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Delay, cost increase announced for U.K. nuclear project
Perspex screens and reduced seating capacity in the Hinkley Point canteens help protect the workforce during breaks, EDF Energy said. Photo: EDF Energy
The unfortunate effects of the COVID-19 pandemic on nuclear new-build projects haven’t stopped with Vogtle: EDF Energy this morning reported that the expected startup date for Unit 1 at its Hinkley Point C site is being pushed from late 2025 to June 2026.
In addition, the project’s completion costs are now estimated to be in the range of £22 billion to £23 billion (about $30.2 billion to $31.5 billion), some £500 million (about $686 million) more than the 2019 estimate, EDF said, adding the caveat that these revisions assume an ability to begin a return to normal site conditions by the second quarter of 2021.
Yunzhao Li, E. E. Lewis, Micheal A. Smith, Hongchun Wu, Liangzhi Cao
Nuclear Science and Engineering | Volume 179 | Number 1 | January 2015 | Pages 42-58
Technical Paper | dx.doi.org/10.13182/NSE13-103
Articles are hosted by Taylor and Francis Online.
Combinations of three approaches are examined as options to replace the algorithms presently employed in the variational nodal code VARIANT. They are preconditioned Generalized Minimal Residual (GMRES) algorithms, parallelism in energy, and Wielandt acceleration. Together with partitioned matrix and Gauss-Seidel (GS) preconditioners, two GMRES algorithms are formulated to replace the upscattering iteration and facilitate energy parallelism and Wielandt acceleration. The GMRES algorithms are tested on two-dimensional thermal and fast reactor diffusion problems. The two GMRES algorithms yield higher efficiencies in energy group parallelization and Wielandt acceleration than simple parallelization of the existing GS algorithm. With preconditioning the GMRES algorithms reduce the total computing time by a factor of 2 to 4 and in some cases by a factor of >10. A multilevel iteration optimization scheme is investigated that automatically adjusts the relative error tolerance of the inner iterations according to the estimated convergence rate of the corresponding outer iterations and updates the Wielandt shift magnitude as the calculations progress. Numerical results based on large two-dimensional thermal and fast reactor diffusion problems demonstrate that automated optimization of the multilevel iterative processes reduces iteration numbers by as much as an order of magnitude.