5 resultados para Stationary bandit

em Greenwich Academic Literature Archive - UK


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Melting of metallic samples in a cold crucible causes inclusions to concentrate on the surface owing to the action of the electromagnetic force in the skin layer. This process is dynamic, involving the melting stage, then quasi-stationary particle separation, and finally the solidification in the cold crucible. The proposed modeling technique is based on the pseudospectral solution method for coupled turbulent fluid flow, thermal and electromagnetic fields within the time varying fluid volume contained by the free surface, and partially the solid crucible wall. The model uses two methods for particle tracking: (1) a direct Lagrangian particle path computation and (2) a drifting concentration model. Lagrangian tracking is implemented for arbitrary unsteady flow. A specific numerical time integration scheme is implemented using implicit advancement that permits relatively large time-steps in the Lagrangian model. The drifting concentration model is based on a local equilibrium drift velocity assumption. Both methods are compared and demonstrated to give qualitatively similar results for stationary flow situations. The particular results presented are obtained for iron alloys. Small size particles of the order of 1 μm are shown to be less prone to separation by electromagnetic field action. In contrast, larger particles, 10 to 100 μm, are easily “trapped” by the electromagnetic field and stay on the sample surface at predetermined locations depending on their size and properties. The model allows optimization for melting power, geometry, and solidification rate.

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The electric current and the associated magnetic field in aluminium electrolysis cells create effects limiting the cell productivity and possibly cause instabilities: surface waving, ‘anode effects’, erosion of pot lining, feed material sedimentation, etc. The instructive analysis is presented via a step by step inclusion of different physical coupling factors affecting the magnetic field, electric current, velocity and wave development in the electrolysis cells. The full time dependent model couples the nonlinear turbulent fluid dynamics and the extended electromagnetic field in the cell, and the whole bus bar circuit with the ferromagnetic effects. Animated examples for the high amperage cells are presented. The theory and numerical model of the electrolysis cell is extended to the cases of variable cell bottom of aluminium layer and the variable thickness of the electrolyte due to the anode non-uniform burn-out process and the presence of the anode channels. The problem of the channel importance is well known Moreau-Evans model) for the stationary interface and the velocity field, and was validated against measurements in commercial cells, particularly with the recently published ‘benchmark’ test for the MHD models of aluminium cells [1]. The presence of electrolyte channels requires also to reconsider the previous magnetohydrodynamic instability theories and the dynamic wave development models. The results indicate the importance of a ‘sloshing’ parametrically excited MHD wave development in the aluminium production cells.

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Exercise can have deleterious effects on the secretion of salivary immunoglobulin A (s-IgA), which appears to be related to perturbations in sympatheticoadrenal activation (Teeuw et al., 2004). Caffeine, commonly used for its ergogenic properties is associated with increased sympathetic nervous system activity, and it has been previously shown that caffeine ingestion before intensive cycling enhances s-IgA responses during exercise (Bishop et al., 2006). Therefore, the aim of the present study was to examine the effect of a performance cereal bar, containing caffeine, before and during prolonged exhaustive cycling on exercise performance and the salivary secretion of IgA, alpha-amylase activity and cortisol. Using a randomised cross-over design and following a 10 – 12 hour overnight fast, 12 trained cyclists, mean (SEM) age: 21(1) yr; height: 179(2) cm; body mass: 73.6(2.5) kg; maximal oxygen uptake, VO2max: 57.9(1.2) completed 2.5 h of cycling at 60%VO2max (with regular water ingestion) on a stationary ergometer, which was followed by a ride to exhaustion at 75% VO2max. Immediately before exercise, and after 55 min and 115 min of exercise participants ingested a 0.9 MJ cereal bar containing 45 g carbohydrate, 5 g protein, 3 g fat and 100 mg of caffeine (CAF) or an isocaloric noncaffeine bar (PLA). Unstimulated timed saliva samples were collected immediately before exercise, after 70 min and 130 min of exercise, and immediately after the exhaustive exercise bout. Saliva was analysed for s-IgA, alpha-amylase activity and cortisol concentration. Saliva flow rates were determined to calculate the s-IgA secretion rate. Data were analysed using a 2-way repeated measures ANOVA and post-hoc t-tests with Holm Bonferroni adjustments applied where appropriate. Time to exhaustion was 35% longer in CAF compared with PLA ((2177 (0.2) vs 1615 (0.16) s; P < 0.05)). Saliva flow rate did not change significantly during the exercise protocol. Exercise was associated with elevations in s-IgA concentration (9% increase), s-IgA secretion rate (24% increase) and alpha-amylase activity (224% increase) post-exhaustion (P < 0.01), but there was no effect of CAF on these responses. Salivary cortisol concentration increased by 64% post-exhaustion in the CAF trial only (P < 0.05), indicating an increase in adrenal activity following caffeine ingestion. Values were 35.7 (5.5) and 19.6 (3.4) nmol/L post-exhaustion for CAF and PLA, respectively. These findings show that ingestion of a caffeine containing cereal bar during prolonged exhaustive cycling enhances endurance performance, increases salivary cortisol secretion post-exhaustion, but does not affect the exercise-induced increases in s-IgA or alpha-amylase activity.

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This study investigated the effect of a fed or fasted state on the salivary immunoglobulin A (s-IgA) response to prolonged cycling. Using a randomized, crossover design, 16 active adults (8 men and 8 women) performed 2 hr of cycling on a stationary ergometer at 65% of maximal oxygen uptake on 1 occasion after an overnight fast (FAST) and on another occasion 2 hr after consuming a 2.2-MJ high-carbohydrate meal (FED). Timed, unstimulated whole saliva samples were collected immediately before ingestion of the meal, immediately preexercise, 5 min before cessation of exercise, immediately postexercise, and 1 hr postexercise. The samples were analyzed for s-IgA concentration, osmolality, and cortisol, and saliva flow rates were determined to calculate s-IgA secretion rate. Saliva flow rate decreased by 50% during exercise (p < .05), and s-IgA concentration increased by 42% (p < .05), but s-IgA secretion rate remained unchanged. There was a 37% reduction in s-IgA:osmolality postexercise (p < .05), and salivary cortisol increased by 68% (p < .05). There was no effect of FED vs. FAST on these salivary responses. The s-IgA concentration, secretion rate, and osmolality were found to be significantly lower in women than in men throughout the exercise protocol (p < .05); however, there was no difference between genders in saliva flow rate, s-IgA:osmolality ratio, or cortisol. These data demonstrate that a fed or fasted state 2 hr before exercise does not influence resting s-IgA or the response to prolonged cycling. Furthermore, these results show lower levels of s-IgA and osmolality in women than in men at rest.

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Granular air-borne particles generally carry very small amounts of electric charge as a consequence of charging by the triboelectric effect. The presence of such particles induces charge of opposite polarity on a stationary conducting electrode. The amount of charge carried by the particles and the trajectories of the particles have significant random components and the signals produced are of very low level. The signal processing is further complicated by the random variation in the concentration of particles, i.e. the solid/gas ratio. This paper compares the results obtained from the electrostatic modelling of such sensors with those obtained from experiments.