Muitiobjective pressurized water reactor reload core design by nondominated genetic algorithm search

The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends: on the core simulator used; the GA itself is code independent.

SIMULATION OF THE ANAEROBIC DIGESTION OF FOOD WASTE

This study has established that the use of a computer model, the Anaerobic Digestion Model 1, is suitable for investigation of the stability and energy balance of the anaerobic digestion of food waste. In simulations, digestion of undiluted food waste was less stable than that of sewage sludge or mixtures of the two, but gave much higher average methane yields per volume of digester. In the best case scenario simulations, food waste resulted in the production of 5.3 Nm3 of methane per day per m3 of digester volume, much higher than that of sewage sludge alone at 1.1 Nm3 of methane per day per m3. There was no substantial difference in the yield per volatile solids added. Food waste, however, did not sustain a stable digestion if its cation content was below a certain level. Mixing food waste and sewage sludge allowed digestion with a lower cation content. The changes in composition of food waste feedstock caused great variation in biogas output and even more so volatile fatty acid concentration, which lowered the digestion stability. Modelling anaerobic digestion allowed simulation of failure scenarios and gave insights into the importance of the cation/anion balance and the magnitude of variability in feedstocks.