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.

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.