Quantification of the probability of containment failure caused by an in-vessel steam explosion for the Sizewell B PWR

AEA Technology has provided an assessment of the probability of α-mode containment failure for the Sizewell B PWR. After a preliminary review of the methodologies available it was decided to use the probabilistic approach described in the paper, based on an extension of the methodology developed by Theofanous et al. (Nucl. Sci. Eng. 97 (1987) 259–325). The input to the assessment is 12 probability distributions; the bases for the quantification of these distributions are discussed. The α-mode assessment performed for the Sizewell B PWR has demonstrated the practicality of the event-tree method with input data represented by probability distributions. The assessment itself has drawn attention to a number of topics, which may be plant and sequence dependent, and has indicated the importance of melt relocation scenarios. The α-mode failure probability following an accident that leads to core melt relocation to the lower head for the Sizewell B PWR has been assessed as a few parts in 10 000, on the basis of current information. This assessment has been the first to consider elevated pressures (6 MPa and 15 MPa) besides atmospheric pressure, but the results suggest only a modest sensitivity to system pressure.

Gentlemen, stop your engines!

For fifty years, computer chess has pursued an original goal of Artificial Intelligence, to produce a chess-engine to compete at the highest level. The goal has arguably been achieved, but that success has made it harder to answer questions about the relative playing strengths of man and machine. The proposal here is to approach such questions in a counter-intuitive way, handicapping or stopping-down chess engines so that they play less well. The intrinsic lack of man-machine games may be side-stepped by analysing existing games to place computer engines as accurately as possible on the FIDE ELO scale of human play. Move-sequences may also be assessed for likelihood if computer-assisted cheating is suspected.

Database Engines for Geographical Information Systems

Our ability to identify, acquire, store, enquire on and analyse data is increasing as never before, especially in the GIS field. Technologies are becoming available to manage a wider variety of data and to make intelligent inferences on that data. The mainstream arrival of large-scale database engines is not far away. The experience of using the first such products tells us that they will radically change data management in the GIS field.

Multiple PID mapping using neural networks in a MIMO steam generator system

A neural network was used to map three PID operating regions for a two-input two-output steam generator system. The network was used in stand alone feedforward operation to control the whole operating range of the process, after being trained from the PID controllers corresponding to each control region. The network inputs are the plant error signals, their integral, their derivative and a 4-error delay train.

Rheology of milk foams produced by steam injection

Rheology of milk foams generated by steam injection was studied during the transient destabilization process using steady flow and dynamic oscillatory techniques: yield stress (τ_y) values were obtained from a stress ramp (0.2 to 25 Pa) and from strain amplitude sweep (0.001 to 3 at 1 Hz of frequency); elastic (G') and viscous (G") moduli were measured by frequency sweep (0.1 to 150 Hz at 0.05 of strain); and the apparent viscosity (η_a) was obtained from the flow curves generated from the stress ramp. The effect of plate roughness and the sweep time on τ_y was also assessed. Yield stress was found to increase with plate roughness whereas it decreased with the sweep time. The values of yield stress and moduli—G' and G"—increased during foam destabilization as a consequence of the changes in foam properties, especially the gas volume fraction, φ, and bubble size, R_32 (Sauter mean bubble radius). Thus, a relationship between τ_y, φ, R_32, and σ (surface tension) was established. The changes in the apparent viscosity, η, showed that the foams behaved like a shear thinning fluid beyond the yield point, fitting the modified Cross model with the relaxation time parameter (λ) also depending on the gas volume fraction. Overall, it was concluded that the viscoelastic behavior of the foam below the yield point and liquid-like behavior thereafter both vary during destabilization due to changes in the foam characteristics.

Production of milk foams by steam injection: the effects of steam pressure and nozzle design

Foam properties depend on the physico-chemical characteristics of the continuous phase, the method of production and process conditions employed; however the preparation of barista-style milk foams in coffee shops by injection of steam uses milk as its main ingredient which limits the control of foam properties by changing the biochemical characteristics of the continuous phase. Therefore, the control of process conditions and nozzle design are the only ways available to produce foams with diverse properties. Milk foams were produced employing different steam pressures (100-280 kPa gauge) and nozzle designs (ejector, plunging-jet and confined-jet nozzles). The foamability of milk, and the stability, bubble size and texture of the foams were investigated. Variations in steam pressure and nozzle design changed the hydrodynamic conditions during foam production, resulting in foams having a range of properties. Steam pressure influenced foam characteristics, although the net effect depended on the nozzle design used. These results suggest that, in addition to the physicochemical determinants of milk, the foam properties can also be controlled by changing the steam pressure and nozzle design.