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Breaking ground on a new approach to construction
The drive to Kairos Power’s reactor demonstration site in Oak Ridge, Tenn., is not only scenic—it’s historic. Nearly 85 years ago, roughly 30,000 construction workers transformed orchards and farmland into a key Manhattan Project site. Depending on your route, you may pass by one of the three gatehouses that were once military checkpoints controlling access to Atomic Energy Commission production facilities.
Richard Vasques, Kai Krycki, Rachel N. Slaybaugh
Nuclear Science and Engineering | Volume 185 | Number 1 | January 2017 | Pages 78-106
Technical Paper | doi.org/10.13182/NSE16-35
Articles are hosted by Taylor and Francis Online.
We investigate the accuracy of the recently proposed nonclassical transport equation. This equation contains an extra independent variable compared to the classical transport equation (the path length s), and models particle transport in homogenized random media in which the distance to collision of a particle is not exponentially distributed. To solve the nonclassical equation, one needs to know the s-dependent ensemble-averaged total cross section Σt(μ, s) or its corresponding path-length distribution function p(μ, s). We consider a one-dimensional (1-D) spatially periodic system consisting of alternating solid and void layers, randomly placed along the x-axis. We obtain an analytical expression for p(μ, s) and use this result to compute the corresponding Σt(μ, s). Then, we proceed to solve numerically the nonclassical equation for different test problems in rod geometry; that is, particles can move only in the directions μ = ±1. To assess the accuracy of these solutions, we produce benchmark results obtained by (i) generating a large number of physical realizations of the system, (ii) numerically solving the transport equation in each realization, and (iii) ensemble-averaging the solutions over all physical realizations. We show that the numerical results validate the nonclassical model; the solutions obtained with the nonclassical equation accurately estimate the ensemble-averaged scalar flux in this 1-D random periodic system, greatly outperforming the widely used atomic mix model in most problems.