Jacobian-free Newton Krylov Research Articles

Jacobian-free Newton-Krylov method for multilevel nonlocal thermal equilibrium radiative transfer problems

Context. The calculation of the emerging radiation from a model atmosphere requires knowledge of the emissivity and absorption coefficients, which are proportional to the atomic level population densities of the levels involved in each transition. Due to the intricate interdependence of the radiation field and the physical state of the atoms, iterative methods are required in order to calculate the atomic level population densities. A variety of different methods have been proposed to solve this problem, which is known as the nonlocal thermodynamical equilibrium (NLTE) problem. Aims. Our goal is to develop an efficient and rapidly converging method to solve the NLTE problem under the assumption of statistical equilibrium. In particular, we explore whether the Jacobian-Free Newton-Krylov (JFNK) method can be used. This method does not require an explicit construction of the Jacobian matrix because it estimates the new correction with the Krylov-subspace method. Methods. We implemented an NLTE radiative transfer code with overlapping bound-bound and bound-free transitions. This solved the statistical equilibrium equations using a JFNK method, assuming a depth-stratified plane-parallel atmosphere. As a reference, we also implemented the Rybicki & Hummer (1992) method based on linearization and operator splitting. Results. Our tests with the Fontenla, Avrett and Loeser C model atmosphere (FAL-C) and two different six-level Ca II and H I atoms show that the JFNK method can converge faster than our reference case by up to a factor 2. This number is evaluated in terms of the total number of evaluations of the formal solution of the radiative transfer equation for all frequencies and directions. This method can also reach a lower residual error compared to the reference case. Conclusions. The JFNK method we developed poses a new alternative to solving the NLTE problem. Because it is not based on operator splitting with a local approximate operator, it can improve the convergence of the NLTE problem in highly scattering cases. One major advantage of this method is that it is expected to allow for a direct implementation of more complex problems, such as overlapping transitions from different active atoms, charge conservation, or a more efficient treatment of partial redistribution, without having to explicitly linearize the equations.

An unconditionally stable scheme for the immersed boundary method with application in cardiac mechanics

The stability of the immersed boundary (IB) method is a challenge in simulating fluid–structure interaction problems, where time step constraints are significantly stricter than in pure fluid simulations. We propose a novel unconditionally stable scheme for the immersed boundary finite element (IBFE) method. The structure is handled implicitly and characterized by strain energy functions, rather than being modeled as fibers or membranes. Through energy estimate, we prove the unconditional stability of the fully discrete approximation in the absence of the convective term. In real simulations of cardiac mechanics problems, the time step is much larger, only limited by the Courant–Friedrichs–Lewy condition of the fluid. The novelty of this work lies in the combination of dual interpolation and distribution operators, the Jacobian-free Newton–Krylov method for solving nonlinear algebraic systems, and the semi-Lagrangian method for handling the convective term. To validate the effectiveness and accuracy of our approach, we present various benchmarks and conduct a quasi-static simulation of a three-dimensional real left ventricular model. We have shown that the numerical stability of our scheme is very robust even with much larger time step compared to conventional explicit IB methods. Our work paves the way for further works on efficient solvers of the IBFE method.

A Parallel Coloring Newton-Krylov Method for Multiphysics Coupling System in Nuclear Reactors

The Newton-Krylov method with the explicit Jacobian matrix is an efficient numerical method for solving the nuclear reactor nonlinear multiphysics coupling system. Compared with the Jacobian-free Newton-Krylov (JFNK) method, it has a better preconditioner matrix (the Jacobian matrix itself) and can achieve a more stable and faster convergence. How to compute the Jacobian matrix efficiently is a key issue for this method. The graph coloring algorithm is an essential technique and has been used to reduce the Jacobian computational burden by exploiting its sparsity. The fewer the coloring numbers in the Jacobian, the less the Jacobian computational cost will be. Besides, when computing the Jacobian in a distributed memory parallel environment, the parallel graph coloring algorithms are required because the Jacobian is distributed among processors. Currently, a popular parallel graph coloring algorithm has been used to color the Jacobian. However, this parallel graph coloring algorithm shows poor scalability in parallel. The coloring numbers will increase with the processors, resulting in poor Jacobian computational efficiency. In this paper, a more efficient parallel graph coloring method is proposed that aims to reduce the coloring numbers and improve Jacobian computation efficiency in parallel. The main feature of the new method is that the coloring numbers decrease with the increasing number of processors. A neutronics/thermal-hydraulic coupling problem arising from the simplified high-temperature gas coolant model is utilized to assess the performance of the newly proposed method. The results show that (1) the parallel coloring number is reduced significantly, (2) the Jacobian computed by the new method is completely correct and excellent parallel scalability is achieved, and (3) the parallel coloring Newton-Krylov method with explicit Jacobian is more efficient and more stable than the parallel JFNK due to a better preconditioner.

An Efficient and Robust ILU(k) Preconditioner for Steady-State Neutron Diffusion Problem Based on MOOSE

Jacobian-free Newton Krylov (JFNK) is an attractive method to solve nonlinear equations in the nuclear engineering community, and has been successfully applied to steady-state neutron diffusion k-eigenvalue problems and multi-physics coupling problems. Preconditioning technique plays an important role in the JFNK algorithm, significantly affecting its computational efficiency. The key point is how to automatically construct a high-quality preconditioning matrix that can improve the convergence rate and perform the preconditioning matrix factorization efficiently and robustly. A reordering-based ILU(k) preconditioner is proposed to achieve the above objectives. In detail, the finite difference technique combined with the coloring algorithm is utilized to automatically construct a preconditioning matrix with low computational cost. Furthermore, the reordering algorithm is employed for the ILU(k) to reduce the additional non-zero elements and pursue robust computational performance. A 2D LRA neutron steady-state benchmark problem is used to evaluate the performance of the proposed preconditioning technique, and a steady-state neutron diffusion k-eigenvalue problem with thermal-hydraulic feedback is also utilized as a supplement. The results show that coloring algorithms can automatically and efficiently construct the preconditioning matrix. The computational efficiency of the FDP with coloring could be about 60 times higher than that of the preconditioner without the coloring algorithm. The reordering-based ILU(k) preconditioner shows excellent robustness, avoiding the effect of the fill-in level k choice in incomplete LU factorization. Moreover, its performances under different fill-in levels are comparable to the optimal computational cost with natural ordering.

On the Use of the Jacobian-Free Newton Krylov Method to Generate One-Group Discontinuity and Super Homogenization Factors for Full-Core Neutron Diffusion Simulations

Coupled Monte Carlo (MC) and thermal-hydraulic analysis is valuable as a design or reference tool but can be slow, especially when implemented in a Picard iteration. Previous work has developed a novel prediction block to achieve convergence with fewer MC simulations. The prediction works in two stages: (1) a surrogate-like model predicts macroscopic cross sections on the fly and (2) a reduced-order neutronic model predicts the flux response to the updated cross sections. The main challenge with the prediction block is that the reduced-order neutronic model cannot reproduce the spatial flux distribution with high fidelity. This paper investigates the well-established Jacobian-free Newton Krylov (JFNK) method to preserve equivalency between a homogeneous (nodal diffusion) solution and a high-fidelity transport (MC) solution. Instead of performing multiple computationally consuming MC simulations, the nonlinear iterative approach iterates on correction parameters, e.g., assembly discontinuity factors (ADFs) or super homogenization (SPH) factors, using unexpensive nodal solutions. The JFNK approach does not require additional overhead from the MC solver to generate flux tallies. Further, the approach iterates on diffusion solutions produced directly from a desired code, thus ensuring that the parameters are compatible with that code. The approach is applied to correct a nodal diffusion solution for a realistic three-dimensional pressurized water reactor core. The results obtained in the paper show that the method is very successful in reproducing the heterogeneous solution (up to 2.5% difference in assembly flux for SPH and 0.3% for ADFs) without needing to modify the source code of the nodal diffusion solver. In addition, the results show that ADFs yield the best agreement and are also stable (i.e., weakly varying) when thermal-hydraulic fields are perturbed.

An Innovational Jacobian-Split Newton-Krylov Method Combining the Advantages of the Jacobian-Free Newton-Krylov Method and the Finite Difference Jacobian-Based Newton-Krylov Method

The Jacobian-free Newton-Krylov (JFNK) method is a widely used and flexible numerical method for solving the neutronic/thermal-hydraulic coupling system. The main property of JFNK is that the Jacobian-vector product is evaluated approximately by finite difference, avoiding the forming and storage of Jacobian explicitly. However, the lack of an efficient preconditioner is a major bottleneck for the JFNK method, leading to poor convergence. The finite difference Jacobian-based Newton-Krylov (DJNK) method is another advanced numerical method, in which the Jacobian matrix is formed and stored explicitly. The DJNK method can provide a better preconditioner for Krylov iteration than JFNK. However, how to compute the Jacobian matrix efficiently and automatically is a key issue for the DJNK method. By fully utilizing the sparsity of the Jacobian matrix and graph coloring algorithm, the Jacobian can be computed efficiently. Unfortunately, when there are dense rows/blocks, a huge computational burden will emerge due to the lack of sparsity, resulting in the extremely poor efficiency of Jacobian computation. In this work, a Jacobian-split Newton-Krylov (JSNK) method is proposed to resolve the dense row/block problem by combining the advantages of JFNK and DJNK. The main feature of the JSNK method is to split the Jacobian matrix into sparse and dense parts. The sparse part of the Jacobian matrix is explicitly constructed using the graph coloring algorithm while for the dense part, the Jacobian-vector product is approximated by finite difference. The computational complexity of the JSNK method is analyzed and compared to the JFNK method and the DJNK method from theoretical and experimental aspects and under different meshes. A simplified two-dimensional (2-D) high-temperature gas-cooled reactor (HTR) model and a simplified 2-D pressurized water reactor model are utilized to demonstrate the superiority of the JSNK method. The numerical results show that the JSNK method successfully resolved the dense rows/blocks. More importantly, its efficiency significantly outperforms the JFNK method and the DJNK method.

A GPU-Accelerated Method for 3D Nonlinear Kelvin Ship Wake Patterns Simulation

The study of ship waves is important for ship detection, coastal erosion and wave drag. This paper proposed a highly paralleled numerical computation method for efficiently simulating three-dimensional nonlinear kelvin waves. First, a numerical model for nonlinear ship waves is established based on potential flow theory, the Jacobian-free Newton–Krylov (JFNK) method and the boundary integral method. To reduce the amount of data stored in the JFNK method and improve the computational efficiency, a banded preconditioner method is then developed by formulating the optimal bandwidth selection rule. After that, a Graphics Process Unit (GPU)-based parallel computing framework is designed, and we used the Compute Unified Device Architecture (CUDA) language to develop a GPU solution. Finally, numerical simulations of 3D nonlinear ship waves under multiple scales are performed by using the GPU and CPU solvers. Simulation results show that the proposed GPU solver is more efficient than the CPU solver with the same accuracy. More than 66% GPU memory can be saved, and the computational speed can be accelerated up to 20 times. Hence, the computation time for Kelvin ship waves simulation can be significantly reduced by applying the GPU parallel numerical scheme, which lays a solid foundation for practical ocean engineering.

Development of a Fully-Implicit Second-Order system Thermal-Hydraulics analysis code for reactor modeling and simulations

There has been continuous advancement in numerical techniques and software engineering in the field of system thermal-hydraulics over the past decade. The current state-of-the-art involves the use of fully-implicit high-resolution schemes in conjunction with the Jacobian-Free Newton-Krylov (JFNK) method for both single-phase and two-phase flows. However, the application of these advanced schemes in system thermal-hydraulics codes is not a common practice. Given the opportunity and the need to develop a new modern system thermal–hydraulic code from scratch, there is no doubt that these recent advancements should be leveraged. In this work, we introduce a new modern object-oriented system thermal-hydraulics code named RETA. RETA is characterized by several key features, including: second-order temporal and spatial discretization schemes for both incompressible and compressible flows, as well as single-phase and two-phase flows; fully-implicit solution schemes utilizing both the Newton and PJFNK methods; and an object-oriented design of major fluid components and physical models, which allows for easy extension. A series of verification and demonstration studies are conducted to verify the implementation, demonstrate the accuracy improvement, and evaluate the performance of the new code. It is concluded that results from the second-order scheme are generally more reliable. Without the concern of a code stability issue, the second-order scheme should be the preferred and default choice for a code user or an analyst.

A hybrid numerical method for non-linear transient heat conduction problems with temperature-dependent thermal conductivity

This paper introduces a hybrid numerical technique aimed at effectively addressing two-dimensional (2D) non-linear transient heat conduction problems, featuring temperature-dependent thermal conductivity. This scheme involves integrating the Krylov deferred correction (KDC) method in the temporal discretization and the generalized finite difference method (GFDM) in the spatial discretization. The core of the KDC method introduces a new unknown variable in the form of the first-order time derivative of temperature, leading to a non-linear equation after temporal discretization. Subsequently, the corresponding non-linear equation is solved in the spatial domain using the GFDM, supported by the Jacobian-free Newton–Krylov (JFNK) solver and fourth-order Taylor series expansion. The accuracy and stability of the hybrid approach are verified through two numerical experiments, demonstrating the strong performance of the present algorithm known as the KDC-GFDM for the simulations of the interested problems in long-time intervals.

Transient Simulation and Parameter Sensitivity Analysis of Godiva Experiment Based on MOOSE Platform

The fast-neutron burst reactor is a chain reactor that can operate in a prompt critical state. In order to ensure the operational safety of the fast-neutron-pulse reactor and prevent the supercritical pulse from causing physical damage to the material, it is necessary to simulate and analyze the pulse operating conditions of the fast-neutron-pulse reactor. Godiva-I is a spherical assembly of highly enriched uranium metal made during the 1950s. A prompt-critical transient in such a nuclear system impels a quick power excursion, which will cause a temperature rise and a subsequent reactivity reduction because of the metal sphere’s expansion. The overall transient lasts for a few fractions of a millisecond. Based on the point kinetics and Monte Carlo method, the temporal and spatial characteristics of transient input power were calculated, the difference of the average reactivity temperature coefficient between uniform density and non-uniform density was compared, and the transient power distribution condition was loaded into the thermal–mechanics calculation of the MOOSE platform; thus, the pulse process of Godiva-I with different initial reactivity periods was simulated. The JFNK (Jacobian–Free–Newton–Krylov) direct method and multi-app indirect method were used to analyze the transient response of the pulse dynamic process using the heat conduction module and tenor mechanics module, respectively. After considering the influence of the inertia effect and wall-reflected neutrons, the simulation results were much closer to the experimental values. Based on the stochastic tools module, the uncertainty propagation and sensitivity analysis of the Godiva-I model were carried out, the uncertainty of external surface displacement of Godiva under input disturbance of material properties and heat source amplitude factor was obtained, and the sensitivity of different input parameters to output parameters was quantified. The research results can lay a technical foundation for the thermal–mechanics coupling analysis and uncertainty quantification of the metal fast reactor.

An implicit particle code with exact energy and charge conservation for electromagnetic studies of dense plasmas

A collisional particle code based on implicit energy- and charge-conserving methods is presented. A modified version of the particle-suppressed Jacobian-Free Newton-Krylov method that can enhance the solver efficiency is introduced. Mathematically, it is shown that this new approach can be viewed as a fixed-point iteration method for the particle positions. The model can exactly conserve global energy and local charge and can efficiently use time steps larger than the plasma period. The algorithm's ability to simulate dense plasmas accurately and efficiently is quantified by simulating the dynamic compression of a plasma slab via a magnetic piston in 1D planar geometry.

A Jacobian-Free Newton–Krylov Method to Solve Tumor Growth Problems with Effective Preconditioning Strategies

A Jacobian-free Newton–Krylov (JFNK) method with effective preconditioning strategies is introduced to solve a diffusion-based tumor growth model, also known as the Fisher–Kolmogorov partial differential equation (PDE). The time discretization of the PDE is based on the backward Euler and the Crank–Nicolson methods. Second-order centered finite differencing is used for the spatial derivatives. We introduce two physics-based preconditioners associated with the first- and second-order temporal discretizations. The theoretical time and spatial accuracies of the numerical scheme are verified through convergence tables and graphs that correspond to different computational settings. We present efficiency studies with and without using the preconditioners. Our numerical findings indicate the excellent performance of the newly proposed preconditioning strategies. In other words, when we turn the preconditioners on, the average number of GMRES and the Newton iterations are significantly reduced.

A Modified JFNK for Solving the HTR Steady State Secondary Circuit Problem

A nuclear power plant is a complex coupling system, which features multi-physics coupling between reactor physics and thermal-hydraulics in the reactor core, as well as the multi-circuit coupling between the primary circuit and the secondary circuit by the shared steam generator (SG). Especially in the pebble-bed modular HTR nuclear power plant, different nuclear steam supply modules are further coupled together through the shared main steam pipes and the related equipment in the secondary circuit, since the special configuration of multiple reactor modules connects to a steam turbine. The JFNK (Jacobian-Free Newton–Krylov) method provides a promising coupling framework to solve the whole HTR nuclear power plant problem, due to its excellent convergence rate and strong robustness. In this work, the JFNK method was modified and applied to the steady-state calculation of the HTR secondary circuit, which plays an important role in simultaneous solutions for the whole HTR nuclear power plant. The main components in the secondary circuit included SG, steam turbine, condenser, feed pump, high/low-pressure heat exchanger, deaerator, as well as the extraction steam from the steam turbine. The results showed that the JFNK method can effectively solve the steady state issue of the HTR secondary circuit. Moreover, the JFNK method could converge well within a wide range of initial values, indicating its strong robustness.

Jacobian-free Newton–Krylov method for the simulation of non-thermal plasma discharges with high-order time integration and physics-based preconditioning

A preconditioning framework for the numerical simulation of non-thermal streamer discharges is developed using the Jacobian-free Newton-Krylov (JFNK) method. A reduced plasma fluid model is considered, consisting of electrons, one positive ion, one negative ion, and the electrostatic potential. The plasma kinetics model includes ionization, electron-ion recombination, electron attachment, electron detachment, and ion-ion recombination. The governing equations are made dimensionless, discretized in space with finite differences, and integrated in time with a fully implicit method based on high-order backward differentiation formulas. The preconditioning framework is based on a linearized form of the governing equations and physics-based operator splitting. The efficiency of the preconditioning strategy is assessed through two test cases: streamer propagation between parallel plates and an axisymmetric pin-to-pin discharge. The fully implicit approach overcomes traditional restrictions in the time step size due to processes such as electron drift, electron diffusion, and dielectric relaxation. Excellent performance is observed through relevant statistics of the JFNK solver, although the number of linear iterations increases for the pin-to-pin discharge when nonlinear numerical boundary conditions are imposed at the electrodes. Performance studies show scalability with O(100-1000) processors for O(10M) unknowns with ample room for optimization.

Simultaneous Solution of Helical Coiled Once-Through Steam Generator with High-Speed Water Property Library

Efficient simulation of the helical coiled once-through steam generator (H-OTSG) is crucial in the design and safety analysis of the high-temperature gas-cooled reactor (HTGR). The physical property and phase transformation of water in the steam generator brings great challenges during simulation. The water properties calculation routine occupies a large part of the computational time in the steam generator solution process. Thus, a thermohydraulic property library is developed based on the IAPWS-IF97 formulation in this work to reduce the computational cost. Here the formulation adopts the backward equation method to avoid iterations in thermodynamic property calculation. Moreover, two Newton-method-based simultaneous solutions are implemented as implicitly nonlinear solvers, including Jacobian-Free Newton–Krylov (JFNK) and Newton–Krylov (NK) methods, due to its excellent computational performance. These simultaneous solution algorithms are combined with the developed water property library to simulate the H-OTSG efficiently. The numerical analysis is performed based on the transient and steady-state cases of the HTR-10 steam generator. Successful simulations of HTR-10 steam generator cases demonstrate the capability of the newly developed method.

Parallel Jacobian-free Newton Krylov discrete ordinates method for pin-by-pin neutron transport models

A parallel Jacobian-Free Newton Krylov discrete ordinates method (comePSn_JFNK) is proposed to solve the multi-dimensional multi-group pin-by-pin neutron transport models, which makes full use of the good efficiency and parallel performance of the JFNK framework and the high accuracy of the Sn method for the large-scale models. In this paper, the k-eigenvalue and the scalar fluxes (rather than the angular fluxes) are chosen as the global solution variables of the parallel JFNK method, and the corresponding residual functions are evaluated by the Koch–Baker–Alcouffe (KBA) algorithm with the spatial domain decomposition in the parallel Sn framework. Unlike the original Sn iterative strategy, only a “flattened” power iterative process which includes a single outer iteration without nested inner iterations is required for the JFNK strategy. Finally, the comePSn_JFNK code is developed in C++ language and, the numerical solutions of the 2-D/3-D KAIST-3A benchmark problems and the 2-D/3-D full-core MOX/UOX pin-by-pin models with different control rod distribution show that comePSn_JFNK method can obtain significant efficiency advantage compared with the original power iteration method (comePSn) for the parallel simulation of the large-scale complicated pin-by-pin models.

Operator split, Picard iteration and JFNK methods based on nonlinear CMFD for transient full core models in the coupling multiphysics environment

Operator Split (OS), Picard iteration and Jacobian-free Newton Krylov (JFNK) methods based on nonlinear coarse mesh finite difference (CMFD) with nodal expansion methods (NEM) are respectively introduced to solve the transient full core coupled models in the COupling Multiphysics Environment (COME). In the COME, in addition to the traditional OS and Picard coupled methods, we develop two different JFNK-based coupled methods with physics and algebraic-based hybrid preconditioners at each time step: OS_JFNK and JFNK coupled methods. Specifically, the efficient JFNK method is applied to solve CMFD discrete models of only neutronics in the OS framework for OS_JFNK coupled strategies or whole Neutronics-Thermal Hydraulic (N-TH) coupled models for JFNK coupled methods. Then nonlinear corrective coupling coefficients are updated by the two-node NEM every few Newton steps at each time step. Six cases of NEACRP 3D core transient benchmarks are analyzed and numerical solutions of OS, OS_JFNK, Picard and JFNK methods in the COME generally agree well with other published solutions. JFNK and Picard coupled methods can track the reference solutions better than OS and OS_JFNK coupled methods due to multiple iterations or simultaneous solutions between neutronics and TH models in the tight coupled form. Furthermore, OS_JFNK or JFNK methods can obtain higher computational efficiency than OS or Picard methods with or without the fission source extrapolation acceleration, respectively, which indicates the potential of the developed COME using different coupled methods for the transient full core multiphysics coupled problems.

A modified JFNK with line search method for solving k-eigenvalue neutronics problems with thermal-hydraulics feedback

The k-eigenvalue neutronics/thermal-hydraulics coupling calculation is a key issue for reactor design and analysis. Jacobian-free Newton-Krylov (JFNK) method, featured with super-linear convergence rate and high efficiency, has been attracting more and more attention to solve the multi-physics coupling problem. However, it may converge to the high-order eigenmode because of the multiple solutions nature of the k-eigenvalue form of multi-physics coupling issue. Based on our previous work, a modified JFNK with a line search method is proposed in this work, which can find the fundamental eigenmode together with thermal-hydraulics feedback in a wide range of initial values. In detail, the existing modified JFNK method is combined with the line search strategy, so that the intermediate iterative solution can avoid a sudden divergence and be adjusted into a convergence basin smoothly. Two simplified 2-D homogeneous reactor models, a PWR model, and an HTR model, are utilized to evaluate the performance of the newly proposed JFNK method. The results show that the performance of this proposed JFNK is more robust than the existing JFNK-based methods.

Development, Verification, and Validation of an Advanced Systems Code KP-SAM for Kairos Power Fluoride Salt–Cooled High-Temperature Reactor (KP-FHR)

To meet the Kairos Power (KP) Fluoride Salt-Cooled High-Temperature Reactor (FHR) (KP-FHR) development and commercialization schedules, the System Analysis Module (SAM), which is an advanced systems code for Generation IV liquid-cooled reactors developed at Argonne National Laboratory (ANL), has been selected as the basis for the development of the KP-FHR systems code KP-SAM. This allows for an accelerated joint development effort between the KP and ANL teams. This paper presents a general overview of the KP-SAM development process, its current status, completed verification, and ongoing validation efforts. KP-SAM development follows the U.S. Nuclear Regulatory Commission Evaluation Model Development and Assessment Process framework. SAM is a high-order fully implicit transient systems code written in C++. The SAM software design, major physical models, and Jacobian Free Newton Krylov–based numerical methods are briefly discussed. KP-SAM has matured enough to be used for the unvalidated demonstration safety analysis for the low-power KP-FHR test reactor (Hermes) as part of Preliminary Safety Analysis Report work. By following the guidance of an internal KP-FHR thermal fluid Phenomena Identification and Ranking Table report, some of the most important separate-effects-test validations were completed for the first iteration. A scaled integral-effects test is under detailed design and will be built in 2022 to provide key data to validate KP-SAM for licensing safety analysis.

Jacobian-free Newton Krylov coarse mesh finite difference algorithm based on high-order nodal expansion method for three-dimensional nuclear reactor pin-by-pin multiphysics coupled models

The nuclear reactor core is a large-scale, complicated and tight-coupled nonlinear multiphysics coupled system including neutron transport, heat conduction of nuclear fuel pins, coolant flow, heat transfer and so on. To meet the demands of the advanced nuclear reactor analysis and design, there is an urgent need to reduce the computational costs and improve the convergence rate for the three-dimensional (3D) nuclear reactor core multiphysics coupled models, especially for a high-fidelity pin-by-pin (at the level of fuel pin by fuel pin) full core simulation. In this work, we develop CNJ, an efficient Jacobian free Newton Krylov (JFNK) coarse mesh finite difference (CMFD) algorithm based on the nodal expansion method (NEM) to simultaneously solve the complicated pin-by-pin neutronics-thermal hydraulic (N-TH) coupled models. The high-order NEM can improve the numerical accuracy of the CMFD method on a coarse mesh and the JFNK method can ensure the rapid convergence and high efficiency on large-scale and nonlinear coupled discrete systems. By combining the CMFD, NEM and JFNK methods and making full use of their respective advantages, the CNJ algorithm can obtain high accuracy and efficiency even on a coarse mesh to greatly reduce the number of solution variables and the computational cost of the 3D coupled models. Finally, two representative and complicated 3D pin-by-pin N-TH coupled models are analyzed to evaluate the numerical accuracy and efficiency advantage of CNJ in detailed.