Lifetime determination of excited states in106Cd

Two separate experiments using the Differential Decay Curve Method have been performed to extract mean lifetimes of excited states in 106Cd. The medium-spin states of interest were populated by the 98Mo( 12C, 4n) 106Cd reaction performed at the Wright Nuclear Structure Lab., Yale University. From this experiment, two isomeric state mean lifetimes have been deduced. The low-lying states were populated by the 96Mo(13C, 3n)106Cd reaction performed at the Institut für Kernphysik, Universität zu Köln. The mean lifetime of the Iπ = 21 + state was deduced, tentatively, as 16.4(9) ps. This value differs from the previously accepted literature value from Coulomb excitation of 10.43(9) ps.

Does precision decrease with set size?

The brain encodes visual information with limited precision. Contradictory evidence exists as to whether the precision with which an item is encoded depends on the number of stimuli in a display (set size). Some studies have found evidence that precision decreases with set size, but others have reported constant precision. These groups of studies differed in two ways. The studies that reported a decrease used displays with heterogeneous stimuli and tasks with a short-term memory component, while the ones that reported constancy used homogeneous stimuli and tasks that did not require short-term memory. To disentangle the effects of heterogeneity and short-memory involvement, we conducted two main experiments. In Experiment 1, stimuli were heterogeneous, and we compared a condition in which target identity was revealed before the stimulus display with one in which it was revealed afterward. In Experiment 2, target identity was fixed, and we compared heterogeneous and homogeneous distractor conditions. In both experiments, we compared an optimal-observer model in which precision is constant with set size with one in which it depends on set size. We found that precision decreases with set size when the distractors are heterogeneous, regardless of whether short-term memory is involved, but not when it is homogeneous. This suggests that heterogeneity, not short-term memory, is the critical factor. In addition, we found that precision exhibits variability across items and trials, which may partly be caused by attentional fluctuations.

On kinematic relaxation and deposition of water droplets in the last stages of low pressure steam turbines

In the first part of the paper steady two-phase flow predictions have been performed for the last stage of a model steam turbine to examine the influence of drag between condensed fog droplets and the continuous vapour phase. In general, droplets due to homogeneous condensation are small and thus kinematic relaxation provides only a minor contribution to the wetness losses. Different droplet size distributions have been investigated to estimate at which size inter-phase friction becomes more important. The second part of the paper deals with the deposition of fog droplets on stator blades. Results from several references are repeated to introduce the two main deposition mechanisms which are inertia and turbulent diffusion. Extensive postprocessing routines have been programmed to calculate droplet deposition due to these effects for a last stage stator blade in three-dimensions. In principle the method to determine droplet deposition by turbulent diffusion equates to that of Yau and Young [1] and the advantages and disadvantages of this relatively simple method are discussed. The investigation includes the influence of different droplet sizes on droplet deposition rates and shows that for small fog droplets turbulent diffusion is the main deposition mechanism. If the droplets size is increased inertial effects become more and more important and for droplets around 1 μm inertial deposition dominates. Assuming realistic droplet sizes the overall deposition equates to about 1% to 3% of the incoming wetness for the investigated guide vane at normal operating conditions. Copyright © 2013 by Solar Turbines Incorporated.

Water droplet flow paths and droplet deposition in low pressure steam turbines

The complex three-dimensional two-phase flow in a low pressure steam turbine is investigated with comprehensive numerical flow simulations. In addition to the condensation process, which already takes place in the last stages of steam turbines, the numerical flow model is enhanced to consider the drag forces between the droplets and the vapour phase. The present paper shows the differences in the flow path of the phases and investigates the effect of an increasing droplet diameter. For the flow simulations a performance cluster is used because of the high effort for such multi-momentum two-phase flow calculations. In steam turbines the deposition of small water droplets on the stator blades or on parts of the casing is responsible for the formation of large coarse water droplets and these may cause additional dissipation as well as damage due to blade erosion. A method is presented that uses detailed CFD data to predict droplet deposition on turbine stator blades. This simulation method to detect regions of droplet deposition can help to improve the design of water removal devices. © Springer-Verlag Berlin Heidelberg 2013.

Unsteady numerical study of wet steam flow in a low pressure steam turbine

In steam power plants condensation already starts in the flow path of the low pressure part of the steam turbine, which leads to a complex three-dimensional two-phase flow. Wetness losses are caused due to thermodynamic and mechanical relaxation processes during condensation and droplet transport. The present investigation focuses on the unsteady effects due to rotor-stator interaction on the droplet formation process. Results of unsteady three dimensional flow simulations of a two-stage steam turbine are presented, whereby this is the first time that non-equilibrium condensation is considered in such simulations. The numerical approach is based on RANS equations, which are extended by a wet steam specific nucleation and droplet growth model. Despite the use of a high performance cluster the unsteady simulation has a considerably high simulation time of approximately 60 days by use of 48 CPUs. © Springer-Verlag Berlin Heidelberg 2012.

Wetness loss prediction for a low pressure steam turbine using computational fluid dynamics

Two-phase computational fluid dynamics modelling is used to investigate the magnitude of different contributions to the wet steam losses in a three-stage model low pressure steam turbine. The thermodynamic losses (due to irreversible heat transfer across a finite temperature difference) and the kinematic relaxation losses (due to the frictional drag of the drops) are evaluated directly from the computational fluid dynamics simulation using a concept based on entropy production rates. The braking losses (due to the impact of large drops on the rotor) are investigated by a separate numerical prediction. The simulations show that in the present case, the dominant effect is the thermodynamic loss that accounts for over 90% of the wetness losses and that both the thermodynamic and the kinematic relaxation losses depend on the droplet diameter. The numerical results are brought into context with the well-known Baumann correlation, and a comparison with available measurement data in the literature is given. The ability of the numerical approach to predict the main wetness losses is confirmed, which permits the use of computational fluid dynamics for further studies on wetness loss correlations. © IMechE 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.