1,531 research outputs found
An analysis of a swimmer’s passive wave resistance using experimental data and CFD simulations
The passive resistance of a swimmer on the free surface has previously been researched experimentally. The contribution of wave resistance to total drag for a swimmer with a velocity around 2.0 m.s-1 was found to vary from 5% for Vorontsov and Rumyantsev (2000), to 21 % for Toussaint et al. (2002) and up to 60% according to Vennell et al. (2006). The exact resistance breakdown of a swimmer remains unknown due to difficulties in the direct measurement of wave resistance. As noted by Sato and Hino (2010), this lack of experimental data makes it difficult to validate numerical simulations of swimmers on the free surface.This study is therefore aimed at presenting direct measurements of a swimmer’s total drag and wave resistance, along with the longitudinal wave cuts which may be used to validate numerical simulations. In this paper, experimental data of a swimmer’s resistance are presented at two different velocities (case 1 = 1.7 m.s-1 and case 2 = 2.1 m.s-1). Total drag was measured using force block dynamometers mounted on a custom-built tow rig (Webb et al., 2011). Moreover, a longitudinal wave cut method was used to directly evaluate wave resistance (Eggers, 1955).The two conditions tested were simulated using the open-source Computational Fluid Dynamics (CFD) code OpenFOAM (OpenFOAM® (2013)). The body geometry is a generic human form, morphed into the correct attitude and depth using the above- and under-water video footage recorded during the experiment. 3D Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations were performed using the Volume of Fluid (VOF) method to solve the air-water interface. A similar numerical technique was used by Banks (2013a) to assess the passive resistance of a swimmer. Two cases were simulated and the error in total drag compared to the experimental data was found to be 1 % and 22 % respectively. In this paper, the resistance components over a swimmer’s typical range of speeds are investigated and compared with the experimental dat
The Influence of Didymosphenia geminate on Fisheries Resources in Rapid Creek, South Dakota – An Eight Year History
The aquatic nuisance diatom Didymosphenia geminata was established in Rapid Creek in the Black Hills of South Dakota in 2002. Shortly thereafter, large declines (\u3e50%) of the naturalized brown trout Salmo trutta population were observed. We evaluated the influence of water resources and D. geminata on (1) declines in brown trout biomass, (2) changes in food resources, and (3) diet of brown trout in Black Hills streams. Drought conditions were largely responsible for trout declines in Black Hills streams. However, comparison of brown trout sizestructure between the pre-D. geminata and post-D. geminata periods revealed that juvenile brown trout abundance increased while adult abundance decreased in Rapid Creek. Changes in food resources in D. geminata-impacted areas were thought to favor juvenile brown trout and negatively impact adults. In the presence of D. geminata, macroinvertebrate abundance was composed of fewer, larger taxa and higher numbers of smaller taxa (i.e., chironomids). Brown trout in Rapid Creek consumed fewer ephemeropterans and a high amount of dipterans. Nonetheless, diet analysis showed that brown trout in Rapid Creek consumed as much or more prey than trout from two other streams unaffected by D. geminata. Moreover, relative weight of brown trout from Rapid Creek was high (\u3e100), implying that food availability was not limiting. These findings imply that D. geminata did not negatively impact feeding and condition of brown trout in Rapid Creek, although mechanisms affecting size-structure in Rapid Creek remain unknown
Longitudinal vehicle dynamics : a comparison of physical and data-driven models under large-scale real-world driving conditions
Mathematical models of vehicle dynamics will form essential components of future autonomous vehicles. They may be used within inverse or forward control loops, or within predictive learning systems. Often, nonlinear physical models are used in this context, which, though conceptually simple (especially for decoupled, longitudinal dynamics), may be computationally costly to parameterise and also inaccurate if they omit vehicle-specific dynamics. In this study we sought to determine the relative merits of a commonly used nonlinear physical model of vehicle dynamics versus data-driven models in large-scale real-world driving conditions. To this end, we compared the performance of a standard nonlinear physical model with a linear state-space model and a neural network model. The large-scale experimental data was obtained from two vehicles; a Lancia Delta car and a Jeep Renegade sport utility vehicle. The vehicles were driven on regular, public roads, during normal human driving, across a range of road gradients. Both data-driven models outperformed the physical model. The neural network model performed best for both vehicles; the state-space model performed almost as well as the neural network for the Lancia Delta, but fell short for the Jeep Renegade whose dynamics were more strongly nonlinear. Our results suggest that the linear data-driven model gives a good trade-off in accuracy and simplicity, whilst the neural network model is most accurate and is extensible to more nonlinear operating conditions, and finally that the widely used physical model may not be the best choice for control design
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Essential Oils in Holy Basil (Ocimum tenuiflorum L.) as Influenced by Planting Dates and Harvest Times in North Alabama
Commonly known as Holy basil, Ocimum tenuiflorum (Lamiaceae), is a popular medicinal herb used for treating ailments ranging from colds to chronic diseases, such as cancers and diabetes. While Holy basil is well known in India and Southeast Asia, the plant is less known in western countries where a lack of information on cultural practices exists. In the current study, a field trial was established to determine the optimum planting date, the changes in essential oil content, and composition of O. tenuiflorum in Alabama. A total of three Holy basil accessions, PI 652056, PI 652057, and PI 288779, were planted three times at monthly intervals, beginning in April 2007. At 30, 60, and 90 days after transplanting (DATP), the aerial parts of two plants from each plot were harvested and used to determine essential oil content and composition of stems and leaves using gas chromatography-mass spectrometry. Sensory properties, yield, and composition of essential oils were affected by planting dates and harvest times. Harvesting during summer months yielded the highest amounts of oil for all three accessions. The chemotypes were identified as one high in eugenol (PI 652056), one high in β-caryophyllene (PI 652057), and a third dominated by eugenol (PI 288779) at the end of the growing period. In accession PI 652056, the level of eugenol increased with a delay in harvest time. For accession PI 652057, the level of β-caryophyllene was high at the 30-day harvest, but decreased significantly by the time of the 60-day harvest when eugenol became the dominant essential oil constituent. For the third accession (PI 288779), the essential oil was dominated by eugenol, reaching over 50% eugenol at 60 days DATP in the June planting, but the percentage of eugenol decreased towards the end of the growing season with a significant increase in (trans)-β-guaiene by 90-DATP. Of the 26 essential oil components identified in the accessions, eugenol, β-caryophyllene, E-methyl cinnamate and (trans)-β-guaiene were the most abundant constituents. The level of these essential oil constituents varied significantly in all accessions at all harvest stages. For O. tenuiflorum seedlings, the date of seeding, transplanting, and harvest DATP (plant maturity) significantly impacted total essential oil content and composition, although the level of changes within the various constituents were dependent upon the accession
Linear system identification of longitudinal vehicle dynamics versus nonlinear physical modelling
Mathematical modelling of vehicle dynamics is essential for the development of autonomous cars. Many of the vehicle models that are used for control design in cars are based on nonlinear physical models. However, it is not clear, especially for the case of longitudinal dynamics, whether such nonlinear models are necessary or simpler models can be used. In this paper, we identify a linear data-driven model of longitudinal vehicle dynamics and compare it to a nonlinear physically derived model. The linear model was identified in continuous-time state-space form using a prediction error method. The identification data were obtained from a Lancia Delta car, over 53 km of normal driving on public roads. The selected linear model was first order with requested torque, brake and road gradient as inputs and car velocity as output. The key results were that 1. the linear model was accurate, with a variance accounted for (VAF) metric of VAF=96.5%, and 2. the identified linear model was also superior in accuracy to the nonlinear physical model, VAF=77.4%. The implication of these results, therefore, is that for longitudinal dynamics, in normal driving conditions, a first order linear model is sufficient to describe the vehicle dynamics. This is advantageous for control design, state estimation and real-time implementation, e.g. in predictive control
A comparison of limited-stretch models of rubber elasticity
In this paper we describe various limited-stretch models of non-linear rubber elasticity, each dependent on only the first invariant of the left Cauchy-Green strain tensor and having only two independent material constants. The models are described as limited-stretch, or restricted elastic, because the strain energy and stress response become infinite at a finite value of the first invariant. These models describe well the limited stretch of the polymer chains of which rubber is composed. We discuss Gent's model which is the simplest limited-stretch model and agrees well with experiment. Various statistical models are then described: the one-chain, three-chain, four-chain and Arruda-Boyce eight-chain models, all of which involve the inverse Langevin function. A numerical comparison between the three-chain and eight-chain models is provided. Next, we compare various models which involve approximations to the inverse Langevin function with the exact inverse Langevin function of the eight-chain model. A new approximate model is proposed that is as simple as Cohen's original model but significantly more accurate. We show that effectively the eight-chain model may be regarded as a linear combination of the neo-Hookean and Gent models. Treloar's model is shown to have about half the percentage error of our new model but it is much more complicated. For completeness a modified Treloar model is introduced but this is only slightly more accurate than Treloar's original model. For the deformations of uniaxial tension, biaxial tension, pure shear and simple shear we compare the accuracy of these models, and that of Puso, with the eight-chain model by means of graphs and a table. Our approximations compare extremely well with models frequently used and described in the literature, having the smallest mean percentage error over most of the range of the argument
An initial assessment of the environmental impact of grocery products
This report presents a series of analyses with the common purpose of establishing which grocery products are likely to contribute most to the environmental impacts (carbon footprint or embodied carbon, embodied energy, water, materials use and waste) associated with UK household consumption. Understanding and prioritising these has enabled reduction actions, interventions and further research to be directed more effectively at those products with the greatest potential to influence overall consumption impacts.The report includes a systematic review of 1,900 grocery carbon footprint data points for 191 products; believed to be the largest assessment of its kind at the time of publication
Induction of T Lymphocytes Specific for Bovine Viral Diarrhea Virus in Calves with Maternal Antibody
Passive antibody to bovine viral diarrhea virus (BVDV) acquired through colostrum intake may interfere with the development of a protective immune response by calves to this virus. The objective of this study was to determine if calves, with a high level of maternal antibody to bovine viral diarrhea virus (BVDV), develop CD4+, CD8+, or γδ T lymphocyte responses to BVDV in the absence of a measurable humoral immune response. Colostrum or milk replacer fed calves were challenged with virulent BVDV at 2-5 weeks of age and/or after maternal antibody had waned. Calves exposed to BVDV while passive antibody levels were high did not mount a measurable humoral immune response to BVDV. However, compared to nonexposed animals, these animals had CD4+, CD8+, and γδ T lymphocytes that were activated by BVDV after exposure to in vitro BVDV. The production of IFNγ by lymphocytes after in vitro BVDV exposure was also much greater in lymphocytes from calves exposed to BVDV in the presence of maternal antibody compared to the nonexposed calves. These data indicate that calves exposed to BVDV while maternal antibody levels are high can develop antigen specific CD4+, CD8+, and γδ T lymphocytes in the absence of an active antibody response. A manuscript presented separately demonstrates that the calves with T lymphocytes specific for BVDV in this study were also protected from virulent BVDV genotype 2 challenge after maternal antibody became undetectable
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A Comparison between Vector Algorithm and CRSS Algorithms for Indoor Localization using Received Signal Strength
noA comparison is presented between two indoor localization algorithms using received signal strength, namely the vector algorithm and the Comparative Received Signal Strength (CRSS) algorithm. Signal values were obtained using ray tracing software and processed with MATLAB to ascertain the effects on localization accuracy of radio map resolution, number of access points and operating frequency. The vector algorithm outperforms the CRSS algorithm, which suffers from ambiguity, although that can be reduced by using more access points and a higher operating frequency. Ambiguity is worsened by the addition of more reference points. The vector algorithm performance is enhanced by adding more access points and reference points while it degrades with increasing frequency provided that the statistical mean of error increased to about 60 cm for most studied cases.Unable to contact publisher. Contact webform only works for members - no email addresses. Raed said he would try and get contact details - email 14th March 2016The full text is unavailable. The publisher is unable to be contacted
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