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首页> 外文期刊>Nuclear science and engineering >Development and implementation of a Newton-BICGSTAB iterative solver in the FORMOSA-B BWR core simulator code
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Development and implementation of a Newton-BICGSTAB iterative solver in the FORMOSA-B BWR core simulator code

机译:在FORMOSA-B BWR核心模拟器代码中开发和实现Newton-BICGSTAB迭代求解器

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A Newton-Krylov iterative solver has been developed to reduce the CPU execution time of boiling water reactor (BWR) core simulators implemented in the core simulator part of the Fuel Optimization for Reloads Multiple Objectives by Simulated Annealing for BWR (FORMOSA-B) code, which is an in-core fuel management optimization code for BWRs. This new solver utilizes Newton's method to explicitly treat strong nonlinearities in the problem, replacing the traditionally used nested iterative approach. Newton's method provides the solver with a higher-than-linear convergence rate, assuming that good initial estimates of the unknowns are provided Within each Newton iteration, an appropriately preconditioned Krylov solver is utilized for solving the linearized system of equations. Taking advantage of the higher convergence rate provided by Newton's method and utilizing an efficient preconditioned Krylov solver, we have developed a Newton-Krylov solver to evaluate the three-dimensional, two-group neutron diffusion equations coupled with a two-phase flow model within a BWR core simulator. Numerical tests on the new solver have shown that speedups ranging from 1.6 to 2.1, with reference to the traditional approach of employing nested iterations to treat the nonlinear feedbacks, can be achieved However, if a preconditioned Krylov solver is employed to complete the inner iterations of the traditional approach, negligible CPU time differences are noted between the Newton-Krylov and traditional (Krylov) approaches.
机译:已开发出Newton-Krylov迭代求解器,以减少在通过针对BWR进行模拟退火的燃料优化重新加载多个目标(FORMOSA-B)代码的核心模拟器部分中实现的沸水堆(BWR)核心模拟器的CPU执行时间,这是BWR的核心燃料管理优化代码。这种新的求解器利用牛顿方法来显式处理问题中的强非线性,从而取代了传统上使用的嵌套迭代方法。牛顿的方法为求解器提供了高于线性的收敛速度,假设在每次牛顿迭代中都提供了未知的良好初始估计,则使用适当预处理的Krylov求解器来求解线性方程组。利用牛顿方法提供的更高的收敛速度并利用高效的预处理Krylov求解器,我们开发了Newton-Krylov求解器来评估三维,两组中子扩散方程以及两相流模型。 BWR核心模拟器。相对于使用嵌套迭代来处理非线性反馈的传统方法,对新求解器的数值测试表明,可以实现1.6到2.1的加速比。但是,如果使用预处理的Krylov求解器来完成新的求解器的内部迭代在传统方法中,Newton-Krylov与传统(Krylov)方法之间的CPU时间差异可忽略不计。

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