JFNK方法迭代过程与物理约束

对Jacobian-free Newton-Krylov(JFNK)方法迭代过程进行分析,通过在迭代过程中吸收物理约束信息,对JFNK方法进行改进.改进后的JFNK方法迭代过程中的迭代序列总是满足物理约束,克服了迭代过程中可能出现的非物理现象.采用改进之后的算法求解二维三温能量方程,可以保证在迭代过程中不会出现负温度问题,使JFNK方法的健壮性得到提高.     

对称性及多群中子扩散方程数值解

在多群中子扩散方程解析解的基础上,利用方程及求解域的对称性建立了新的数值求解中子扩散方程的理论模型.该模型显著的优点是适用于各种对称区域(二维、三维区域)尤其是非正方形区域中子扩散方程的求解,它彻底避免了常规节块法应用于非正方形几何时所出现的奇异性问题,且所得的解在求解域内任意点上均满足扩散方程.以二、三维六角形几何为例建立了数学模型,并用基准问题校核了模型的正确性. 关键词： 中子扩散方程 对称群 数值解 解析     

用SIP和SSIP方法求解三维反应堆中子扩散方程

本文首先简要介绍三维区域中的中子扩散方程及其差分方程的建立及求解的内、外迭代过程。然后导出内迭代过程中求解差分方程的SIP和SSIP公式,以及内、外迭代的加速方法和迭代参数的选取。最后给出一些数值结果。     

求解二维三温辐射扩散方程组的一种代数两层迭代方法

在二维三温辐射扩散方程离散代数方程组的求解中,由于光子、电子和离子温度之间存在耦合关系,而且三个温度在同种介质中有不同的扩散性质,使得经典的代数多重网格(AMG)方法难以直接应用.基于特殊粗化策略,在粗网格层解除了这种耦合关系,得到一种代数两层网格方法,而粗网格方程由经典AMG方法求解.将这一算法具体应用于JFNK(Jacobian自由的Newton-Krylov)框架中预处理方程的求解,并基于该框架求解二维三温辐射扩散方程组.数值结果显示了算法的可扩展性和健壮性.     

基于节块展开法的Jacobian-Free Newton Krylov联立求解物理-热工耦合问题

目前反应堆物理热工耦合程序通常采用固定点迭代思路, 这可能导致部分工况收敛速度慢, 甚至出现不收敛的现象, 严重影响了计算效率. 基于此, 本文将高效的粗网节块展开法(NEM)与Jacobian-Free Newton-Krylov (JFNK)方法结合, 成功地开发出了一套新方法NEM_JFNK, 实现了联立求解物理热工耦合问题. 首先将NEM推广到热工问题的求解, 之后使用NEM来离散物理-热工耦合问题的所有控制方程, 使得所有变量都能在粗网格下进行离散, 从而大大减小求解问题的规模; 其次将NEM离散后的方程经过某些特殊的处理, 成功地嵌入JFNK的计算框架, 最终开发出了基于线性预处理的NEM_JFNK, 即LP_NEM_JFNK. 此外, 为了充分利用原有的迭代程序, 避免JFNK残差方程的重新建立, 本文还开发了无需重构残差方程的NEM_JFNK, 即NRC_NEM_JFNK, 并实现“黑箱”耦合. 文中以一维中子-热工模型为例, 给出LP_NEM_JFNK和NRC_NEM_JFNK数学模型, 并对计算结果进行分析. 结果表明:新方法无论是收敛速度还是计算效率都具有明显优势.     

泄漏迭代法在求解中子扩散方程中的应用

本文着重介绍了用于求解中子扩散方程的泄漏迭代方法及其边界条件的解析处理,并将此方法用于反应堆设计的计算,结果表明,这种泄漏迭代方法可以满足反应堆的设计要求。     

JFNK方法在S N输运计算中的应用

JFNK(Jacobian-free Newton-Krylov)方法是一种求解非线性方程的高效迭代算法。传统输运计算中的负通量修正与k-特征值迭代使得原本线性的输运计算转变为非线性问题数值求解。为提高非线性输运问题的计算效率,将这两类非线性问题离散成残差形式的非线性方程组,并采用JFNK方法对其进行迭代求解。分析不同约束条件对JFNK方法性能的影响,并将其与NK(Newton-Krylov)方法进行对比。针对JFNK方法的内迭代过程,分析两类子空间方法(GMRES(m)与LGMRES)对整体计算效率的影响。数值结果表明：①相比于传统的幂迭代方法,JFNK方法具有更高的计算效率;②Jacobian矩阵向量积的差分近似对结果没有影响,且基于物理的约束条件比标准的数学约束更加高效;③LGMRES可以充分利用子空间的信息,从而使得JFNK方法整体表现更加高效。     

粒子输运方程的确定论计算方法

针对实际应用中辐射和中子输运数值模拟,讨论球一维和柱二维几何粒子输运方程确定论计算方法的研究现状,包括离散纵标、球谐函数、迭代加速、并行计算等方法.重点讨论输运计算方法所取得的若干研究进展,包括离散纵标求积组、自适应时间离散格式、本征值迭代求解方法、简化球谐函数方法、修正的子网格隅角平衡方法、灰体综合加速方法、迭代初值选取方法、输运与扩散耦合方法、基于预估校正的并行格式等.简要介绍了相关输运计算程序的研制情况,并分析输运计算方法存在的难点,提出待开展研究的内容.     

非定常对流扩散方程的高精度多重网格方法

由已有的求解定常对流扩散方程的高阶紧致差分格式出发,直接推导出了数值求解非定常对流扩散方程的一种高阶隐式紧致差分格式,其时间为二阶精度,空间为四阶精度,并且是无条件稳定的。为了加快传统迭代法在求解隐格式时在每一个时间步上的迭代收敛速度,采用了多重网格加速技术。数值实验结果验证了本文方法的高阶精度、高效性及高稳定性。     

间断有限元方法求解一维非平衡辐射扩散方程

研究一维非平衡辐射扩散方程的数值方法.通过求解间断系数热传导方程的广义黎曼问题,得到一种带加权数值流量,基于该数值流量构造了一类新型的间断有限元方法.在时间离散上采用向后Euler方法,形成的非线性方程组采用Picard迭代求解.数值试验表明该方法具有捕捉大梯度的能力,而且能适应扩散系数间断的情形.     

Implementation of the Jacobian-free Newton–Krylov method for solving the first-order ice sheet momentum balance

We have implemented the Jacobian-free Newton–Krylov (JFNK) method for solving the first-order ice sheet momentum equation in order to improve the numerical performance of the Glimmer-Community Ice Sheet Model (Glimmer-CISM), the land ice component of the Community Earth System Model (CESM). Our JFNK implementation is based on significant re-use of existing code. For example, our physics-based preconditioner uses the original Picard linear solver in Glimmer-CISM. For several test cases spanning a range of geometries and boundary conditions, our JFNK implementation is 1.8–3.6 times more efficient than the standard Picard solver in Glimmer-CISM. Importantly, this computational gain of JFNK over the Picard solver increases when refining the grid. Global convergence of the JFNK solver has been significantly improved by rescaling the equation for the basal boundary condition and through the use of an inexact Newton method. While a diverse set of test cases show that our JFNK implementation is usually robust, for some problems it may fail to converge with increasing resolution (as does the Picard solver). Globalization through parameter continuation did not remedy this problem and future work to improve robustness will explore a combination of Picard and JFNK and the use of homotopy methods.     

A second order self-consistent IMEX method for radiation hydrodynamics

We present a second order self-consistent implicit/explicit (methods that use the combination of implicit and explicit discretizations are often referred to as IMEX (implicit/explicit) methods ,  and ) time integration technique for solving radiation hydrodynamics problems. The operators of the radiation hydrodynamics are splitted as such that the hydrodynamics equations are solved explicitly making use of the capability of well-understood explicit schemes. On the other hand, the radiation diffusion part is solved implicitly. The idea of the self-consistent IMEX method is to hybridize the implicit and explicit time discretizations in a nonlinearly consistent way to achieve second order time convergent calculations. In our self-consistent IMEX method, we solve the hydrodynamics equations inside the implicit block as part of the nonlinear function evaluation making use of the Jacobian-free Newton Krylov (JFNK) method ,  and . This is done to avoid order reductions in time convergence due to the operator splitting. We present results from several test calculations in order to validate the numerical order of our scheme. For each test, we have established second order time convergence.     

Improving the numerical convergence of viscous-plastic sea ice models with the Jacobian-free Newton–Krylov method

We have implemented the Jacobian-free Newton–Krylov (JFNK) method to solve the sea ice momentum equation with a viscous-plastic (VP) formulation. The JFNK method has many advantages: the system matrix (the Jacobian) does not need to be formed and stored, the method is parallelizable and the convergence can be nearly quadratic in the vicinity of the solution. The convergence rate of our JFNK implementation is characterized by two phases: an initial phase with slow convergence and a fast phase for which the residual norm decreases significantly from one Newton iteration to the next. Because of this fast phase, the computational gain of the JFNK method over the standard solver used in existing VP models increases with the required drop in the residual norm (termination criterion). The JFNK method is between 3 and 6.6 times faster (depending on the spatial resolution and termination criterion) than the standard solver using a preconditioned generalized minimum residual method. Resolutions tested in this study are 80, 40, 20 and 10 km. For a large required drop in the residual norm, both JFNK and standard solvers sometimes do not converge. The failure rate for both solvers increases as the grid is refined but stays relatively small (less than 2.3% of failures). With increasing spatial resolution, the velocity gradients (sea ice deformations) get more and more important. Nonlinear solvers such as the JFNK method tend to have difficulties when there are such sharp structures in the solution. This lack of robustness of both solvers is however a debatable problem as it mostly occurs for large required drops in the residual norm. Furthermore, when it occurs, it usually affects only a few grid cells, i.e., the residual is small for all the velocity components except in very localized regions. Globalization approaches for the JFNK solver, such as the line search method, have not yet proven to be successful. Further investigation is needed.     

A fully second order implicit/explicit time integration technique for hydrodynamics plus nonlinear heat conduction problems

We present a fully second order implicit/explicit time integration technique for solving hydrodynamics coupled with nonlinear heat conduction problems. The idea is to hybridize an implicit and an explicit discretization in such a way to achieve second order time convergent calculations. In this scope, the hydrodynamics equations are discretized explicitly making use of the capability of well-understood explicit schemes. On the other hand, the nonlinear heat conduction is solved implicitly. Such methods are often referred to as IMEX methods [2], [1], [3]. The Jacobian-Free Newton Krylov (JFNK) method (e.g. [10], [9]) is applied to the problem in such a way as to render a nonlinearly iterated IMEX method. We solve three test problems in order to validate the numerical order of the scheme. For each test, we established second order time convergence. We support these numerical results with a modified equation analysis (MEA) [21], [20]. The set of equations studied here constitute a base model for radiation hydrodynamics.     

Parallel Jacobian-free Newton Krylov solution of the discrete ordinates method with flux limiters for 3D radiative transfer

The present study introduces a parallel Jacobian-free Newton Krylov (JFNK) general minimal residual (GMRES) solution for the discretized radiative transfer equation (RTE) in 3D, absorbing, emitting and scattering media. For the angular and spatial discretization of the RTE, the discrete ordinates method (DOM) and the finite volume method (FVM) including flux limiters are employed, respectively. Instead of forming and storing a large Jacobian matrix, JFNK methods allow for large memory savings as the required Jacobian-vector products are rather approximated by semiexact and numerical formulations, for which convergence and computational times are presented. Parallelization of the GMRES solution is introduced in a combined memory-shared/memory-distributed formulation that takes advantage of the fact that only large vector arrays remain in the JFNK process. Results are presented for 3D test cases including a simple homogeneous, isotropic medium and a more complex non-homogeneous, non-isothermal, absorbing–emitting and anisotropic scattering medium with collimated intensities. Additionally, convergence and stability of Gram–Schmidt and Householder orthogonalizations for the Arnoldi process in the parallel GMRES algorithms are discussed and analyzed. Overall, the introduction of JFNK methods results in a parallel, yet scalable to the tested 2048 processors, and memory affordable solution to 3D radiative transfer problems without compromising the accuracy and convergence of a Newton-like solution.     

On the comparison of semi-analytical methods for the stability analysis of delay differential equations

This paper provides the first comparison of the semi-discretization, spectral element, and Legendre collocation methods. Each method is a technique for solving delay differential equations (DDEs) as well as determining regions of stability in the DDE parameter space. We present the necessary concepts, assumptions, and equations required to implement each method. To compare the relative performance between the methods, the convergence rate and computational time for each method is compared in three numerical studies consisting of a ship stability example, the delayed damped Mathieu equation, and a helicopter rotor control problem. For each study, we present one or more stability diagrams in the parameter space and one or more convergence plots. The spectral element method is demonstrated to have the quickest convergence rate while the Legendre collocation method requires the least computational time. The semi-discretization method on the other hand has both the slowest convergence rate and requires the most computational time.     

非线性薛定谔方程的高阶分裂改进光滑粒子动力学算法

为提高传统光滑粒子动力学(SPH)方法求解高维非线性薛定谔(nonlinear Schr?dinger/Gross-Pitaevskii equation, NLS/GP)方程的数值精度和计算效率,本文首先基于高阶时间分裂思想将非线性薛定谔方程分解成线性导数项和非线性项,其次拓展一阶对称SPH方法对复数域上线性导数部分进行显式求解,最后引入MPI并行技术,结合边界施加虚粒子方法给出一种能够准确、高效地求解高维NLS/GP方程的高阶分裂修正并行SPH方法.数值模拟中,首先对带有周期性和Dirichlet边界条件的NLS方程进行求解,并与解析解做对比,准确地得到了周期边界下孤立波的奇异性,且对提出方法的数值精度、收敛速度和计算效率进行了分析;随后,运用给出的高阶分裂粒子方法对复杂二维和三维NLS/GP问题进行了数值预测,并与其他数值结果进行比较,准确地展现了非线性孤立波传播中的奇异现象和玻色-爱因斯坦凝聚态中带外旋转项的量子涡旋变化过程.     

A comparison of the Jacobian-free Newton–Krylov method and the EVP model for solving the sea ice momentum equation with a viscous-plastic formulation: A serial algorithm study

Numerical convergence properties of a recently developed Jacobian-free Newton–Krylov (JFNK) solver are compared to the ones of the widely used EVP model when solving the sea ice momentum equation with a Viscous-Plastic (VP) formulation. To do so, very accurate reference solutions are produced with an independent Picard solver with an advective time step of 10 s and a tight nonlinear convergence criterion on 10, 20, 40, and 80-km grids. Approximate solutions with the JFNK and EVP solvers are obtained for advective time steps of 10, 20 and 30 min. Because of an artificial elastic term, the EVP model permits an explicit time-stepping scheme with a relatively large subcycling time step. The elastic waves excited during the subcycling are intended to damp out and almost entirely disappear such that the approximate solution should be close to the VP solution. Results show that residual elastic waves cause the EVP approximate solution to have notable differences with the reference solution and that these differences get more important as the grid is refined. Compared to the reference solution, additional shear lines and zones of strong convergence/divergence are seen in the EVP approximate solution. The approximate solution obtained with the JFNK solver is very close to the reference solution for all spatial resolutions tested.     

The energy conserving particle-in-cell method

A new particle-in-cell (PIC) method, that conserves energy exactly, is presented. The particle equations of motion and the Maxwell’s equations are differenced implicitly in time by the midpoint rule and solved concurrently by a Jacobian-free Newton Krylov (JFNK) solver. Several tests show that the finite grid instability is eliminated in energy conserving PIC simulations, and the method correctly describes the two-stream and Weibel instabilities, conserving exactly the total energy. The computational time of the energy conserving PIC method increases linearly with the number of particles, and it is rather insensitive to the number of grid points and time step. The kinetic enslavement technique can be effectively used to reduce the problem matrix size and the number of JFNK solver iterations.