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Godzilla is helping ITER prepare for tokamak assembly
ITER employees stand by Godzilla, the most powerful commercially available industrial robot available. (Photo: ITER)
Many people are familiar with Godzilla as a giant reptilian monster that emerged from the sea off the coast of Japan, the product of radioactive contamination. These days, there is a new Godzilla, but it has a positive—and entirely fact-based—association with nuclear energy. This one has emerged inside the Tokamak Assembly Preparation Building of ITER in southern France.
Mikio Uematsu
Nuclear Science and Engineering | Volume 125 | Number 3 | March 1997 | Pages 300-313
Technical Paper | doi.org/10.13182/NSE97-A24276
Articles are hosted by Taylor and Francis Online.
A parallel processing method for the two-dimensional Sn transport code DOT3.5 has been developed to achieve a drastic reduction in computation time. In the proposed method, parallelization is achieved with angular domain decomposition and/or space domain decomposition.The calculational speed of parallel processing by angular domain decomposition is largely influenced by frequent communications between processing elements. To assess parallelization efficiency, sample problems with up to 32 × 32 spatial meshes were solved with a Sun workstation using the PVM message-passing library. As a result, parallel calculation using 16 processing elements, for example, was found to be nine times as fast as that with one processing element.,As for parallel processing by geometry segmentation, the influence of processing element communications on computation time is small; however, discontinuity at the segment boundary degrades convergence speed. To accelerate the convergence, an alternate sweep of angular flux in conjunction with space domain decomposition and a two-step rescaling method consisting of segmentwise rescaling and ordinary pointwise rescaling have been developed. By applying the developed method, the number of iterations needed to obtain a converged flux solution was reduced by a factor of 2. As a result, parallel calculation using 16 processing elements was found to be 5.9 times as fast as the original DOT3.5 calculation.
