An Investigation of the Plume Theories of Briggs and Hanna

Many models have been developed for or applied to the prediction of mechanical draft cooling tower plumes. However, due to a serious lack of data up to this date, little has been done to verify the predictive capability of these mathematical models. This thesis attempts to rectify this situation somewhat by undertaking a thorough investigation of the plume theories of G. A. Briggs and S. R. Hanna. A study of their theoretical foundations and development, practical formulations, and ability to predict the height and length of the visible portion of mechanical-draft cooling tower plumes is undertaken. Detailed derivations of their predictive equations are presented along with an analysis of the key assumptions needed for their development. Methods of evaluating parameters and techniques by which the models may be extended are examined. Also, the model of Eagles and Kohlenstein is presented as an example of the application of Briggs\u27 and Hanna\u27s plume theories. Two collections of mechanical-draft cooling tower data (gathered at the Benning Road, Washington, D. C., and Purdue University, Indiana, power plants) are outlined and their utility for model verification discussed. They are used to test the models of Briggs, Hanna, and Eagles-Kohlenstein, with the following results: Briggs\u27 simplest model, though not designed for visible plume predictions, does reasonably well; Hanna\u27s plume predictions are well correlated with the observed plume features, but they tend to consistently over- or under-predict plume height and length; Eagles-Kohlenstein\u27s model, which was calibrated with one of the data sets, tends to give predictions similar to the simpler Hanna model. It is concluded that, although further studies should be made, these models can be expected to give factor of two to three predictions, if properly utilized, of the maximum height and length of mechanical-draft cooling tower plumes which extend a sufficient distance from their sources

Urban Integrated Pest Management Training for Retail Store Employees

A pilot training program in pest management and proper pesticide use was initiated in Illinois for retail and garden center employees by University of Illinois Extension. Primary instructors for the workshop included Integrated Pest Management and Horticulture educators. Because retail stores that sell pesticides are an important source of information for the homeowner, one method of transferring integrated pest management (IPM) strategies to the urban audience is to provide specialized training to retail store employees. In general, the current level of employee pest management training in retail stores that sell pesticides appears limited. This audience, however, seems very receptive to increasing the expertise of their employees, with the primary goal of improved customer service

Clustered engine study

Several topics are presented in viewgraph form which together encompass the preliminary assessment of nuclear thermal rocket engine clustering. The study objectives, schedule, flow, and groundrules are covered. This is followed by the NASA groundrules mission and our interpretation of the associated operational scenario. The NASA reference vehicle is illustrated, then the four propulsion system options are examined. Each propulsion system's preliminary design, fluid systems, operating characteristics, thrust structure, dimensions, and mass properties are detailed as well as the associated key propulsion system/vehicle interfaces. A brief series of systems analysis is also covered including: thrust vector control requirements, engine out possibilities, propulsion system failure modes, surviving system requirements, and technology requirements. An assessment of vehicle/propulsion system impacts due to the lessons learned are presented

Assessing the Medical Emergency Preparedness of Dental Faculty, Residents, and Practicing Periodontists: An Exploratory Study

With the increased number of elderly and medically compromised individuals receiving dental care and the presence of systemic comorbidities and associated treatment modalities in this patient population, it is imperative that dentists be prepared to manage a variety of medical emergencies. The aim of this study was to assess the knowledge of and preparedness to manage common medical emergencies of cohorts of practicing periodontists, specialty residents, and faculty members, both for comparative purposes and as an aid to refining a dental school’s standardized case scenarios. The study, conducted in 2017, was designed for four groups of randomly selected participants with at least 20 in each group; the actual number of voluntary participants was 28 private practice periodontists, 22 residents in specialty programs, 21 specialist faculty members, and 24 general practice faculty members. Participants were asked to evaluate ten clinical emergency cases and identify the diagnosis and indicated intervention for each. Groups were also evaluated for differences among correct responses for each case. Overall, there were no statistically significant differences for number of correct diagnoses or interventions among the four groups. However, several cases had varying degrees of incorrect diagnoses and management across all groups. Participants who had recently graduated or were still in school were able to treat cases appropriately more often than the other participants. Further refinement of cases to assess provider preparedness to correctly diagnose and manage medical emergencies is needed, specifically establishing case-specific features and addressing areas of potential confusion before the cases are used for educational purposes

Dynamic Parametric Sensitivity Optimization Using Simultaneous Discretization in JModelica.org

Dynamic optimization problems involving parametric sensitivities, such as optimal experimental design, are typically solved using shooting-based methods, while leveraging numerical integrators with sensitivity computation capabilities. In this paper we present how simultaneous discretization can be employed to solve these problems, by augmenting the dynamic optimization problems with forward sensitivity equations. We present an implementation of this approach in the open-source, Modelica-based tool JModelica.org, which addresses the need for solving optimal experimental design problems in Modelica tools. The implementation is demonstrated on a fed-batch reactor and a plate-fin heat exchanger