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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.
Gilles L. Ramone, Marvin L. Adams, Paul F. Nowak
Nuclear Science and Engineering | Volume 125 | Number 3 | March 1997 | Pages 257-283
Technical Paper | doi.org/10.13182/NSE97-A24274
Articles are hosted by Taylor and Francis Online.
A family of transport synthetic acceleration (TSA) methods for iteratively solving within-group scattering problems is presented. A single iteration in these schemes consists of a transport sweep followed by a low-order calculation, which itself is a simplified transport problem. The method for isotropic-scattering problems in X- Y geometry is described. Our Fourier analysis of a model problem for equations with no spatial discretization shows that a previously proposed TSA method is unstable in two dimensions but that our modifications make it stable and rapidly convergent. The same procedure for discretized transport equations, using the step characteristic and two bilinear discontinuous methods, shows that discretization enhances TSA performance. A conjugate gradient algorithm for the low-order problem is described, a crude quadrature set for the low-order problem is proposed, and the number of low-order iterations per high-order sweep is limited to a relatively small value. These features lead to simple and efficient improvements to the method. TSA is tested on a series of problems, and a set of parameters is proposed for which the method behaves especially well. TSA achieves a substantial reduction in computational cost over source iteration, regardless of discretization parameters or material properties, and this reduction increases with the difficulty of the problem.