Multifidelity Uncertainty Quantification of a Commercial Supersonic Transport

The objective of this work was to develop a multifidelity uncertainty quantification approach for efficient analysis of a commercial supersonic transport. An approach based on non-intrusive polynomial chaos was formulated in which a low-fidelity model could be corrected by any number of high-fidelity models. The formulation and methodology also allows for the addition of uncertainty sources not present in the lower fidelity models. To demonstrate the applicability of the multifidelity polynomial chaos approach, two model problems were explored. The first was supersonic airfoil with three levels of modeling fidelity, each capturing an additional level of physics. The second problem was a commercial supersonic transport. This model had three levels of fidelity that included two different modeling approaches and the addition of physics between the fidelity levels. Both problems illustrate the applicability and significant computational savings of the multifidelity polynomial chaos method

Trim Flight Conditions for a Low-Boom Aircraft Design Under Uncertainty

The purpose of this paper is to investigate the noise generation of a low-boom aircraft design in flight trim conditions under uncertainty. The deflection of control surfaces to maintain a trimmed flight state has the potential to change the perceived loudness at the ground. Furthermore, the uncertainties associated with the control surface deflections can complicate the overall uncertainty quantification. Incorporation of the uncertainties in the prediction of perceived sound levels during the design phase can lead to improved robustness. In this paper, a brief review of low-boom flight trim research is presented. Realistic flight trim conditions requiring control surface deflection are integrated into the current research efforts for uncertainty quantification and vehicle design. In addition, a generalized set of procedures for the characterization of uncertainties in flight trim conditions are introduced. In a case study of the application of these procedures, a 5 decibel average difference in the perceived level of loudness was found between clean (no deflections) and trimmed configurations. Also, uncertainties attributable to control surface deflection were found to account for, on average, over 50% of the total near field uncertainty. Uncertainty discretization methods implemented were able to give more insight into the overall global variances

Alien Registration- West, Thomas H. (Limestone, Aroostook County)

https://digitalmaine.com/alien_docs/35226/thumbnail.jp

Nature, community, & will : a study in literary and social thought

Includes bibliographical references.In three essays, West explores the morality of asceticism, discipline, and dignity within the works of eight social theorists. He attempts to discover a feeling of pride over human affairs that differs from the pride which is condemned by theology.The devices of nature : George Fitzhugh and Thomas Carlyle -- The divided consciousness : Allen Tate, John Crowe Ransom, Paul Elmer More -- Nature and artifice : Hannah Arendt, Theodore Roszak, Paul Goodman.Digitized at the University of Missouri--Columbia MU Libraries Digitization Lab in 2013. Digitized at 600 dpi with Zeutschel, OS 15000 scanner. Access copy, available in MOspace, is 400 dpi, grayscale

Leadership and organisational outcomes in healthcare

This research examined to what extent and how leadership is related to organisational outcomes in healthcare. Based on the Job Demands-Resource model, a set of hypotheses was developed, which predicted that the effect of leadership on healthcare outcomes would be mediated by job design, employee engagement, work pressure, opportunity for involvement, and work-life balance. The research focused on the National Health Service (NHS) in England, and examined the relationships between senior leadership, first line supervisory leadership and outcomes. Three years of data (2008 – 2010) were gathered from four data sources: the NHS National Staff Survey, the NHS Inpatient Survey, the NHS Electronic Record, and the NHS Information Centre. The data were drawn from 390 healthcare organisations and over 285,000 staff annually for each of the three years. Parallel mediation regressions modelled both cross sectional and longitudinal designs. The findings revealed strong relationships between senior leadership and supervisor support respectively and job design, engagement, opportunity for involvement, and work-life balance, while senior leadership was also associated with work pressure. Except for job design, there were significant relationships between the mediating variables and the outcomes of patient satisfaction, employee job satisfaction, absenteeism, and turnover. Relative importance analysis showed that senior leadership accounted for significantly more variance in relationships with outcomes than supervisor support in the majority of models tested. Results are discussed in relation to theoretical and practical contributions. They suggest that leadership plays a significant role in organisational outcomes in healthcare and that previous research may have underestimated how influential senior leaders may be in relation to these outcomes. Moreover, the research suggests that leaders in healthcare may influence outcomes by the way they manage the work pressure, engagement, opportunity for involvement and work-life balance of those they lead

Scalable Bayesian modeling, monitoring and analysis of dynamic network flow data

Traffic flow count data in networks arise in many applications, such as automobile or aviation transportation, certain directed social network contexts, and Internet studies. Using an example of Internet browser traffic flow through site-segments of an international news website, we present Bayesian analyses of two linked classes of models which, in tandem, allow fast, scalable and interpretable Bayesian inference. We first develop flexible state-space models for streaming count data, able to adaptively characterize and quantify network dynamics efficiently in real-time. We then use these models as emulators of more structured, time-varying gravity models that allow formal dissection of network dynamics. This yields interpretable inferences on traffic flow characteristics, and on dynamics in interactions among network nodes. Bayesian monitoring theory defines a strategy for sequential model assessment and adaptation in cases when network flow data deviates from model-based predictions. Exploratory and sequential monitoring analyses of evolving traffic on a network of web site-segments in e-commerce demonstrate the utility of this coupled Bayesian emulation approach to analysis of streaming network count data.Comment: 29 pages, 16 figure