Flexible data input layer architecture (FDILA) for quick-response decision making tools in volatile manufacturing systems

This paper proposes the foundation for a flexible data input management system as a vital part of a generic solution for quick-response decision making. Lack of a comprehensive data input layer between data acquisition and processing systems has been realized and thought of. The proposed FDILA is applicable to a wide variety of volatile manufacturing environments. It provides a generic platform that enables systems designers to define any number of data entry points and types regardless of their make and specifications in a standard fashion. This is achieved by providing a variable definition layer immediately on top of the data acquisition layer and before data pre-processing layer. For proof of concept, National Instruments’ Labview data acquisition software is used to simulate a typical shop floor data acquisition system. The extracted data can then be fed into a data mining module that builds cost modeling functions involving the plant’s Key Performance Factors

Overview of the JET results in support to ITER

The 2014–2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at βN ~ 1.8 and n/nGW ~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D–T campaign and 14 MeV neutron calibration strategy are reviewed.European Commission (EUROfusion 633053

Deep Predictive Models for Collision Risk Assessment in Autonomous Driving

In this paper, we investigate a predictive approach for collision risk assessment in autonomous and assisted driving. A deep predictive model is trained to anticipate imminent accidents from traditional video streams. In particular, the model learns to identify cues in RGB images that are predictive of hazardous upcoming situations. In contrast to previous work, our approach incorporates (a) temporal information during decision making, (b) multi-modal information about the environment, as well as the proprioceptive state and steering actions of the controlled vehicle, and (c) information about the uncertainty inherent to the task. To this end, we discuss Deep Predictive Models and present an implementation using a Bayesian Convolutional LSTM. Experiments in a simple simulation environment show that the approach can learn to predict impending accidents with reasonable accuracy, especially when multiple cameras are used as input sources.Comment: 8 pages, 4 figure

Trick or Heat? Manipulating Critical Temperature-Based Control Systems Using Rectification Attacks

Temperature sensing and control systems are widely used in the closed-loop control of critical processes such as maintaining the thermal stability of patients, or in alarm systems for detecting temperature-related hazards. However, the security of these systems has yet to be completely explored, leaving potential attack surfaces that can be exploited to take control over critical systems. In this paper we investigate the reliability of temperature-based control systems from a security and safety perspective. We show how unexpected consequences and safety risks can be induced by physical-level attacks on analog temperature sensing components. For instance, we demonstrate that an adversary could remotely manipulate the temperature sensor measurements of an infant incubator to cause potential safety issues, without tampering with the victim system or triggering automatic temperature alarms. This attack exploits the unintended rectification effect that can be induced in operational and instrumentation amplifiers to control the sensor output, tricking the internal control loop of the victim system to heat up or cool down. Furthermore, we show how the exploit of this hardware-level vulnerability could affect different classes of analog sensors that share similar signal conditioning processes. Our experimental results indicate that conventional defenses commonly deployed in these systems are not sufficient to mitigate the threat, so we propose a prototype design of a low-cost anomaly detector for critical applications to ensure the integrity of temperature sensor signals.Comment: Accepted at the ACM Conference on Computer and Communications Security (CCS), 201

Robust scaling in fusion science: case study for the L-H power threshold

In regression analysis for deriving scaling laws in the context of fusion studies, standard regression methods are usually applied, of which ordinary least squares (OLS) is the most popular. However, concerns have been raised with respect to several assumptions underlying OLS in its application to fusion data. More sophisticated statistical techniques are available, but they are not widely used in the fusion community and, moreover, the predictions by scaling laws may vary significantly depending on the particular regression technique. Therefore we have developed a new regression method, which we call geodesic least squares regression (GLS), that is robust in the presence of significant uncertainty on both the data and the regression model. The method is based on probabilistic modeling of all variables involved in the scaling expression, using adequate probability distributions and a natural similarity measure between them (geodesic distance). In this work we revisit the scaling law for the power threshold for the L-to-H transition in tokamaks, using data from the multi-machine ITPA databases. Depending on model assumptions, OLS can yield different predictions of the power threshold for ITER. In contrast, GLS regression delivers consistent results. Consequently, given the ubiquity and importance of scaling laws and parametric dependence studies in fusion research, GLS regression is proposed as a robust and easily implemented alternative to classic regression techniques

Study and optimization of magnetized ICRF discharges for tokamak wall conditioning and assessment of the applicability to ITER

Het ambitieuze ITER-tokamakproject is momenteel het toonaangevende onderwerp in het wereldwijde onderzoek naar magnetische fusie. In deze experimentele tokamak zullen brandstofmengsels van deuterium en tritium sterk verhit worden tot de vereiste fusietemperatuur van ongeveer 150 miljoen graden. Bij deze hoge temperaturen verkrijgt men een plasma. De prestaties van fusieplasmas zijn sterk afhankelijk van de interactie tussen het plasma en de reactorwandcomponenten. Een noodzakelijke methode om de gevolgen van de plasma-wand-interactie te controleren bestaat uit het optimaliseren van de staat van de reactorwandoppervlakken, namelijk wandconditionering, met behulp van specifieke plasma-ontladingen met lage temperaturen. De kwalificatie van routine wandconditioneringsontladingen toepasbaar in de tokamak ITER heeft een hoge prioriteit binnen het magnetische fusieonderzoek. Dit proefschrift kadert in het internationale R&D-programma rond de wandconditioneringstechniek “Ion Cyclotron Wall Conditioning” (ICWC) dat als doel heeft de ICWC-techniek te consolideren en de toepasbaarheid ervan op ITER te kwalificeren. Het omvat zowel experimenteel werk op vier Europese tokamaks, nl. TORE SUPRA, TEXTOR, ASDEX Upgrade en JET, waarbij de efficientie van ICWC voor specifieke conditioneringsdoelstellingen werd nagegaan en geoptimaliseerd, als het modeleren van de ICWC-conditioneringsplasmas en de plasma-wand-interactie tijdens ICWC. De toepasbaarheid van de techniek voor specifieke conditioneringsdoelstellingen op ITER werd aangetoond, en verdere onderzoeksdoelstellingen werden geïdentificeerd