment. The benefits of these services for the transport sector are clear but many technological and business challenges need to be faced before a real mass market deployment. Service delivery platforms are not prepared for fulfilling the needs of this complex environment with restrictive requirements due to the criticism of some services To overcome this situation, we propose a solution called VISIONS “Vehicular communication Improvement: Solution based on IMS Operational Nodes and Services”. VISIONS leverages on IMS subsystem and NGN enablers, and follows the CALM reference Architecture standardized by ISO. It also avoids the use of Road Side Units (RSUs), reducing complexity and high costs in terms of deployment and maintenance. We demonstrate the benefits in the following areas: 1. VANET networks efficiency. VISIONS provide a mechanism for the vehicles to access valuable information from IMS and its capabilities through a cellular channel. This efficiency improvement will occur in two relevant areas: a. Routing mechanisms. These protocols are responsible of carrying information from a vehicle to another (or a group of vehicles) using multihop mechanisms. We do not propose a new algorithm but the use of VANET topology information provided through our solution to enrich the performance of these protocols. b. Security. Many aspects of security (privacy, key, authentication, access control, revocation mechanisms, etc) are not resolved in vehicular communications. Our solution efficiently disseminates revocation information to neutralize malicious nodes in the VANET. 2. Service delivery platform. It is based on extended enablers, reference architectures, standard protocols and open APIs. By following this approach, we reduce costs and resources for service development, deployment and maintenance. To quantify these benefits in VANET networks, we provide an analytical model of the system and simulate our solution in realistic scenarios. The simulations results demonstrate how VISIONS improves the performance of relevant routing protocols and is more efficient neutralizing security attacks than the widely proposed solutions based on RSUs. Finally, we design an innovative Social Network service based in our platform, explaining how VISIONS facilitate the deployment and usage of complex capabilities. RESUMEN Los servicios digitales y comunicaciones en entornos vehiculares proporcionan herramientas esenciales para mejorar el transporte por carretera; reduciendo el número de accidentes, mejorando la eficiencia del tráfico y optimizando el transporte de mercancías y personas. Las comunicaciones vehiculares generalmente están basadas en redes VANET (Vehicular Ad hoc Networks). En dichas redes, los vehículos se comunican entre sí sin necesidad de infraestructura. Las redes VANET están principalmente orientadas a difundir información (por ejemplo advertencias de seguridad) a los vehículos en determinadas zonas geográficas, pero presentan unos requisitos muy exigentes que no se han resuelto con éxito hasta la fecha. Algunos de estos retos son; saturación del canal de acceso de radio debido al acceso simultáneo de múltiples vehículos, la eficiencia de protocolos de encaminamiento en topologías que varían rápidamente, la calidad de servicio (QoS) y los mecanismos de seguridad para detectar y neutralizar los ataques maliciosos de manera eficiente. Los servicios vehiculares pueden clasificarse en cuatro grupos: Seguridad, Eficiencia del tráfico, Sostenibilidad, e Infotainment (información y entretenimiento). Los beneficios de estos servicios para el sector son claros, pero es necesario resolver muchos desafíos tecnológicos y de negocio antes de una implementación real. Las actuales plataformas de despliegue de servicios no están preparadas para satisfacer las necesidades de este complejo entorno con requisitos muy restrictivos debido a la criticidad de algunas aplicaciones. Con el objetivo de mejorar esta situación, proponemos una solución llamada VISIONS “Vehicular communication Improvement: Solution based on IMS Operational Nodes and Services”. VISIONS se basa en el subsistema IMS, las capacidades NGN y es compatible con la arquitectura de referencia CALM estandarizado por ISO para sistemas de transporte. También evita el uso de elementos en las carreteras, conocidos como Road Side Units (RSU), reduciendo la complejidad y los altos costes de despliegue y mantenimiento. A lo largo de la tesis, demostramos los beneficios en las siguientes áreas: 1. Eficiencia en redes VANET. VISIONS proporciona un mecanismo para que los vehículos accedan a información valiosa proporcionada por IMS y sus capacidades a través de un canal de celular. Dicho mecanismo contribuye a la mejora de dos áreas importantes: a. Mecanismos de encaminamiento. Estos protocolos son responsables de llevar información de un vehículo a otro (o a un grupo de vehículos) utilizando múltiples saltos. No proponemos un nuevo algoritmo de encaminamiento, sino el uso de información topológica de la red VANET a través de nuestra solución para enriquecer el funcionamiento de los protocolos más relevantes. b. Seguridad. Muchos aspectos de la seguridad (privacidad, gestión de claves, autenticación, control de acceso, mecanismos de revocación, etc) no están resueltos en las comunicaciones vehiculares. Nuestra solución difunde de manera eficiente la información de revocación para neutralizar los nodos maliciosos en la red. 2. Plataforma de despliegue de servicios. Está basada en capacidades NGN, arquitecturas de referencia, protocolos estándar y APIs abiertos. Siguiendo este enfoque, reducimos costes y optimizamos procesos para el desarrollo, despliegue y mantenimiento de servicios vehiculares. Para cuantificar estos beneficios en las redes VANET, ofrecemos un modelo de analítico del sistema y simulamos nuestra solución en escenarios realistas. Los resultados de las simulaciones muestran cómo VISIONS mejora el rendimiento de los protocolos de encaminamiento relevantes y neutraliza los ataques a la seguridad de forma más eficientes que las soluciones basadas en RSU. Por último, diseñamos un innovador servicio de red social basado en nuestra plataforma, explicando cómo VISIONS facilita el despliegue y el uso de las capacidades NGN.

Operational Modal Analysis using Expectation Maximization Algorithm

This paper presents a time-domain stochastic system identification method based on Maximum Likelihood Estimation and the Expectation Maximization algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated applying the proposed identification method to a set of 100 simulated cases. The numerical results show that the proposed method estimates all the modal parameters reasonably well in the presence of 30% measurement noise even. Finally, advantages and disadvantages of the method have been discussed.

Operational modal analisys using joint statistical analysis of multiple records

In Operational Modal Analysis (OMA) of a structure, the data acquisition process may be repeated many times. In these cases, the analyst has several similar records for the modal analysis of the structure that have been obtained at di�erent time instants (multiple records). The solution obtained varies from one record to another, sometimes considerably. The differences are due to several reasons: statistical errors of estimation, changes in the external forces (unmeasured forces) that modify the output spectra, appearance of spurious modes, etc. Combining the results of the di�erent individual analysis is not straightforward. To solve the problem, we propose to make the joint estimation of the parameters using all the records. This can be done in a very simple way using state space models and computing the estimates by maximum-likelihood. The method provides a single result for the modal parameters that combines optimally all the records.

Deriving the full-reducing Krivine machine from the small-step operational semantics of normal order

We derive by program transformation Pierre Crégut s full-reducing Krivine machine KN from the structural operational semantics of the normal order reduction strategy in a closure-converted pure lambda calculus. We thus establish the correspondence between the strategy and the machine, and showcase our technique for deriving full-reducing abstract machines. Actually, the machine we obtain is a slightly optimised version that can work with open terms and may be used in implementations of proof assistants.

Operational costs and reliability in a large rural electrification programme based on solar home systems

Experiences in decentralized rural electrification programmes using solar home systems have suffered difficulties during the operation and maintenance phase, due in many cases, to the underestimation of the maintenance cost, because of the decentralized character of the activity, and also because the reliability of the solar home system components is frequently unknown. This paper reports on the reliability study and cost characterization achieved in a large photovoltaic rural electrification programme carried out in Morocco. The paper aims to determinate the reliability features of the solar systems, focusing in the in-field testing for batteries and photovoltaic modules. The degradation rates for batteries and PV modules have been extracted from the in-field experiments. On the other hand, the main costs related to the operation and maintenance activity have been identified with the aim of establishing the main factors that lead to the failure of the quality sustainability in many rural electrification programmes.