Tidal turbine blade load experiments for oscillatory motion

This paper presents blade root bending moment measurements of a horizontal-axis tidal turbine for planar oscillatory motion, conducted in a stationary water towing tank. By comparing the measurements with quasi-steady reconstructions for both single and multiple frequency oscillatory motion, the bending moment was shown to be sensitive to both frequency and amplitude, as well as to the mean tip-speed ratio. The unsteady loads associated with the separation of the flow and dynamic stall are shown to be of considerably greater importance than those which are already present for attached flow, such as added mass and dynamic inflow. A linear model fit to the unsteady bending moment also indicates that the inertia contribution is relatively small. For cases where attached flow exists over the majority of the load cycle, these reconstruction methods are likely to be sufficient to obtain a reasonable prediction of the root out-of-plane bending moment. However, turbines whose blades are likely to operate near stall are likely to require more complex models for accurate load predictions to mitigate the risk of fatigue failure

Performance analysis of wells turbine blades using the entropy generation minimization method

Wells turbine concept depends on utilizing the oscillating air column generated over marine waves to drive a turbine. As a matter of fact, previous researches on the performance analysis of such turbine were based on the first law of thermodynamics only. Nonetheless, the actual useful energy loss cannot be completely justified by the first law because it does not distinguish between the quantity and the quality of energy. Therefore, the present work investigates the second law efficiency and entropy generation characteristics around different blades that are used in Wells turbine under oscillating flow conditions. The work is performed by using time-dependent CFD models of different NACA airfoils under sinusoidal flow boundary conditions. Numerical investigations are carried out for the incompressible viscous flow around the blades to obtain the entropy generation due to viscous dissipation. It is found that the value of second law efficiency of the NACA0015 airfoil blade is higher by approximately 1.5% than the second law efficiency of the NACA0012, NACA0020 and NACA0021 airfoils. Furthermore, it is found that the angle of attack radically affects the second law efficiency and such effect is quantified for NACA0015 for angle of attack ranging from -15° to 25°

Interfacial Effect-Based Quantification of Droplet Isothermal Nucleic Acid Amplification for Bacterial Infection

Bacterial infection is a widespread problem in humans that can potentially lead to hospitalization and morbidity. The largest obstacle for physicians/clinicians is the time delay in accurately identifying infectious bacteria, especially their sub-species, in order to adequately treat and diagnose such infected patients. Loop-mediated amplification (LAMP) is a nucleic acid amplification method that has been widely used in diagnostic applications due to its simplicity of constant temperature, use of up to 4 to 6 primers (rendering it highly specific), and capability of amplifying low copies of target sequences. Use of interfacial effect-based monitoring is expected to dramatically shorten the time-to-results of nucleic acid amplification techniques. In this work, we developed a LAMP-based point-of-care platform for detection of bacterial infection, utilizing smartphone measurement of contact angle from oil-immersed droplet LAMP reactions. Whole bacteria (Escherichia coli O157:H7) were assayed in buffer as well as 5% diluted human whole blood. Monitoring of droplet LAMP reactions was demonstrated in a three-compartment, isothermal proportional-integrated-derived (PID)-controlled chip. Smartphone-captured images of droplet LAMP reactions, and their contact angles, were evaluated. Contact angle decreased substantially upon target amplification in both buffer and whole blood samples. In comparison, notarget control (NTC) droplets remained stable throughout the 30 min isothermal reactions. These results were explained by the pre-adsorption of plasma proteins to an oil-water interface (lowering contact angle), followed by time-dependent amplicon formation and their preferential adsorption to the plasma protein-occupied oil-water interface. Time-to-results was as fast as 5 min, allowing physicians to quickly make their decision for infected patients. The developed assay demonstrated quantification of bacteria concentration, with a limit-of-detection at 10(2) CFU/mu L for buffer samples, and binary target or no-target identification with a limit-of-detection at 10 CFU/mu L for 5% diluted whole blood samples.Cardiovascular Biomedical Engineering Training Grant from U.S. National Institutes of Health [T32HL007955]; W. L. Gore & Associates, Inc.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Unsteady effects during resistance tests on a ship model in a towing tank

It is known that there are oscillations in the wave resistance during the constantvelocity phase of a towing-tank resistance test on a ship model. In this work, the unsteady thin-ship resistance theory has been applied to this case. The results have been compared with experiment data obtained using a towing carriage the velocity history of which can be programmed. It is demonstrated here that generally excellent correlation exists between the theory and the experiments. In particular, one can predict the influence of Froude number, rate of acceleration, and type of smoothing of the acceleration on the characteristics of the oscillations. These characteristics include the amplitude, rate of decay, frequency, and phasing of the oscillations in the curve of wave resistance versus time

Risk factors for the evolutionary emergence of pathogens

Recent outbreaks of novel infectious diseases (e.g. SARS, influenza H1N1) have highlighted the threat of cross-species pathogen transmission. When first introduced to a population, a pathogen is often poorly adapted to its new host and must evolve in order to escape extinction. Theoretical arguments and empirical studies have suggested various factors to explain why some pathogens emerge and others do not, including host contact structure, pathogen adaptive pathways and mutation rates. Using a multi-type branching process, we model the spread of an introduced pathogen evolving through several strains. Extending previous models, we use a network-based approach to separate host contact patterns from pathogen transmissibility. We also allow for arbitrary adaptive pathways. These generalizations lead to novel predictions regarding the impact of hypothesized risk factors. Pathogen fitness depends on the host population in which it circulates, and the ‘riskiest’ contact distribution and adaptive pathway depend on initial transmissibility. Emergence probability is sensitive to mutation probabilities and number of adaptive steps required, with the possibility of large adaptive steps (e.g. simultaneous point mutations or recombination) having a dramatic effect. In most situations, increasing overall mutation probability increases the risk of emergence; however, notable exceptions arise when deleterious mutations are available

Regional fresh snowfall microbiology and chemistry are driven by geography in storm-tracked events, Colorado, USA

Snowfall is a global phenomenon highly integrated with hydrology and ecology. Forays into studying bioaerosols and their dependence on aeolian movement are largely constrained to either precipitation-independent analyses or in silico models. Though snowpack and glacial microbiological studies have been conducted, little is known about the biological component of meteoric snow. Through culture-independent phylogenetic and geochemical analyses, we show that the geographical location at which snow precipitates determines snowfall’s geochemical and microbiological composition. Storm-tracking, furthermore, can be used as a valuable environmental indicator to trace down what factors are influencing bioaerosols. We estimate annual aeolian snowfall deposits of up to ∼10 kg of bacterial/archaeal biomass per hectare along our study area of the eastern Front Range in Colorado. The dominant kinds of microbiota captured in an analysis of seven snow events at two different locations, one urban, one rural, across the winter of 2016/2017 included phyla Proteobacteria, Bacteroidetes, Firmicutes, and Acidobacteria, though a multitude of different kinds of organisms were found in both. Taxonomically, Bacteroidetes were more abundant in Golden (urban plain) snow while Proteobacteria were more common in Sunshine (rural mountain) samples. Chemically, Golden snowfall was positively correlated with some metals and anions. The work also hints at better informing the “everything is everywhere” hypotheses of the microbial world and that atmospheric transport of microbiota is not only common, but is capable of disseminating vast amounts of microbiota of different physiologies and genetics that then affect ecosystems globally. Snowfall, we conclude, is a significant repository of microbiological material with strong implications for both ecosystem genetic flux and general bio-aerosol theory

A glassy contribution to the heat capacity of hcp 4^4He solids

We model the low-temperature specific heat of solid $^4$He in the hexagonal closed packed structure by invoking two-level tunneling states in addition to the usual phonon contribution of a Debye crystal for temperatures far below the Debye temperature, $T < \Theta_D/50$. By introducing a cutoff energy in the two-level tunneling density of states, we can describe the excess specific heat observed in solid hcp $^4$He, as well as the low-temperature linear term in the specific heat. Agreement is found with recent measurements of the temperature behavior of both specific heat and pressure. These results suggest the presence of a very small fraction, at the parts-per-million (ppm) level, of two-level tunneling systems in solid $^4$He, irrespective of the existence of supersolidity.Comment: 11 pages, 4 figure

Modular and predictable assembly of porous organic molecular crystals

Nanoporous molecular frameworks are important in applications such as separation, storage and catalysis. Empirical rules exist for their assembly but it is still challenging to place and segregate functionality in three-dimensional porous solids in a predictable way. Indeed, recent studies of mixed crystalline frameworks suggest a preference for the statistical distribution of functionalities throughout the pores rather than, for example, the functional group localization found in the reactive sites of enzymes. This is a potential limitation for 'one-pot' chemical syntheses of porous frameworks from simple starting materials. An alternative strategy is to prepare porous solids from synthetically preorganized molecular pores. In principle, functional organic pore modules could be covalently prefabricated and then assembled to produce materials with specific properties. However, this vision of mix-and-match assembly is far from being realized, not least because of the challenge in reliably predicting three-dimensional structures for molecular crystals, which lack the strong directional bonding found in networks. Here we show that highly porous crystalline solids can be produced by mixing different organic cage modules that self-assemble by means of chiral recognition. The structures of the resulting materials can be predicted computationally, allowing in silico materials design strategies. The constituent pore modules are synthesized in high yields on gram scales in a one-step reaction. Assembly of the porous co-crystals is as simple as combining the modules in solution and removing the solvent. In some cases, the chiral recognition between modules can be exploited to produce porous organic nanoparticles. We show that the method is valid for four different cage modules and can in principle be generalized in a computationally predictable manner based on a lock-and-key assembly between modules