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NRC looks to leverage previous approvals for large LWRs
During this time of resurging interest in nuclear power, many conversations have centered on one fundamental problem: Electricity is needed now, but nuclear projects (in recent decades) have taken many years to get permitted and built.
In the past few years, a bevy of new strategies have been pursued to fix this problem. Workforce programs that seek to laterally transition skilled people from other industries, plans to reuse the transmission infrastructure at shuttered coal sites, efforts to restart plants like Palisades or Duane Arnold, new reactor designs that build on the legacy of research done in the early days of atomic power—all of these plans share a common throughline: leveraging work already done instead of starting over from square one to get new plants designed and built.
Jean-Marc Depinay, Michel Caillaud, Remi Sentis
Nuclear Science and Engineering | Volume 152 | Number 1 | January 2006 | Pages 48-55
Technical Paper | doi.org/10.13182/NSE06-A2562
Articles are hosted by Taylor and Francis Online.
Application of the Monte Carlo method to deep-penetration transport problems often requires a biasing technique based on the use of an importance function. Here, in the framework of a multigroup model, we use an importance function in the form Ig([arrow over]x, [arrow over]) = eKg[arrow over].[arrow over]x[varphi]g([arrow over]), where g is the energy group index that ranges from 1 to G and [arrow over] is a vector usually fixed empirically. We describe an algorithm to find a good set of coefficients Kg and a good set of functions [varphi]g. To do this, we solve a system derived from the homogenous adjoint equations. We give two numerical examples where we show how these importance functions can enhance the accuracy of the computation.