Turbulence model performance in continuous casting simulations

This paper concerns the development and validation (using an oil/water system) of a finite volume computer model of the continuous casting process for steel flat products. The emphasis is on hydrodynamic aspects and in particular the dynamic behaviour of the metal/slag interface. Instability and wave action encourage the entrainment of inclusions into the melt affecting product quality. To track the interface between oil and water a new implicit algorithm was developed, called the Counter Diffusion Method. To prevent excessive damping, a time-filtered version of the k-e model, was found necessary, with appropriate density stratification terms representing interface turbulence damping.

FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.