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Going Nuclear: Notes from the officially unofficial book tour
I work in the analytical labs at one of Europe’s oldest and largest nuclear sites: Sellafield, in northwestern England. I spend my days at the fume hood front, pipette in one hand and radiation probe in the other (and dosimeter pinned to my chest, of course). Outside the lab, I have a second job: I moonlight as a writer and public speaker. My new popular science book—Going Nuclear: How the Atom Will Save the World—came out last summer, and it feels like my life has been running at full power ever since.
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.