Experimental results on gravity driven fully condensing flows in vertical tubes, their agreement with theory, and their differences with shear driven flows' boundary-condition sensitivities

This doctoral thesis presents the experimental results along with a suitable synthesis with computational/theoretical results towards development of a reliable heat transfer correlation for a specific annular condensation flow regime inside a vertical tube. For fully condensing flows of pure vapor (FC-72) inside a vertical cylindrical tube of 6.6 mm diameter and 0.7 m length, the experimental measurements are shown to yield values of average heat transfer co-efficient, and approximate length of full condensation. The experimental conditions cover: mass flux G over a range of 2.9 kg/m2-s ≤ G ≤ 87.7 kg/m2-s, temperature difference ∆T (saturation temperature at the inlet pressure minus the mean condensing surface temperature) of 5 ºC to 45 ºC, and cases for which the length of full condensation xFC is in the range of 0 < xFC < 0.7 m. The range of flow conditions over which there is good agreement (within 15%) with the theory and its modeling assumptions has been identified. Additionally, the ranges of flow conditions for which there are significant discrepancies (between 15 -30% and greater than 30%) with theory have also been identified. The paper also refers to a brief set of key experimental results with regard to sensitivity of the flow to time-varying or quasi-steady (i.e. steady in the mean) impositions of pressure at both the inlet and the outlet. The experimental results support the updated theoretical/computational results that gravity dominated condensing flows do not allow such elliptic impositions.

Structural capacity of steel tubular cast-in-place piling

Steel tubular cast-in-place pilings are used throughout the country for many different project types. These piles are a closed-end pipe with varying wall thicknesses and outer diameters, that are driven to depth and then the core is filled with concrete. These piles are typically used for smaller bridges, or secondary structures. Mostly the piling is designed based on a resistance based method which is a function of the soil properties of which the pile is driven through, however there is a structural capacity of these members that is considered to be the upper bound on the loading of the member. This structural capacity is given by the AASHTO LRFD (2010), with two methods. These two methods are based on a composite or non-composite section. Many state agencies and corporations use the non-composite equation because it is requires much less computation and is known to be conservative. However with the trends of the time, more and more structural elements are being investigated to determine ways to better understand the mechanics of the members, which could lead to more efficient and safer designs. In this project, a set of these piling are investigated. The way the cross section reacts to several different loading conditions, along with a more detailed observation of the material properties is considered as part of this research. The evaluation consisted of testing stub sections of pile with varying sizes (10-¾”, 12-¾”), wall thicknesses (0.375”, 0.5”), and testing methods (whole compression, composite compression, push through, core sampling). These stub sections were chosen as they would represent a similar bracing length to many different soils. In addition, a finite element model was developed using ANSYS to predict the strains from the testing of the pile cross sections. This model was able to simulate the strains from most of the loading conditions and sizes that were tested. The bond between the steel shell and the concrete core, along with the concrete strength through the depth of the cross section were some of the material properties of these sections that were investigated.

An Experience-Driven Pedagogy for the Instruction of Software Testing in Computer Science

In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.

Data-driven estimates of the number of clusters in multivariate time series

An important problem in unsupervised data clustering is how to determine the number of clusters. Here we investigate how this can be achieved in an automated way by using interrelation matrices of multivariate time series. Two nonparametric and purely data driven algorithms are expounded and compared. The first exploits the eigenvalue spectra of surrogate data, while the second employs the eigenvector components of the interrelation matrix. Compared to the first algorithm, the second approach is computationally faster and not limited to linear interrelation measures.

Prosthetically driven, computer-guided implant planning for the edentulous maxilla: a model study

OBJECTIVES: To analyze computer-assisted diagnostics and virtual implant planning and to evaluate the indication for template-guided flapless surgery and immediate loading in the rehabilitation of the edentulous maxilla. MATERIALS AND METHODS: Forty patients with an edentulous maxilla were selected for this study. The three-dimensional analysis and virtual implant planning was performed with the NobelGuide software program (Nobel Biocare, Göteborg, Sweden). Prior to the computer tomography aesthetics and functional aspects were checked clinically. Either a well-fitting denture or an optimized prosthetic setup was used and then converted to a radiographic template. This allowed for a computer-guided analysis of the jaw together with the prosthesis. Accordingly, the best implant position was determined in relation to the bone structure and prospective tooth position. For all jaws, the hypothetical indication for (1) four implants with a bar overdenture and (2) six implants with a simple fixed prosthesis were planned. The planning of the optimized implant position was then analyzed as follows: the number of implants was calculated that could be placed in sufficient quantity of bone. Additional surgical procedures (guided bone regeneration, sinus floor elevation) that would be necessary due the reduced bone quality and quantity were identified. The indication of template-guided, flapless surgery or an immediate loaded protocol was evaluated. RESULTS: Model (a) - bar overdentures: for 28 patients (70%), all four implants could be placed in sufficient bone (total 112 implants). Thus, a full, flapless procedure could be suggested. For six patients (15%), sufficient bone was not available for any of their planned implants. The remaining six patients had exhibited a combination of sufficient or insufficient bone. Model (b) - simple fixed prosthesis: for 12 patients (30%), all six implants could be placed in sufficient bone (total 72 implants). Thus, a full, flapless procedure could be suggested. For seven patients (17%), sufficient bone was not available for any of their planned implants. The remaining 21 patients had exhibited a combination of sufficient or insufficient bone. DISCUSSION: In the maxilla, advanced atrophy is often observed, and implant placement becomes difficult or impossible. Thus, flapless surgery or an immediate loading protocol can be performed just in a selected number of patients. Nevertheless, the use of a computer program for prosthetically driven implant planning is highly efficient and safe. The three-dimensional view of the maxilla allows the determination of the best implant position, the optimization of the implant axis, and the definition of the best surgical and prosthetic solution for the patient. Thus, a protocol that combines a computer-guided technique with conventional surgical procedures becomes a promising option, which needs to be further evaluated and improved.

Hepatitis C virus drug resistance and immune-driven adaptations: relevance to new antiviral therapy

The efficacy of specifically targeted anti-viral therapy for hepatitis C virus (HCV) (STAT-C), including HCV protease and polymerase inhibitors, is limited by the presence of drug-specific viral resistance mutations within the targeted proteins. Genetic diversity within these viral proteins also evolves under selective pressures provided by host human leukocyte antigen (HLA)-restricted immune responses, which may therefore influence STAT-C treatment response. Here, the prevalence of drug resistance mutations relevant to 27 developmental STAT-C drugs, and the potential for drug and immune selective pressures to intersect at sites along the HCV genome, is explored. HCV nonstructural (NS) 3 protease or NS5B polymerase sequences and HLA assignment were obtained from study populations from Australia, Switzerland, and the United Kingdom. Four hundred five treatment-naïve individuals with chronic HCV infection were considered (259 genotype 1, 146 genotype 3), of which 38.5% were coinfected with human immunodeficiency virus (HIV). We identified preexisting STAT-C drug resistance mutations in sequences from this large cohort. The frequency of the variations varied according to individual STAT-C drug and HCV genotype/subtype. Of individuals infected with subtype 1a, 21.5% exhibited genetic variation at a known drug resistance site. Furthermore, we identified areas in HCV protease and polymerase that are under both potential HLA-driven pressure and therapy selection and identified six HLA-associated polymorphisms (P