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Framatome begins expansion of facilities in Virginia
An official groundbreaking last week at Framatome’s Mill Ridge Road facility, in Lynchburg, Va., marks the start of a $50 million expansion and an eventual addition of 500 employees, according to the nuclear company.
Juan-Luis François, Cecilia Martín-del-Campo, Luis B. Morales, Miguel-Angel Palomera
Nuclear Science and Engineering | Volume 155 | Number 3 | March 2007 | Pages 367-377
Technical Paper | Mathematics and Computation, Supercomputing, Reactor Physics and Nuclear and Biological Applications | doi.org/10.13182/NSE07-A2669
Articles are hosted by Taylor and Francis Online.
The development of a basic scatter search (SS) algorithm for the optimization of radial enrichment and gadolinia distributions for boiling water reactor (BWR) fuel lattices is presented in this paper. Scatter search is considered an evolutionary algorithm that constructs solutions by combining others. The goal of this methodology is to enable the implementation of solution procedures that can derive new solutions from combined elements. The main mechanism for combining solutions is such that a new solution is created from the strategic combination of other solutions to explore the solutions' space. Thus, an algorithm based on SS to design a 10 × 10 fuel pin array with two water zones and diagonal symmetry was developed. The lattice performance is evaluated using a global objective function, in which the multiobjective optimization problem is converted into a single-objective problem using weighting factors to attach decision-maker preferences to each objective. The objective function is evaluated using values obtained from the HELIOS code. The results show that the main design variables (average lattice enrichment and power peaking factor) are improved, related to the reference lattice, while the reactivity requirement is satisfied. Results also demonstrate that the SS method is an efficient optimization algorithm when it is applied to the BWR design and optimization problem. Its main features are based on the use of heuristic rules since the beginning of the process, which allows directing the optimization process to the solution, and the use of the diversity mechanism in the combination operator, which allows covering the search space in an efficient way.