Analysis of low load transients for the Vandellòs-II NPP: Application to operation and control support

The Technical University of Catalonia (UPC) has been jointly working with the Asociación Nuclear Ascó-Vandellòs (ANAV) for a number of years in order to establish, qualify and use best estimate (BE) models for the reactors under the control of ANAV. ANAV is the consortium that is responsible for operation of the Ascó and Vandellòs-II reactors. The reactors are Westinghouse-design three-loop PWRs with an approximate electrical power of 1000 MW. The existing integral plant models for each plant are currently used for many different purposes among which are support of plant operation and control. Quite a number of studies have been done in order to improve both safety and plant competitiveness. Most of these dynamic analyses were carried out in relation to transients starting at nominal full power or at least, very close to full power. This paper develops a specific use of the Vandellòs-II plant model for operation and control support at low power involving new ranges of system actuation parameters. It also examines scenarios that are somewhat different from those typically analysed. The study starts showing the results of an assessment case, which is a start-up test and provides some additional qualification, and subsequently attempts to establish calculations to support both an improvement in feed water controls and to set up operating recommendations for low-load manual operation of feed water turbo-pump. Both results hopefully, will produce an outcome, which leads to an improvement in safety and reduces reactor trip probability.     

Perceived Visual Complexity and Visual Search Performance of Automotive Instrument Cluster: A Quantitative Measurement Study

Advancements in technology have spurred the development of new in-vehicle applications. Drivers are faced with different driving contexts due to an increase in the number of devices that provide a wealth of diverse information. However, such a scenario can cause drivers to become distracted. Therefore, research on how the presentation of visual information can affect drivers’ performance is important. In this study, an analysis of quantifiable measurements that affect drivers’ perception of visual complexity and visual search performance was conducted. A questionnaire was administered to assess subjective perception of visual complexity, and a user experiment using eye tracking was designed to explore participants’ visual search performance. The results of subjective visual complexity perception and visual search performance suggested that some objective measurement variables were significantly related only to perceived visual complexity, whereas others affected both subjective and behavioral measurements. Thus it is possible to predict which quantifiable measurement variables affect subjective perception of visual complexity and which affect visual search performance. Therefore, this study allows understanding and explaining of perception of visual complexity by quantifiable measurements and the different ways by which these measurements affect visual search performance.     

Robust network monitoring in the presence of non-cooperative traffic queries

We present the design of a predictive load shedding scheme for a network monitoring platform that supports multiple and competing traffic queries. The proposed scheme can anticipate overload situations and minimize their impact on the accuracy of the traffic queries. The main novelty of our approach is that it considers queries as black boxes, with arbitrary (and highly variable) input traffic and processing cost. Our system only requires a high-level specification of the accuracy requirements of each query to guide the load shedding procedure and assures a fair allocation of computing resources to queries in a non-cooperative environment. We present an implementation of our load shedding scheme in an existing network monitoring system and evaluate it with a diverse set of traffic queries. Our results show that, with the load shedding mechanism in place, the monitoring system can preserve the accuracy of the queries within predefined error bounds even during extreme overload conditions.     

EEG signal preprocessing for biometric recognition

Electroencephalography (EEG) has been recently investigated as a biometric modality for automatic people recognition purposes. Several studies have shown that brain signals possess subject-specific traits that allow distinguishing people. Nonetheless, extracting discriminative characteristics from EEG recordings may be a challenging task, due to the significant presence of artifacts in the acquired data. In order to cope with such issue, in this paper we evaluate the effectiveness of some preprocessing techniques in automatically removing undesired EEG contributions, with the aim of improving the achievable recognition rates. Specifically, methods based on blind source separation and sample entropy estimation are here investigated. An extensive set of experimental tests, performed over a large database comprising recordings taken from 50 healthy subjects during three distinct sessions spanning a period of about one month, in both eyes-closed and eyes-open conditions, is carried out to analyze the performance of the proposed approaches.     

Tool integration for flexible simulation of distributed algorithms

Over the last two decades, considerable research has been done in distributed operating systems, which can be attributed to faster processors and better communication technologies. A distributed operating system requires distributed algorithms to provide basic operating system functionality like mutual exclusion, deadlock detection, etc. A number of such algorithms have been proposed in the literature. Traditionally, these distributed algorithms have been presented in a theoretical way, with limited attempts to simulate actual working models. This paper discusses our experience in simulating distributed algorithms with the aid of some existing tools, including OPNET and Xplot. We discuss our efforts to define a basic model‐based framework for rapid simulation and visualization, and illustrate how we used this framework to evaluate some classic algorithms. We have also shown how the performance of different algorithms can be compared based on some collected statistics. To keep the focus of this paper on the approach itself, and our experience with tool integration, we only discuss some relatively simple models. Yet, the approach can be applied to more complex algorithm specifications. Copyright © 2001 John Wiley & Sons, Ltd.     

Binary ant colony optimization applied to variable screening in the Mahalanobis–Taguchi System

This work presents the application of the Mahalanobis–Taguchi System (MTS) to a dimensional problem in the automotive industry. The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm. Moreover, a comparison with respect to binary particle swarm optimization algorithm is also presented and a discussion regarding the numerical results is given.     

巴塔哥尼亚Remota酒店的瞭望台

项目名称：巴塔哥尼亚Remota酒店的瞭望台设计者：German del Sol助理建筑师：Jose Luis Ibanez,Francisca Schueler,Carlos Venegas     

Superconducting Quantum Metamaterials from High Pressure Melt Infiltration of Metals into Block Copolymer Double Gyroid Derived Ceramic Templates

Mesoscale order can lead to emergent properties including phononic bandgaps or topologically protected states. Block copolymers offer a route to mesoscale periodic architectures, but their use as structure directing agents for metallic materials has not been fully realized. A versatile approach to mesostructured metals via bulk block copolymer self-assembly derived ceramic templates, is demonstrated. Molten indium is infiltrated into mesoporous, double gyroidal silicon nitride templates under high pressure to yield bulk, 3D periodic nanocomposites as free-standing monoliths which exhibit emergent quantum-scale phenomena. Vortices are artificially introduced when double gyroidal indium metal behaves as a type II superconductor, with evidence of strong pinning centers arrayed on the order of the double gyroid lattice size. Sample behavior is reproducible over months, showing high stability. High pressure infiltration of bulk block copolymer self-assembly based ceramic templates is an enabling tool for studying high-quality metals with previously inaccessible architectures, and paves the way for the emerging field of block-copolymer derived quantum metamaterials.     

Thermo-Adaptive Block Copolymer Structural Color Electronics

Flexible electronics that enable the visualization of thermal energy have significant potential for various applications, such as thermal diagnosis, sensing and imaging, and displays. Thermo-adaptive flexible electronic devices based on thin 1D block copolymer (BCP) photonic crystal (PC) films with self-assembled periodic nanostructures are presented. By employing a thermo-responsive polymer/non-volatile hygroscopic ionic liquid (IL) blend on a BCP film, full visible structural colors (SCs) are developed because of the temperature-dependent expansion and contraction of one BCP domain via IL injection and release, respectively, as a function of temperature. Reversible SC control of the bi-layered BCP/IL polymer blend film from room temperature to 80 °C facilitates the development of various thermo-adaptive SC flexible electronic devices including pixel arrays of reflective-mode displays and capacitive sensing display. A flexible diagnostic thermal patch is demonstrated with the bi-layered BCP/IL polymer blend enabling the visualization of local heat sources from the human body to microelectronic circuits.