Solid phase velocity measurements utilising electrostatic sensors and cross correlation signal processing

Gas-solids two phase systems are widely employed within process plant in the form of pneumatic conveyors, dust extraction systems and solid fuel injection systems. The measurement of solids phase velocity therefore has wide potential application in flow monitoring and, in conjunction with density measurement instrumentation, solids mass flow rate measurement. Historically, a number of authors have detailed possible measurement techniques, and some have published limited test results. It is, however, apparent that none of these technologies have found wide application in industry. Solids phase velocity measurements were undertaken using real time cross correlation of signals from two electrostatic sensors spaced axially along a pipeline conveying pulverised coal (PF). Details of the measurement equipment, the pilot scale test rig and the test results are presented.

Laser Doppler velocimetry measurements of particle velocity profiles in gas-solid two-phase flows

The measurement of particle velocities in two-phase gas-solid systems has a wide application in flow monitoring in process plant, where two-phase gas-solids systems are frequently employed in the form of pneumatic conveyors and solid fuel injection systems. Such measurements have proved to be difficult to make reliably in industrial environments. This paper details particle velocity measurements made in a two phase gas-solid now utilising a laser Doppler velocimetry system. Tests were carried out using both wheat flour and pulverised coal as the solids phase, with air being used as the gaseous phase throughout. A pipeline of circular section, having a diameter of 53 mm was used for the test work, with air velocities ranging from 25 to 45 m/s and suspension densities ranging from 0.001 kg to 1 kg of solids per cubic meter of air. Details of both the test equipment used, and the results of the measurements are presented.

Bridging the gap with teamwork: collaborative leadership for communities of practice in the learning and skills sector

Collaborative approaches in leadership and management are increasingly acknowledged to play a key role in successful institutions in the learning and skills sector (LSS) (Ofsted, 2004). Such approaches may be important in bridging the potential 'distance' (psychological, cultural, interactional and geographical) (Collinson, 2005) that may exist between 'leaders' and 'followers', fostering more democratic communal solidarity. This paper reports on a 2006-07 research project funded by the Centre for Excellence in Leadership (CEL) that aimed to collect and analyse data on 'collaborative leadership' (CL) in the learning and skills sector. The project investigated collaborative leadership and its potential for benefiting staff through trust and knowledge-sharing in communities of practice (CoPs). The project forms part of longer-term educational research investigating leadership in a collaborative inquiry process (Jameson et al., 2006). The research examined the potential for CL to benefit institutions, analysing respondents' understanding of and resistance to collaborative practices. Quantitative and qualitative data from senior managers and lecturers was analysed using electronic data in SPSS and Tropes Zoom. The project aimed to recommend systems and practices for more inclusive, diverse leadership (Lumby et al., 2005). Collaborative leadership has increasingly gained international prominence as emphasis shifted towards team leadership beyond zero-sum 'leadership'/ 'followership' polarities into more mature conceptions of shared leadership spaces, within which synergistic leadership spaces can be mediated. The relevance of collaboration within the LSS has been highlighted following a spate of recent government-driven policy developments in FE. The promotion of CL addresses concerns about the apparent 'remoteness' of some senior managers, and the 'neo-management' control of professionals which can increase 'distance' between leaders and 'followers' and may de-professionalise staff in an already disempowered sector. Positive benefit from 'collaborative advantage' tends to be assumed in idealistic interpretations of CL, but potential 'collaborative inertia' may be problematic in a sector characterised by rapid top-down policy changes and continuous external audit and surveillance. Constant pressure for achievement against goals leaves little time for democratic group negotiations, despite the desires of leaders to create a more collaborative ethos. Yet prior models of intentional communities of practice potentially offer promise for CL practice to improve group performance despite multiple constraints. The CAMEL CoP model (JISC infoNet, 2006) was linked to the project, providing one practical way of implementing CL within situated professional networks.The project found that a good understanding of CL was demonstrated by most respondents, who thought it could enable staff to share power and work in partnership to build trust and conjoin skills, abilities and experience to achieve common goals for the good of the sector. However, although most respondents expressed agreement with the concept and ideals of CL, many thought this was currently an idealistically democratic, unachievable pipe dream in the LSS. Many respondents expressed concerns with the 'audit culture' and authoritarian management structures in FE. While there was a strong desire to see greater levels of implementation of CL, and 'collaborative advantage' from the 'knowledge sharing benefit potential' of team leadership, respondents also strongly advised against the pitfalls of 'collaborative inertia'. A 'distance' between senior leadership views and those of staff lower down the hierarchy regarding aspects of leadership performance in the sector was reported. Finally, the project found that more research is needed to investigate CL and develop innovative methods of practical implementation within autonomous communities of professional practice.

Effects of training peer tutors in content knowledge versus tutoring skills on giving feedback to help tutees’ complex tasks

This study aims to investigate the effectiveness of training tutors in content knowledge of a particular domain versus training them in tutoring skills of pedagogical knowledge when tutoring on a complex tutee task. Forty-seven tutor-tutee pairs of fourth year secondary school students were created and assigned to one of two treatments. Twenty-two tutors received training in content knowledge and the other twenty-five tutors in tutoring skills. Tutors formulated written feedback immediately after the training. Tutees first interpreted the tutor feedback and then used it to revise their research questions. The results showed that tutors trained in tutoring skills formulated more effective feedback than tutors trained in content knowledge. In addition, tutees helped by tutoring-skills tutors found the feedback more motivating than those helped by content- knowledge tutors. However, no differences were found in tutee performance on revision. The findings are discussed in terms of the set-up of this study and implications for improving the effectiveness of peer tutoring.

Buoyancy measurements and vertical distribution of eggs of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus)

Measurements were made of the density and settling velocity of eggs of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus), using a density-gradient column. These results were related to observed vertical distributions of eggs obtained from stratified vertical distribution sampling in the Bay of Biscay. Eggs of both species had slightly positive buoyancy in local seawater throughout most of their development until near hatching, when there was a marked increase in density and they became negatively buoyant. The settling velocity of anchovy eggs, which are shaped as prolate ellipsoids, was close to predictions for spherical particles of equivalent volume. An improved model was developed for prediction of the settling velocity of sardine eggs, which are spherical with a relatively large perivitelline volume; this incorporated permeability of the chorion and adjustment of the density of the perivitelline fluid to ambient seawater. Eggs of both species were located mostly in the top 20 m of the water column, in increasing abundance towards the surface. A sub-surface peak of egg abundance was sometimes observed at the pycnocline, particularly where this was pronounced and associated with a low-salinity surface layer. There was a progressive deepening of the depth distributions for successive stages of egg development. Results from this study can be applied for improved plankton sampling of sardine and anchovy eggs and in modelling studies of their vertical distribution.

Position and structure of the subtropical/Azores front region from combined Lagrangian and remote sensing (IR/altimeter/SeaWIFS) measurements

The position and structure of the North Atlantic Subtropical Front is studied using Lagrangian flow tracks and remote sensing (AVHRR imagery: TOPEX/POSEIDON altimetry: SeaWiFS) in a broad region ( similar to 31 degree to similar to 36 degree N) of marked gradient of dynamic height (Azores Current) that extends from the Mid-Atlantic Ridge (MAR), near similar to 40 degree W, to the Eastern Boundary ( similar to 10 degree W). Drogued Argos buoy and ALACE tracks are superposed on infrared satellite images in the Subtropical Front region. Cold (cyclonic) structures, called storms, and warm (anticyclonic) structures of 100-300 km in size can be found on the south side of the Subtropical Front outcrop, which has a temperature contrast of about 1 degree C that can be followed for similar to 2500 km near 35 degree N. Warmer water adjacent to the outcrop is flowing eastward (Azores Current) but some warm water is returned westward about 300 km to the south (southern Counterflow). Estimates of horizontal diffusion in a Storm (D=2.2t10 super(2) m super(2) s super(-1)) and in the Subtropical Front region near 200 m depth (D sub(x)=1.3t10 super(4) m super(2) s super(-1), D sub(y)=2.6t10 super(3) m super(2) s super(-1)) are made from the Lagrangian tracks. Altimeter and in situ measurements show that Storms track westwards. Storms are separated by about 510 km and move westward at 2.7 km d super(-1). Remote sensing reveals that some initial structures start evolving as far east as 23 degree W but are more organized near 29 degree W and therefore Storms are about 1 year old when they reach the MAR (having travelled a distance of 1000 km). Structure and seasonality in SeaWiFS data in the region is examined.

How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.