972 resultados para 443
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It is well known that during alloy solidification, convection currents close to the so-lidification front have an influence on the structure of dendrites, the local solute concentration, the pattern of solid segregation, and eventually the microstructure of the casting and hence its mechanical properties. Controlled stirring of the melt in continuous casting or in ingot solidification is thought to have a beneficial effect. Free convection currents occur naturally due to temperature differences in the melt and for any given configuration, their strength is a function of the degree of superheat present. A more controlled forced convection current can be induced using electro-magnetic stirring. The authors have applied their Control-Volume based MHD method [1, 2] to the problem of tin solidification in an annular crucible with a water-cooled inner wall and a resistance heated outer one, for both free and forced convection situations and for various degrees of superheat. This problem was studied experimentally by Vives and Perry [3] who obtained temperature measurements, front positions and maps of electro-magnetic body force for a range of superheat values. The results of the mathematical model are compared critically against the experimental ones, in order to validate the model and also to demonstrate the usefulness of the coupled solution technique followed, as a predictive tool and a design aid. Figs 6, refs 19.
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The consecutive, partly overlapping emergence of expert systems and then neural computation methods among intelligent technologies, is reflected in the evolving scene of their application to nuclear engineering. This paper provides a bird's eye view of the state of the application in the domain, along with a review of a particular task, the one perhaps economically more important: refueling design in nuclear power reactors.
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Review of: Peter Reimann and Hans Spada (eds), Learning in Humans and Machines: Towards an Interdisciplinary Learning Science, Pergamon. (1995). ISBN: 978-0080425696
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Evacuation analysis of passenger and commercial shipping can be undertaken using computer-based simulation tools such as maritimeEXODUS. These tools emulate human shipboard behaviour during emergency scenarios; however it is largely based around the behaviour of civilian passengers and fixtures and fittings of merchant vessels. If these tools and procedures are to be applied to naval vessels there is a clear requirement to understand the behaviour of well-trained naval personnel interacting with the fixtures and fittings that are exclusive to warships. Human factor trials using Royal Navy training facilities were recently undertaken to collect data to improve our understanding of the performance of naval personnel in warship environments. The trials were designed and conducted by staff from the Fire Safety Engineering Group (FSEG) of the University of Greenwich on behalf of the Sea Technology Group (STG), Defence Procurement Agency. The trials involved a selection of RN volunteers with sea-going experience in warships, operating and traversing structural components under different angles of heel. This paper describes the trials and some of the collected data.
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The amount of atmospheric hydrogen chloride (HCl) within fire enclosures produced from the combustion of chloride-based materials tends to decay as the fire effluent is transported through the enclosure due to mixing with fresh air and absorption by solids. This paper describes an HCl decay model, typically used in zone models, which has been modified and applied to a computational fluid dynamics (CFD)-based fire field model. While the modified model still makes use of some empirical formulations to represent the deposition mechanisms, these have been reduced from the original three to two through the use of the CFD framework. Furthermore, the effect of HCl flow to the wall surfaces on the time to reach equilibrium between HCl in the boundary layer and on wall surfaces is addressed by the modified model. Simulation results using the modified HCl decay model are compared with data from three experiments. The model is found to be able to reproduce the experimental trends and the predicted HCl levels are in good agreement with measured values
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Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.
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Decapoda taken in Continuous Plankton Recorder (CPR) samples from the Pacific in 1997 and 2000-2003 have been identified and measured. Some previously un-described larval stages were referred to species and characteristics of these are described. Distributions and seasonal occurrence of decapod taxa in the samples are described and discussed with particular emphasis on the dendrobranchiate shrimp Sergestes similis and the brachyurans Cancer spp. And Chionoecetes spp. There is a prolonged larval season at low levels of abundance off the Californian coast but in the more northern waters there is a shorter productive period but numbers of larvae per sample are high, particularly in June. Larvae of Chionoecetes and other Oregoninae were found only from May to July.
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In July 2004, dominant populations of microbial ultraplankton (<5 μm), in the surface of the Celtic Sea (between UK and Eire), were repeatedly mapped using flow cytometry, at 1.5 km resolution over a region of diameter 100 km. The numerically dominant representatives of all basic functional types were enumerated including one group of phototrophic bacteria (Syn), two groups of phytoplankton (PP, NP), three groups of heterotrophic bacterioplankton (HB) and the regionally dominant group of heterotrophic protists (HP). The distributions of all organisms showed strong spatial variability with little relation to variability in physical fields such as salinity and temperature. Furthermore, there was little agreement between distributions of different organisms. The only linear correlation consistently explaining more than 50% of the variance between any pairing of the organism groups enumerated is between two different groups of HB. Specifically, no linear, or non-linear, relationship is found between any pairings of SYB, PP or HB groups with their protist predators HP. Looking for multiple dependencies, factor analysis reveals three groupings: Syn, PP and low nucleic acid content HB (LNA); high nucleic acid content HB (HNA); HP and NP. Even the manner in which the spatial variability of Syn, PP and HB abundance varies as a function of lengthscale (represented by a semivariogram) differs significantly from that for HP. In summary, although all microbial planktonic groups enumerated are present and numerically dominant throughout the region studied, at face value the relationships between them seem weak. Nevertheless, the behaviour of a simple, illustrative ecological model, with strongly interacting phototrophs and heterotrophs, with stochastic forcing, is shown to be consistent with the observed poor correlations and differences in how spatial variability varies with lengthscale. Thus, our study suggests that a comparison of microbial abundances alone may not discern strong underlying trophic interactions. Specific knowledge of these processes, in particular grazing, will be required to explain the causes of the observed microbial spatial variability and its resulting consequences for the functioning of the ecosystem.