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G7 pledges support for nuclear at Italy meeting
The Group of Seven (G7) recommitted its support for nuclear energy in the countries that opt to use it at a Ministerial Meeting on Climate in Italy last month.
In a statement following the April meeting, the group committed to support multilateral efforts to strengthen the resilience of nuclear supply chains, referencing the goal set by 25 countries during last year’s COP28 climate conference in Dubai to triple global nuclear generating capacity by 2050.
Kibog Lee, Chang Hyo Kim
Nuclear Science and Engineering | Volume 143 | Number 3 | March 2003 | Pages 268-280
Technical Paper | doi.org/10.13182/NSE03-A2335
Articles are hosted by Taylor and Francis Online.
A least-squares method is presented that is designed for an advanced core power distribution monitoring calculation of pressurized water reactors (PWRs) and its applicability to the Yonggwang Unit 3 (YGN-3) PWR in terms of computational speed and accuracy. The method here makes use of the solution to the normal equation that is derived from solving the overdetermined system of equations comprising the fixed in-core detector response equations and the nodal neutronics design equations in the least-squares principle. In order to ensure high computational accuracy and speed of power distribution monitoring calculations, the nonlinear analytical nodal method (ANM) is employed for accurate core neutronics calculations, and a preconditioned conjugate gradient normal residual iteration algorithm is adopted for speedy solution to the normal equation. The applicability of the least-squares method for the core power distribution monitoring of the YGN-3 PWR is examined by pure numerical experiments in which the reference three-dimensional (3-D) power distribution is calculated by the 36 node-per-fuel-assembly (N/A) nonlinear ANM. Simulated detector signals are derived from the reference power distribution to establish detector response equations. The 3-D monitored core power distribution is obtained from the 1 or 4 N/A solution to the normal equation and compared with the reference power distribution to determine the prediction accuracy. It is shown that the least-squares method can predict a very accurate 3-D power distribution within the acceptable computation time of a few seconds on a 733-MHz personal computer.