Wireless Applications for Structural Monitoring of Inflatable Habitats

A viewgraph presentation on wireless applications for structural health monitoring of inflatable space structures is shown. The topics include: 1) Background; 2) REquirements; 3) Implementation; and 4) strucutral health monitoring system summary

Discrete Predictive Analysis in Probabilistic Safety Assessment

This paper presents methods for predicting future numbers of component failures for probabilistic safety assessments (PSAs). The research is motivated and illustrated by discrete failure data from the nuclear industry, including failure counts for emergency diesel generators, pumps, and motor operated valves. Failure counts are modeled with Poisson and binomial distributions. Multiple-failure environments create extra problems for predictive inference, and are a primary focus of this paper. Common cause failures (CCFs), in particular, refer to the simultaneous failure of system components due to an external event. CCF prediction is investigated, and approximate inference methods are derived for various CCF models

Common Cause Failure Prediction Using Data Mapping

To estimate power plant reliability, a probabilistic safety assessment might combine failure data from various sites. Because dependent failures are a critical concern in the nuclear industry, combining failure data from component groups of different sizes is a challenging problem. One procedure, called data mapping, translates failure data across component group sizes. This includes common cause failures, which are simultaneous failure events of two or more components in a group. In this paper, we present methods for predicting future plant reliability using mapped common cause failure data. The prediction technique is motivated by discrete failure data from emergency diesel generators at U.S. plants. The underlying failure distributions are based on homogeneous Poisson processes. Both Bayesian and frequentist prediction methods are presented, and if non-informative prior distributions are applied, the upper prediction bounds for the generators are the same

Ariel - Volume 3 Number 8

Editors Richard J. Bonanno Robin A. Edwards Associate Editors Steven Ager Tom Williams Lay-out Editor Eugenia Miller Contributing Editors Paul Bialas Robert Breckenridge David Jacoby Mike LeWitt Terry Burt Michael Leo Editors Emeritus Delvyn C. Case, Jr. Paul M. Fernhof

Political Skill for Sport Professionals: Theory, Research, and Career Success Implications

Motivated by an increasing interpersonal aspect to the profession of sport coaching, the importance of being socially effective as a coach has multiplied in significance. This review specifically considers the social effectiveness construct, political skill, as a crucial aspect to career success through the perspective of a sport coaching lens. Political skill refers to the ability to effectually understand others at work, and to then use that information to influence others to behave in ways that enhance one’s personal and/or organizational objective. Political skill is a means through which sport coaches may be able to build and maintain important and influential relationships with key stakeholders (e.g., athletic directors), thus improving the possibility of a successful coaching career. This article presents a review of theoretical foundations for the association between political skill and career success as well as practical applications (e.g., active listening, empowerment, volunteerism) for sport coaches when managing important stakeholder relationships. Research suggestions for the continued advancement of political skill research are also provided

Search for Inclusive b → sl^+l^-

We have searched for the effective flavor changing neutral-current decays b→sl^+l^- using an inclusive method. We set upper limits on the branching ratios B(b→se^+e^-)<5.7×10^(-5), B(b→sμ^+μ^-)<5.8×10^(-5), and B(b→se^±μ^∓)<2.2×10^(-5) [at 90% confidence level (C.L.)]. Combing the dielectron and dimuon decay modes we find B(b→sl^+l^-)<4.2×10^(-5) (at 90% C.L.)