Effect of high order interpolation in the stability and efficiency of the time-integration process in vorticity-velocity CFD algorithms

The numerical solution of the incompressible Navier-Stokes Equations offers an effective alternative to the experimental analysis of Fluid-Structure interaction i.e. dynamical coupling between a fluid and a solid which otherwise is very complex, time consuming and very expensive. To have a method which can accurately model these types of mechanical systems by numerical solutions becomes a great option, since these advantages are even more obvious when considering huge structures like bridges, high rise buildings, or even wind turbine blades with diameters as large as 200 meters. The modeling of such processes, however, involves complex multiphysics problems along with complex geometries. This thesis focuses on a novel vorticity-velocity formulation called the KLE to solve the incompressible Navier-stokes equations for such FSI problems. This scheme allows for the implementation of robust adaptive ODE time integration schemes and thus allows us to tackle the various multiphysics problems as separate modules. The current algorithm for KLE employs a structured or unstructured mesh for spatial discretization and it allows the use of a self-adaptive or fixed time step ODE solver while dealing with unsteady problems. This research deals with the analysis of the effects of the Courant-Friedrichs-Lewy (CFL) condition for KLE when applied to unsteady Stoke’s problem. The objective is to conduct a numerical analysis for stability and, hence, for convergence. Our results confirmthat the time step ∆t is constrained by the CFL-like condition ∆t ≤ const. hα, where h denotes the variable that represents spatial discretization.

Dynamic merge of discrete goods flow – Impact on throughput and efficiency

Continuous conveyors with a dynamic merge were developed with adaptable control equipment to differentiate these merges from competing Stop-and-Go merges. With a dynamic merge, the partial flows are manipulated by influencing speeds so that transport units need not stop for the merge. This leads to a more uniform flow of materials, which is qualitatively observable and verifiable in long-term measurements. And although this type of merge is visually mesmerizing, does it lead to advantages from the view of material flow technology? Our study with real data indicates that a dynamic merge shows a 24% increase in performance, but only for symmetric or nearly symmetric flows. This performance advantage decreases as the flows become less symmetric, approaching the throughput of traditional Stop-and-Go merges. And with a cost premium for a continuous merge of approximately 10% due to the additional technical components (belt conveyor, adjustable drive engines, software, etc.), this restricts their economical use.

The physician's perception of medical error and its application to the development of an educational training tool.

It is becoming clear that if we are to impact the rate of medical errors it will have to be done at the practicing physician level. The purpose of this project was to survey the attitude of physicians in Alabama concerning their perception of medical error, and to obtain their thoughts and desires for medical education in the area of medical errors. The information will be used in the development of a physician education program.

Distribution and Efficiency of Bacteriolysis in the Gut of Arenicola Marina and Three Additional Deposit Feeders

A simple technique was developed to measure the bacteriolytic activities of the digestive fluids of the deposit-feeding polychaete Arenicola marina. Lysis of a cultured environmental isolate, incubated with extracts of gut luminal contents, was monitored spectrophotometrically. Concurrent direct counts were used to verify cell lysis. The ability of extracts from 8 longitudinal sections of the gut to lyse the bacterium was monitored. The digestive ceca, anterior stomach, and posterior stomach regions exhibited high lytic activities, whereas bacteriolytic activities in all other regions of the gut were negligible. Similarly, extracts of surface sediments and fecal castings showed negligible lytic capabilities. The sharply limited distribution of lytic activity implicates the ceca as the source of bacteriolytic agent and suggests a true plug-flow system, with little axial mixing. Questions regarding the fate of lytic agents, which disappear abruptly posterior to the stomach, remain unanswered. Localization of lysis in the gut coupled with estimates of gut residence time permit the calculation that ingested bacteria are exposed to strong lytic activity for approximately 20 min. Incubation of in situ sediment samples with gut fluids corroborates the distributional findings of the in vitro work although the efficiency of lysis is much reduced, possibly due to exopolymer capsules and slimes of natural sedimentary bacteria. Cross-phyletic comparisons of bacteriolytic activities reveal both qualitative and quantitative differences. Much less demarcation of lytic activity is observed in the guts of a holothuroid (Caudina arenata) and a hemichordate (Stereobalanus canadensis), with a pattern more similar to that of A. marina observed in another polychaete, Amphitrite johnstoni. Quantitatively, the polychaetes showed higher levels of activity with rates in A. marina exceeding those of the hemichordate and holothuroid by more than 10-fold.

Improving Surveying Accuracy and Efficiency in Connecticut: An Accuracy Assessment of GEOID03 and GEOID09

Comparing published NAVD 88 Helmert orthometric heights of First-Order bench marks against GPS-determined orthometric heights showed that GEOID03 and GEOID09 perform at their reported accuracy in Connecticut. GPS-determined orthometric heights were determined by subtracting geoid undulations from ellipsoid heights obtained from a network least-squares adjustment of GPS occupations in 2007 and 2008. A total of 73 markers were occupied in these stability classes: 25 class A, 11 class B, 12 class C, 2 class D bench marks, and 23 temporary marks with transferred elevations. Adjusted ellipsoid heights were compared against OPUS as a check. We found that: the GPS-determined orthometric heights of stability class A markers and the transfers are statistically lower than their published values but just barely; stability class B, C and D markers are also statistically lower in a manner consistent with subsidence or settling; GEOID09 does not exhibit a statistically significant residual trend across Connecticut; and GEOID09 out-performed GEOID03. A "correction surface" is not recommended in spite of the geoid models being statistically different than the NAVD 88 heights because the uncertainties involved dominate the discrepancies. Instead, it is recommended that the vertical control network be re-observed.

Productivity Growth and Efficiency in Indian Banking: A Comparison of Public, Private, and Foreign Banks

India's public sector banks (PSBs) are compared unfavorably with their private sector counterparts, domestic and foreign. This comparison rests, for the most part, on financial measures of performance, and such a comparison provides much of the rationale for privatization of PSBs.In this paper, we attempt a comparison between PSBs and their private sector counterparts based on measures of productivity that use quantities of outputs and inputs. We employ two measures of productivity: Tornqvist and Malmquist total factor productivity growth. We attempt these comparisons over the period 1992-2000, comparing PSBs with both domestic private and foreign banks. Out of a total of four comparisons we have made, there are no differences in three cases, PSBs do better in two, and foreign banks in one. To put it differently, PSBs are seen to be at a disadvantage in only one out of six comparisons. It is difficult, therefore, to sustain the proposition that efficiency and productivity have been lower in public sector banks relative to their peers in the private sector.

Liberalization, Ownership, and Efficiency in Indian Banking: A Nonparametric Approach

This paper empirically estimates and analyzes various efficiency scores of Indian banks during 1997-2003 using data envelopment analysis (DEA). During the 1990s India's financial sector underwent a process of gradual liberalization aimed at strengthening and improving the operational efficiency of the financial system. It is observed, none the less, that Indian banks are still not much differentiated in terms of input or output oriented technical efficiency and cost efficiency. However, they differ sharply in respect of revenue and profit efficiencies. The results provide interesting insight into the empirical correlates of efficiency scores of Indian banks. Bank size, ownership, and the fact of its being listed on the stock exchange are some of the factors that are found to have positive impact on the average profit efficiency and to some extent revenue efficiency scores are. Finally, we observe that the median efficiency scores of Indian banks in general and of bigger banks in particular have improved considerably during the post-reform period.

Reputation and Efficiency: A Nonparametric Assessment of America's Top-Rated MBA Programs

Widely publicized reports of fresh MBAs getting multiple job offers with six-figure annual salaries leave a long-lasting general impression about the high quality of selected business schools. While such spectacular achievement in job placement rightly deserves recognition, one should not lose sight of the resources expended in order to accomplish this result. In this study, we employ a measure of Pareto-Koopmans global efficiency to evaluate the efficiency levels of the MBA programs in Business Week's top-rated list. We compute input- and output-oriented radial and non-radial efficiency measures for comparison. Among three tier groups, the schools from a higher tier group on average are more efficient than those from lower tiers, although variations in efficiency levels do occur within the same tier, which exist over different measures of efficiency.

Responses of three tropical seagrass species to CO2 enrichment

Increased atmospheric carbon dioxide leads to ocean acidification and carbon dioxide (CO2) enrichment of seawater. Given the important ecological functions of seagrass meadows, understanding their responses to CO2 will be critical for the management of coastal ecosystems. This study examined the physiological responses of three tropical seagrasses to a range of seawater pCO2 levels in a laboratory. Cymodocea serrulata, Halodule uninervis and Thalassia hemprichii were exposed to four different pCO2 treatments (442-1204 µatm) for 2 weeks, approximating the range of end-of-century emission scenarios. Photosynthetic responses were quantified using optode-based oxygen flux measurements. Across all three species, net productivity and energetic surplus (PG:R) significantly increased with a rise in pCO2 (linear models, P < 0.05). Photosynthesis-irradiance curve-derived photosynthetic parameters-maximum photosynthetic rates (P max) and efficiency (alpha) also increased as pCO2 increased (linear models, P < 0.05). The response for productivity measures was similar across species, i.e. similar slopes in linear models. A decrease in compensation light requirement (Ec) with increasing pCO2 was evident in C. serrulata and H. uninervis, but not in T. hemprichii. Despite higher productivity with pCO2 enrichment, leaf growth rates in C. serrulata did not increase, while those in H. uninervis and T. hemprichii significantly increased with increasing pCO2 levels. While seagrasses can be carbon-limited and productivity can respond positively to CO2 enrichment, varying carbon allocation strategies amongst species suggest differential growth response between species. Thus, future increase in seawater CO2 concentration may lead to an overall increase in seagrass biomass and productivity, as well as community changes in seagrass meadows.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Relationship among Corneal Biomechanics, Refractive Error, and Axial Length

Purpose: To evaluate the relationship between different ocular and corneal biomechanical parameters in emmetropic and ametropic healthy white children. Methods: This study included 293 eyes of 293 healthy Spanish children (135 boys and 158 girls), ranging in age from 6 to 17 years. Subjects were divided according to the refractive error: control (emmetropia, 99 children), myopia (100 children), and hyperopia (94 children) groups. In all cases, corneal hysteresis (CH) and corneal resistance factor (CRF) were evaluated with the Ocular Response Analyzer system. Axial length (AL) and mean corneal power were also measured by partial coherence interferometry (IOLMaster), and central corneal thickness (CCT) and anterior chamber depth were measured by anterior segment optical coherence tomography (Visante). Results: Mean (±SD) CH and CRF were 12.12 (±1.71) and 12.30 (±1.89) mm Hg, respectively. Mean (±SD) CCT was 542.68 (±37.20) μm and mean (±SD) spherical equivalent was +0.14 (±3.41) diopters. A positive correlation was found between CH and CRF (p < 0.001), and both correlated as well with CCT (p < 0.0001). Corneal resistance factor was found to decrease with increasing age (p = 0.01). Lower levels of CH were associated with longer AL and more myopia (p < 0.001 and p = 0.001, respectively). Higher values of CH were associated with increasing hyperopia. Significant differences in CH were found between emmetropic and myopic groups (p < 0.001) and between myopic and hyperopic groups (p = 0.011). There were also significant differences in CRF between emmetropic and myopic groups (p = 0.02). Multiple linear regression analysis showed that lower CH and CRF significantly associated with thinner CCT, longer AL, and flatter corneal curvature. Conclusions: The Ocular Response Analyzer corneal biomechanical properties seem to be compromised in myopia from an early age, especially in high myopia.