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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.
J. Coulot, F. Lavielle, A. Faggiano, N. Bellon, B. Aubert, M. Schlumberger, M. Ricard
Nuclear Science and Engineering | Volume 149 | Number 2 | February 2005 | Pages 124-130
Technical Paper | doi.org/10.13182/NSE05-A2483
Articles are hosted by Taylor and Francis Online.
Standard macroscopic methods used to assess the dose in nuclear medicine are limited to cases of homogeneous radionuclide distributions and provide dose estimations at the organ level. In a few applications, like radioimmunotherapy, the mean dose to an organ is not suitable to explain clinical observations, and knowledge of the dose at the tissular level is mandatory. Therefore, one must determine how particles lose their energy and what is the best way to represent tissues. The Monte Carlo method is appropriate to solve the problem of particle transport, but the question of the geometric representation of biology remains. In this paper, we describe a software (CLUSTER3D) that is able to build randomly biologically representative sphere cluster geometries using a statistical description of tissues. These geometries are then used by our Monte Carlo code called DOSE3D to perform particle transport. First results obtained on thyroid models highlight the need of cellular and tissular data to take into account actual radionuclide distributions in tissues. The flexibility and reliability of the method makes it a useful tool to study the energy deposition at various cellular and tissular levels in any configuration.