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Second round of Launch Pad selections includes eight newcomers
The National Reactor Innovation Center at Idaho National Laboratory has announced 13 project selections across 12 companies for the Nuclear Energy Launch Pad, a Department of Energy–led program that integrates reactor and fuel facility authorization, testing, and deployment support for private nuclear developers.
The Launch Pad emerged from the Reactor Pilot Program and Fuel Line Pilot Program.
According to INL, projects selected include reactor development and nuclear fuel cycle advancements, including fabrication, enrichment, and conversion technologies.
Cong Liu, Junxia Wei, Bin Zhang, Jinhong Li, Zhiqiang Sheng, Shuang Tan
Nuclear Science and Engineering | Volume 197 | Number 11 | November 2023 | Pages 2853-2883
Regular Research Article | doi.org/10.1080/00295639.2023.2169537
Articles are hosted by Taylor and Francis Online.
Maintaining a reasonable balance between computational accuracy and overhead is important for neutron transport simulations of engineering problems. This paper presents a goal-oriented mesh adaptive algorithm applied to the multigroup discrete ordinates equation for fixed source and criticality problems. The dual-weighted residual (DWR) approach estimates numerical solution errors and drives local mesh refinement for specific targets, such as detector response, integral flux, and multiplication factor. We employ a reconstruction method to evaluate the spatial residuals of the fluxes obtained by the weighted difference scheme. To improve the performance of adaptive algorithms, new estimation models are proposed for adjoint fluxes needed by the DWR theory, including a regional goal model for fixed source problems and an inconsistent fission source model for k-eigenvalue problems. Additionally, we analyze the impact of the truncation of flux reconstruction and isotropic approximation of adjoint fluxes on grid error indicators and adaptive calculations. Numerical results demonstrate that for the quantities of interest, our adaptive approach saves more than 70% of computational effort and run time when obtaining a level of high accuracy comparable to that of uniform fine grids.