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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.
William D. Fullmer, Martin A. Lopez De Bertodano
Nuclear Technology | Volume 191 | Number 2 | August 2015 | Pages 185-192
Technical Note | Fission Reactors | doi.org/10.13182/NT14-110
Articles are hosted by Taylor and Francis Online.
One-dimensional two-fluid models used for the simulation of large, industrial-scale problems require many simplifying assumptions to make a closed model that is tractable, applicable to a wide variety of flow regimes, and computationally efficient. Of particular interest here is the virtual mass force and the simplified form used in the RELAP5/MOD3.3 model. Comparison of the characteristics of the simplified model with a more complete two-fluid model for bubbly two-phase flow shows a remarkable similarity. Comparison to experimental data is also surprisingly favorable—provided that the flow conditions are determined appropriately. Namely, the characteristic analysis determined that a drift velocity for distorted bubbly flow, rather than for churn-turbulent flow, matches the data more accurately. The study is concluded by implementing a distorted bubbly drift velocity correlation into the RELAP5/MOD3.3 code. A comparison of the void wave speeds with the data confirms the results of the characteristic analysis.