A programmable web platform for distributed access, analysis, and visualization of data

© 2023. The authors. This document is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by /4.0/ This document is the published version of a published work that appeared in final form in Fusion Engineering and Design .Daily work of Fusion Data Research (FDR) scientists faces three practical challenges: (i) getting access to vast amounts of validated, curated, and (ideally) annotated discharge data, (ii) applying a wide variety of standard, domain-specific, and home-made analysis and visualization software libraries and routines, and (iii) using fast, specialized, and not easy to obtain hardware and software installations. This paper introduces a novel web platform that addresses these three challenges in a federated way. Based on a client–server architecture, the new platform allows for easy use and exchange of curated data, validated analysis and visualization routines, and even networked hardware and software installations among the FDR community. This exchange goes beyond the mere use of a code repository, but facilitates the creation of an actual ready-to-use network of computers which can be used remotely to configure and perform data analysis. The network functions in a federated way, in which each member of the community contributes, using the same web platform, with its data, programming experience, and hardware and software availability. The platform is open source

A Systematic Two-Layer Approach to Develop Web-based Experimentation Environments for Control Engineering Education

This paper introduces the systematic approach currently used by the Department of Computer Science and Automatic Control of the Spanish University of Distance Learning (UNED) to develop Web-based laboratories for distance learning of topics with high technical contents such as control engineering. This approach differentiates two layers in the construction of web- based laboratories: the experimentation layer and the e-learning layer. For the experimentation layer, LabVIEW and data acquisition boards from National Instruments are used to create the server-side applications and Easy Java Simulations for the client-side interfaces. For the e-learning layer, the eMersion environment is used to support the required flexible educational scheme. This paper describes the programming techniques implemented and the design considerations that justify these particular choices. As an llustrative case-study, an example of development of a web-based application is discussed, in which an electrical drive servo-motor is introduced as a convenient setup to practice with motion control applications. Other significant examples of web-based experiments developed by the authors are also reported

Knowledge systems for real experimentation by means of industrial automation cells

Comunicación presentada a las XXXIX Jornadas de Automática, celebradas en Badajoz del 5 al 7 de Septiembre de 2018 y organizada por la Universidad de Extremadura.En la actualidad, las amenazas hacia las infraestructuras críticas están consideradas por la UE (Unión Europea) así como por otros estamentos internacionales, uno de los riesgos más graves para la estabilidad de sus estados, afectando su disfuncionalidad gravemente a la economía y la sociedad. Ello se debe, específicamente, a que los avances constantes en las tecnologías de la información y las comunicaciones se trasladan a los Sistemas de Control Industrial (SCI) proporcionando una gran flexibilidad de interconexión gracias a su escalabilidad y a modelos con una conectividad cada vez más simple e intuitiva. El uso de las redes de comunicación hace que estos sistemas sean altamente vulnerables, ya que no fueron diseñados originalmente para este tipo de expansión o formas de comunicaciones. En sus orígenes fueron diseñados con el propósito principal de otorgar la máxima disponibilidad de procesos. Sin embargo, hoy en día, la disponibilidad sigue siendo su misión principal. En este trabajo, se presenta el sistema SICERCAI, el cual aporta nuevas capacidades de investigación, desarrollo, simulación y banco de pruebas del funcionamiento de estos sistemas. A su vez, otorga capacidades de anticipación del comportamiento de un sistema en producción industrial y, como consecuencia directa, altas capacidades de ciberresiliencia. Como es un sistema abierto a la interconexión, permite la construcción de Células de Automatización Industrial (CAI) con elementos de los diferentes fabricantes de componentes industriales, pudiéndose agregar al sistema SICERCAI para cubrir el 100% de las posibilidades arquitectónicas existentes en la industria actual. De esta manera se consiguen recrear entornos industriales de carácter híbrido, siendo este aspecto el que más se asemeja a la realidad en la industria.This work, by the development of the SIKERCIA system, provides new capacities of research, development, simulation and testing of the functioning of critical infrastructures, and the capacity of anticipating the behavior of a system in industrial production. At the same time, SIKERCIA provides high capacities of cyber-resilience and also describes the condition of maturity with regard to the cybersecurity of the services implemented in SIKERCIA and catalogued as essential. All the above is provided by a system that has been tested, analyzing industrial environments. As it is a system open to interconnection, it allows the construction of Industrial Automation Cells using industrial components from different manufacturers, which can be added to the SIKERCIA system to cover 100% of the existing architectural possibilities in the current industry.Ministerio de Economía y Competitividad. Proyectos ENE2015-64914-C3-2-R y DPI2017-84259-C2-2-R.peerReviewe

Desarrollo de un entorno colaborativo para aplicaciones de fusión

[Resumen] El entorno colaborativo desarrollado permite realizar un envío de tareas a ser procesadas en clusters de supercomputación, sin necesidad de que los usuarios de las mismas deban conocer la infraestructura subyacente o estar familirizados con las órdenes de más bajo nivel necesarias para interactuar con estos sistemas.Este trabajo ha sido parcialmente financiado por el Ministerio de Economía y Competitividad, dentro de los proyectos ENE2015-64914-C3-2-R, ENE2015-64914-C3-1-R, ENE2012-38970-C04-03 y DPI2014-55932-C2-2-Rhttps://doi.org/10.17979/spudc.978849749808

Results of the JET real-time disruption predictor in the ITER-like wall campaigns

The impact of disruptions in JET became even more important with the replacement of the previous Carbon Fiber Composite (CFC) wall with a more fragile full metal ITER-like wall (ILW). The development of robust disruption mitigation systems is crucial for JET (and also for ITER). Moreover, a reliable real-time (RT) disruption predictor is a pre-requisite to any mitigation method. The Advance Predictor Of DISruptions (APODIS) has been installed in the JET Real-Time Data Network (RTDN) for the RT recognition of disruptions. The predictor operates with the new ILW but it has been trained only with discharges belonging to campaigns with the CFC wall. 7 realtime signals are used to characterize the plasma status (disruptive or non-disruptive) at regular intervals of 1 ms. After the first 3 JET ILW campaigns (991 discharges), the success rate of the predictor is 98.36% (alarms are triggered in average 426 ms before the disruptions). The false alarm and missed alarm rates are 0.92% and 1.64%

Overview of JET Results

AbstrAct Recent advances in data mining allow the automatic recognition of physical phenomena in the databases of fusion devices without human intervention. This is important to create large databases of physical events (thereby increasing the statistical relevance) in an unattended manner. Important examples are the L/H and H/L transitions. In this contribution, a novel technique is introduced to automatically locate H/L transitions in JET by using conformal predictors. The focus is on H/L transitions because typically there is not a clear signature in the time series of the most widely available signals to recognize the change of confinement. Conformal predictors hedge their prediction by means of two parameters: confidence and credibility. The technique has been based on binary supervised classifiers to separate the samples of the respective confinement modes. Results with several underlying classifiers are presented

Providing Collaborative Support to Virtual and Remote Laboratories

Virtual and remote laboratories (VRLs) are e-learning resources that enhance the accessibility of experimental setups providing a distance teaching framework which meets the student's hands-on learning needs. In addition, online collaborative communication represents a practical and a constructivist method to transmit the knowledge and experience from the teacher to students, overcoming physical distance and isolation. This paper describes the extension of two open source tools: (1) the learning management system Moodle, and (2) the tool to create VRLs Easy Java Simulations (EJS). Our extension provides: (1) synchronous collaborative support to any VRL developed with EJS (i.e., any existing VRL written in EJS can be automatically converted into a collaborative lab with no cost), and (2) support to deploy synchronous collaborative VRLs into Moodle. Using our approach students and/or teachers can invite other users enrolled in a Moodle course to a real-time collaborative experimental session, sharing and/or supervising experiences at the same time they practice and explore experiments using VRLs.This work was supported by the Spanish Government under the CICYT Project DPI2007-61068 and the GITE grant of the Technology and Educational Innovation Vice-President Office of the University of Alicante

Implementation of the disruption predictor APODIS in JET Real Time Network using the MARTe framework

Disruptions in tokamaks devices are unavoidable, and they can have a significant impact on machine integrity. So it is very important have mechanisms to predict this phenomenon. Disruption prediction is a very complex task, not only because it is a multi-dimensional problem, but also because in order to be effective, it has to detect well in advance the actual disruptive event, in order to be able to use successful mitigation strategies. With these constraints in mind a real-time disruption predictor has been developed to be used in JET tokamak. The predictor has been designed to run in the Multithreaded Application Real-Time executor (MARTe) framework. The predictor ?Advanced Predictor Of DISruptions? (APODIS) is based on Support Vector Machine (SVM)

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

Mejora de la calidad docente por la investigación en el sector industrial

Motivación del alumno mediante nuevas metodologías presenciales derivadas de la investigación aplicada y orientadas hacia el emprendimiento en el sector industrial. Las metodologías encaminadas a dar solución en los desarrollos de investigación se utilizan como ejemplos significativos en las materias que forman parte del proyecto