Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring

As the nuclear power plants within the UK age, there is an increased requirement for condition monitoring to ensure that the plants are still be able to operate safely. This paper describes the novel application of Intelligent Systems (IS) techniques to provide decision support to the condition monitoring of Nuclear Power Plant (NPP) reactor cores within the UK. The resulting system, BETA (British Energy Trace Analysis) is deployed within the UK’s nuclear operator and provides automated decision support for the analysis of refuelling data, a lead indicator of the health of AGR (Advanced Gas-cooled Reactor) nuclear power plant cores. The key contribution of this work is the improvement of existing manual, labour-intensive analysis through the application of IS techniques to provide decision support to NPP reactor core condition monitoring. This enables an existing source of condition monitoring data to be analysed in a rapid and repeatable manner, providing additional information relating to core health on a more regular basis than routine inspection data allows. The application of IS techniques addresses two issues with the existing manual interpretation of the data, namely the limited availability of expertise and the variability of assessment between different experts. Decision support is provided by four applications of intelligent systems techniques. Two instances of a rule-based expert system are deployed, the first to automatically identify key features within the refuelling data and the second to classify specific types of anomaly. Clustering techniques are applied to support the definition of benchmark behaviour, which is used to detect the presence of anomalies within the refuelling data. Finally data mining techniques are used to track the evolution of the normal benchmark behaviour over time. This results in a system that not only provides support for analysing new refuelling events but also provides the platform to allow future events to be analysed. The BETA system has been deployed within the nuclear operator in the UK and is used at both the engineering offices and on station to support the analysis of refuelling events from two AGR stations, with a view to expanding it to the rest of the fleet in the near future.     

Martensitic transformations in Ti-Mo alloys

A detailed investigation has been made of the structure of alloys of the Ti-Mo system containing up to 10wt% Mo, water-quenched from the-phase region. With increase in molybdenum content, the martensite structure changes from hexagonal () to orthorhombic () at 4 wt% Mo, and at 10 wt% Mo, the structure is completely retained . For alloy compositions <4 wt% Mo, there is a diffusional component in the transformation of the -phase at the quench rates employed. There is a transition, with increase in molybdenum content, in morphology (from massive to acicular) and in substructure (from dislocations to twins). However, the transitions in crystallography, morphology and sub-structure are not directly related to one another except for an abrupt loss of dislocation substructure at the/ transition. The to crystallographic transition has the characteristics of a second order transformation, and evidence has been obtained of the existence of a spinodal within the metastable orthorhombic system. The orthorhombic martensites of Ti-6 and 8 wt% Mo decompose during quenching producing a fine modulated structure within the martensite plates, consistent with a proposed spinodal mode of decomposition.     

Inhibition of neutral cholesteryl ester hydrolase by the glycolytic enzyme enolase. Is this a secondary function of enolase?

There is an accumulation of the glycolytic enzyme enolase and of cholesteryl esters in macrophages that have been converted into “foam” cells. In this study, we questioned whether enolase could be involved in this accumulation of cholesteryl esters by inhibiting the activity of neutral cholesteryl ester hydrolases. Enolase from both yeast and rabbit muscle were incubated with three different cholesteryl ester hydrolases and were shown to inhibit the hydrolysis of cholesteryl esters. Inhibition was dependent on the concentration of enolase and appeared to occur through binding of the enolase to the cholesteryl ester. Nevertheless, the yeast and rabbit muscle enolases differed in their efficiency of inhibition and in their mechanism of action. Purification of commercial enolase preparations by gel-filtration yielded single proteins with the same inhibitory activities as the originals, indicating that the inhibition was not due to the presence of an impurity. Partially purified αα-and γγ-isoforms of the enzyme from rat brain also appear to have inhibitory effects on cholesteryl ester hydrolysis. Negative control of the hydrolytic phase of the cholesterol/cholesteryl ester cycle may be a secondary function of enolases which correlates with the accumulation of cholesteryl esters in a number of neuro-degenerative and demyelinating diseases.     

Outpatient chemotherapy of advanced breast cancer in a community setting: a five-drug regimen

Forty-two (37 evaluable) unselected women with advanced breast carcinoma were treated with a modified "Cooper regimen" in a community setting. After 12 weeks of induction therapy, the patients were evaluated for response and toxicity. The 74% overall response rate (78% in the evaluable group) compares favorably with that of other series. The median duration of remission was 13.7 months. The median survival was 17 months for the evaluable patients and 14 months for the entire group. Twenty-two percent of the patients required hospitalization during the induction phase, and 35% were treated exclusively as outpatients during all phases of therapy. There was only one drug-related death. It is concluded that a complex chemotherapeutic regimen can be managed adequately by physicians experienced in chemotherapy in a community setting with results comparable to those from cancer centers.     

Interval Set Clustering of Web Users with Rough K-Means

Data collection and analysis in web mining faces certain unique challenges. Due to a variety of reasons inherent in web browsing and web logging, the likelihood of bad or incomplete data is higher than conventional applications. The analytical techniques in web mining need to accommodate such data. Fuzzy and rough sets provide the ability to deal with incomplete and approximate information. Fuzzy set theory has been shown to be useful in three important aspects of web and data mining, namely clustering, association, and sequential analysis. There is increasing interest in research on clustering based on rough set theory. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users. Researchers have pointed out some important differences between clustering in conventional applications and clustering in web mining. For example, the clusters and associations in web mining do not necessarily have crisp boundaries. As a result, researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have used genetic algorithms based on rough set theory for clustering. However, the genetic algorithms based clustering may not be able to handle the large amount of data typical in a web mining application. This paper proposes a variation of the K-means clustering algorithm based on properties of rough sets. The proposed algorithm represents clusters as interval or rough sets. The paper also describes the design of an experiment including data collection and the clustering process. The experiment is used to create interval set representations of clusters of web visitors.     

The development of a visual interactive simulation of packaging flow lines

The design and implementation of new manufacturing processes or the reconfiguration/reuse of existing machines is a multidisciplinary activity. The introduction and modification of processes requires input from a variety of people with disparate skills, backgrounds, responsibilities and requirements. In addition, the trend towards globalization of businesses has resulted in collaborative projects involving domain experts who speak different languages and originate from different cultural backgrounds. Clearly effective communication via common representations is essential in such projects. A visual interactive simulation that can easily be modified (i.e. reconfigured, extended or reused) is an effective method of providing a common representation for personnel involved in the design and implementation of manufacturing processes. In this paper the development of a visual interactive simulation is discussed with regards to the problem of investigating the operation and interoperation of a number of workstations that comprise a beverage can production flow line. A consortium of European partners was involved in the project to determine the opportunities to increase the efficiency of the current operation with respect to material usage and machine operational efficiency.     

Improved phase stability and electrochemical performance of (Y,In,Ca)BaCo3ZnO7+δ cathodes for intermediate temperature solid oxide fuel cells

With an aim to combine the performance-enhancing properties of Ca with the stability-promoting properties of In in the swedenborgite YBaCo₄O_7+δ-based cathodes for solid oxide fuel cells (SOFC), cation-substituted Y_1−x−yIn_xCa_yBaCo₃ZnO_7+δ (0.2 ≤ (x + y) ≤ 0.5) oxides have been explored. All samples presented in this work are stable in air after 120 h exposure to 600, 700, and 800 °C. Increasing In content shows a negligible impact on polarization resistances (R_p), but causes an increase in the activation energies (E_a) of (Y,In,Ca)BaCo₃ZnO_7+δ + Gd_0.2Ce_0.8O_1.9 (GDC) composite cathodes on 8 mol% yttria-stabilized zirconia (8YSZ) electrolyte supported symmetric cells. Increasing Ca content shows a decrease in R_p and an increase in E_a on similar electrochemical cells. All (Y,In,Ca)BaCo₃ZnO_7+δ samples investigated here show superior performance compared to the unsubstituted YBaCo₃ZnO_7+δ + GDC cathode in the range of 400–800 °C. Especially, the Y_0.5In_0.1Ca_0.4BaCo₃ZnO_7+δ + GDC composite cathode exhibits good performance on GDC electrolytes in the range of 400–600 °C. With superior phase stability and electrochemical performance, the (Y,In,Ca)BaCo₃ZnO_7+δ series of oxides are attractive cathode candidates for intermediate temperature SOFCs.     

Electrochemical detection of 14 common munitions constituents

Electrochemical detections of 14 munitions constituents (MCs) listed on the Environmental Protection Agency hazardous waste list were examined using square wave voltammetry. Of the MCs that showed peak resolution in the scanned range, the reduction potential, limit of detection and limit of quantitation are reported here. The MCs tested are in three groups: nitrobenzenes, nitrotoluenes, and other nitro-aromatics: tetryl, HMX, and RDX. There was a correlation between peak resolution and the number of nitro groups for the nitrobenzenes and nitrotoluenes. The nitro group distance from the methyl for the nitrotoluenes with two nitro groups showed some correlation to the ability to detect as well. Some mixture experiments were conducted in which MCs with three and two nitro groups were detected simultaneously. While tetryl readily displayed two peaks, RDX and HMX did not show such clear peak resolution.     

Evaluating model fit for growth curve models: Integration of fit indices from SEM and MLM frameworks.

Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation modeling (SEM) perspective has focused only on the covariance structure, but growth curve models have four potential sources of misspecification: within-individual covariance matrix, between-individuals covariance matrix, marginal mean structure, and conditional mean structure. (c) Growth curve models can be estimated in both the SEM and multilevel modeling (MLM) frameworks; these have different emphases for the evaluation of model fit. In this article, the authors discuss the challenges presented by these 3 issues in the calculation and interpretation of SEM- and MLM-based fit indices for growth curve models and conclude by identifying some lines for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)