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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.
M. M. R. Williams
Nuclear Science and Engineering | Volume 135 | Number 2 | June 2000 | Pages 123-140
Technical Paper | doi.org/10.13182/NSE00-A2129
Articles are hosted by Taylor and Francis Online.
A formalism has been developed for studying the transmission of neutrons through a spatially stochastic medium. The stochastic components are represented by absorbing plates of randomly varying strength and random position. This type of geometry enables the Feinberg-Galanin-Horning method to be employed and leads to the solution of a coupled set of linear equations for the flux at the plate positions. The matrix of the coefficients contains members that are random and these are solved by simulation. That is, the strength and plate positions are sampled from uniform distributions and the equations solved many times (in this case 105 simulations are carried out). Probability distributions for the plate transmission and reflection factors are constructed from which the mean and variance can be computed.These essentially exact solutions enable closure approximations to be assessed for accuracy. To this end, we have compared the mean and variance obtained from the first order smoothing approximation of Keller with the exact results and have found excellent agreement for the mean values but note deviations of up to 40% for the variance. Nevertheless, for the problems considered here, first order smoothing appears to be of practical value and is very efficient numerically in comparison with simulation.