Intrinsic state lifetimes in Pd103 and Cd106,107

The mean-lifetimes, τ, of various medium-spin excited states in Pd103 and Cd106,107 have been deduced using the Recoil Distance Doppler Shift technique and the Differential Decay Curve Method. In Cd106, the mean-lifetimes of the Iπ=12+ state at Ex=5418 keV and the Iπ=11- state at Ex=4324 keV have been deduced as 11.4(17)ps and 8.2(7)ps, respectively. The associated β2 deformation within the axially-symmetric deformed rotor model for these states are 0.14(1) and 0.14(1), respectively. The β2 deformation of 0.14(1) for the Iπ=12+ state in Cd106 compares with a predicted β2 value from total Routhian surface (TRS) calculations of 0.17. In addition, the mean-lifetimes of the yrast Iπ=152- states in Pd103 (at Ex=1262 keV) and Cd107 (at Ex=1360 keV) have been deduced to be 31.2(44)ps and 31.4(17)ps, respectively, corresponding to β2 values of 0.16(1) and 0.12(1) assuming axial symmetry. Agreement with TRS calculations are good for Pd103 but deviate for that predicted for Cd107. © 2007 The American Physical Society.

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.