232 resultados para CONSENSUS PREDICTION
Resumo:
This work proposes a extends a novel approach to compute tran sonic Limit Cycle Oscillations using high fidelity analysis. CFD based Harmonic Balance methods have proven to be efficient tools to predict periodic phenomena. This paper’s contribution is to present a methodology to determine the unknown frequency of oscillations using an implicit for- mulation of the HB method to accurately capture Limit Cycle Oscillations (LCOs); this is achieved by defining a frequency updating procedure based on a coupled CFD/CSD Harmonic Balance formulation to find the LCO condition. A pitch/plunge aerofoil and respective linear structural models is used to exercise the new method. Results show consistent agreement between the proposed and time-marching methods for both LCO amplitude and frequency.
Resumo:
The Harmonic Balance method is an attractive solution for computing periodic responses and can be an alternative to time domain methods, at a reduced computational cost. The current paper investigates using a Harmonic Balance method for simulating limit cycle oscillations under uncertainty. The Harmonic Balance method is used in conjunction with a non-intrusive polynomial-chaos approach to propagate variability and is validated against Monte Carlo analysis. Results show the potential of the approach for a range of nonlinear dynamical systems, including a full wing configuration exhibiting supercritical and subcritical bifurcations, at a fraction of the cost of performing time domain simulations.
Resumo:
The methane solubility in five pure electrolyte solvents and one binary solvent mixture for lithium ion batteries – such as ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC) and the (50:50 wt%) mixture of EC:DMC was studied experimentally at pressures close to atmospheric and as a function of temperature between (280 and 343) K by using an isochoric saturation technique. The effect of the selected anions of a lithium salt LiX (X = hexafluorophosphate,
<img height="16" border="0" style="vertical-align:bottom" width="27" alt="View the MathML source" title="View the MathML source" src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0021961414002146-si1.gif">PF6-; tris(pentafluoroethane)trifluorurophosphate, FAP−; bis(trifluoromethylsulfonyl)imide, TFSI−) on the methane solubility in electrolytes for lithium ion batteries was then investigated using a model electrolyte based on the binary mixture of EC:DMC (50:50 wt%) + 1 mol · dm−3 of lithium salt in the same temperature and pressure ranges. Based on experimental solubility data, the Henry’s law constant of the methane in these solutions were then deduced and compared together and with those predicted by using COSMO-RS methodology within COSMOthermX software. From this study, it appears that the methane solubility in each pure solvent decreases with the temperature and increases in the following order: EC < PC < EC:EMC (50:50 wt%) < DMC < EMC < DEC, showing that this increases with the van der Walls force in solution. Additionally, in all investigated EC:DMC (50:50 wt%) + 1 mol · dm−3 of lithium salt electrolytes, the methane solubility decreases also with the temperature and the methane solubility is higher in the electrolyte containing the LiFAP salt, followed by that based on the LiTFSI one. From the variation of the Henry’s law constants with the temperature, the partial molar thermodynamic functions of solvation, such as the standard Gibbs free energy, the enthalpy, and the entropy where then calculated, as well as the mixing enthalpy of the solvent with methane in its hypothetical liquid state. Finally, the effect of the gas structure on their solubility in selected solutions was discussed by comparing methane solubility data reported in the present work with carbon dioxide solubility data available in the same solvents or mixtures to discern the more harmful gas generated during the degradation of the electrolyte, which limits the battery lifetime.
Resumo:
In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).
Resumo:
Electric Vehicle (EV) technology has developed rapidly in recent years, with the result that increasing levels of EV penetration are expected on electrical grids in the near future. The increasing electricity demand due to EVs is expected to provide many challenges for grid companies, and it is expected that it will be necessary to reinforce the current electrical grid infrastructure to cater for increasing loads at distribution level. However, by harnessing the power of Vehicle to Grid (V2G) technologies, groups of EVs could be harnessed to provide ancillary services to the grid. Current unbalance occurs at distribution level when currents are unbalanced between each of the phases. In this paper a distributed consensus algorithm is used to coordinate EV charging in order to minimise current unbalance. Simulation results demonstrate that the proposed algorithm is effective in rebalancing phase currents.
Resumo:
The 1998 Multiparty Agreement established a consociational system that contains within it an explicit dualism: unionist/nationalist, north and south of Ireland, and British and Irish. But although this formula has facilitated relatively stable and devolved governance, it is based on a distorted representation of a society in which there are much more complex divisions and, indeed, many common problems. Citizen-led efforts towards deliberative democracy since the 1980s have demonstrated both the will and the capacity for alternative, consensual political expressions. This chapter examines the challenges and opportunities facing these citizen-led initiatives in a political environment which, despite the significant decline in violence and terror, seems stubbornly resistant to the idea of broadening the various means of democratic participation.
Resumo:
OBJECTIVES: To investigate mechanisms of reduced susceptibility to commonly used antibiotics in Prevotella cultured from patients with cystic fibrosis (CF), patients with invasive infection and healthy control subjects and to determine whether genotype can be used to predict phenotypic resistance.
METHODS: The susceptibility of 157 Prevotella isolates to seven antibiotics was compared, with detection of resistance genes (cfxA-type gene, ermF and tetQ), mutations within the CfxA-type β-lactamase and expression of efflux pumps.
RESULTS: Prevotella isolates positive for a cfxA-type gene had higher MICs of amoxicillin and ceftazidime compared with isolates negative for this gene (P < 0.001). A mutation within the CfxA-type β-lactamase (Y239D) was associated with ceftazidime resistance (P = 0.011). The UK CF isolates were 5.3-fold, 2.7-fold and 5.7-fold more likely to harbour ermF compared with the US CF, UK invasive and UK healthy control isolates, respectively. Higher concentrations of azithromycin (P < 0.001) and clindamycin (P < 0.001) were also required to inhibit the growth of the ermF-positive isolates compared with ermF-negative isolates. Furthermore, tetQ-positive Prevotella isolates had higher MICs of tetracycline (P = 0.001) and doxycycline (P < 0.001) compared with tetQ-negative isolates. Prevotella spp. were also shown, for the first time, to express resistance nodulation division (RND)-type efflux pumps.
CONCLUSIONS: This study has demonstrated that Prevotella isolated from various sources harbour a common pool of resistance genes and possess RND-type efflux pumps, which may contribute to tetracycline resistance. The findings indicate that antibiotic resistance is common in Prevotella spp., but the genotypic traits investigated do not reflect phenotypic antibiotic resistance in every instance.
Resumo:
Low-velocity impact damage can drastically reduce the residual mechanical properties of the composite structure even when there is barely visible impact damage. The ability to computationally predict the extent of damage and compression after impact (CAI) strength of a composite structure can potentially lead to the exploration of a larger design space without incurring significant development time and cost penalties. A three-dimensional damage model, to predict both low-velocity impact damage and compression after impact CAI strength of composite laminates, has been developed and implemented as a user material subroutine in the commercial finite element package, ABAQUS/Explicit. The virtual tests were executed in two steps, one to capture the impact damage and the other to predict the CAI strength. The observed intra-laminar damage features, delamination damage area as well as residual strength are discussed. It is shown that the predicted results for impact damage and CAI strength correlated well with experimental testing.
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The comparator account holds that processes of motor prediction contribute to the sense of agency by attenuating incoming sensory information and that disruptions to this process contribute to misattributions of agency in schizophrenia. Over the last 25 years this simple and powerful model has gained widespread support not only as it relates to bodily actions but also as an account of misattributions of agency for inner speech, potentially explaining the etiology of auditory verbal hallucination (AVH). In this paper we provide a detailed analysis of the traditional comparator account for inner speech, pointing out serious problems with the specification of inner speech on which it is based and highlighting inconsistencies in the interpretation of the electrophysiological evidence commonly cited in its favor. In light of these analyses we propose a new comparator account of misattributed inner speech. The new account follows leading models of motor imagery in proposing that inner speech is not attenuated by motor prediction, but rather derived directly from it. We describe how failures of motor prediction would therefore directly affect the phenomenology of inner speech and trigger a mismatch in the comparison between motor prediction and motor intention, contributing to abnormal feelings of agency. We argue that the new account fits with the emerging phenomenological evidence that AVHs are both distinct from ordinary inner speech and heterogeneous. Finally, we explore the possibility that the new comparator account may extend to explain disruptions across a range of imagistic modalities, and outline avenues for future research.
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Responses by marine species to ocean acidification (OA) have recently been shown to be modulated by external factors including temperature, food supply and salinity. However the role of a fundamental biological parameter relevant to all organisms, that of body size, in governing responses to multiple stressors has been almost entirely overlooked. Recent consensus suggests allometric scaling of metabolism with body size differs between species, the commonly cited 'universal' mass scaling exponent (b) of A3/4 representing an average of exponents that naturally vary. One model, the Metabolic-Level Boundaries hypothesis, provides a testable prediction: that b will decrease within species under increasing temperature. However, no previous studies have examined how metabolic scaling may be directly affected by OA. We acclimated a wide body-mass range of three common NE Atlantic echinoderms (the sea star Asterias rubens, the brittlestars Ophiothrix fragilis and Amphiura filiformis) to two levels of pCO(2) and three temperatures, and metabolic rates were determined using closed-chamber respirometry. The results show that contrary to some models these echinoderm species possess a notable degree of stability in metabolic scaling under different abiotic conditions; the mass scaling exponent (b) varied in value between species, but not within species under different conditions. Additionally, we found no effect of OA on metabolic rates in any species. These data suggest responses to abiotic stressors are not modulated by body size in these species, as reflected in the stability of the metabolic scaling relationship. Such equivalence in response across ontogenetic size ranges has important implications for the stability of ecological food webs.
Resumo:
Mollusks are the most morphologically disparate living animal phylum, they have diversified into all habitats, and have a deep fossil record. Monophyly and identity of their eight living classes is undisputed, but relationships between these groups and patterns of their early radiation have remained elusive. Arguments about traditional morphological phylogeny focus on a small number of topological concepts but often without regard to proximity of the individual classes. In contrast, molecular studies have proposed a number of radically different, inherently contradictory, and controversial sister relationships. Here, we assembled a dataset of 42 unique published trees describing molluscan interrelationships. We used these data to ask several questions about the state of resolution of molluscan phylogeny compared to a null model of the variation possible in random trees constructed from a monophyletic assemblage of eight terminals. Although 27 different unique trees have been proposed from morphological inference, the majority of these are not statistically different from each other. Within the available molecular topologies, only four studies to date have included the deep-sea class Monoplacophora; but 36.4% of all trees are not significantly different. We also present supertrees derived from 2 data partitions and 3 methods, including all available molecular molluscan phylogenies, which will form the basis for future hypothesis testing. The supertrees presented here were not constructed to provide yet another hypothesis of molluscan relationships, but rather to algorithmically evaluate the relationships present in the disparate published topologies. Based on the totality of available evidence, certain patterns of relatedness among constituent taxa become clear. The internodal distance is consistently short between a few taxon pairs, particularly supporting the relatedness of Monoplacophora and the chitons, Polyplacophora. Other taxon pairs are rarely or never found in close proximity, such as the vermiform Caudofoveata and Bivalvia. Our results have specific utility for guiding constructive research planning in order to better test relationships in Mollusca as well as other problematic groups. Taxa with consistently proximate relationships should be the focus of a combined approach in a concerted assessment of potential genetic and anatomical homology, while unequivocally distant taxa will make the most constructive choices for exemplar selection in higher-level phylogenomic analyses.