Journal of Computational Physics最新文献

{"title":"A denoising multiscale particle method for nonequilibrium flow simulations","authors":"Hao Yang,&nbsp;Kaikai Feng,&nbsp;Ziqi Cui,&nbsp;Jun Zhang","doi":"10.1016/j.jcp.2025.114096","DOIUrl":"10.1016/j.jcp.2025.114096","url":null,"abstract":"<div><div>The direct simulation Monte Carlo (DSMC) method is promising for simulating rarefied nonequilibrium flows, but its inherent limitations on spatiotemporal resolution and statistical noise hinder applications in near-continuum and low-signal regimes. This work proposes a denoising multiscale particle (DMP) method for efficient particle-based simulations. The DMP method employs a Bhatnagar–Gross–Krook (BGK) relaxation process to simplify binary collisions. Its denoising strategy, inspired by the information preservation method, incorporates low-noise collective information into each simulation particle. This collective information evolves anchored on the information-augmented Shakhov BGK equation, which provides a theoretical foundation for analyzing transport and denoising properties. Macroscopic flow quantities are obtained by statistically averaging this collective information, resulting in a signal-to-noise ratio independent of signal magnitude in low- to moderate-signal regimes, while proportional to the local rarefaction level. An operator splitting scheme is utilized to decouple particle movement and relaxation, enabling a simple and efficient implementation but introducing numerical dissipation in the Navier–Stokes limit. In DMP, this numerical dissipation error is quantified and mitigated through incorporating anti-dissipation target distribution and information compensation terms, endowing the method with multiscale simulation capability. Consequently, the DMP method allows for coarser spatiotemporal resolutions and requires fewer sampling particles than DSMC. Various numerical experiments validate the accuracy and demonstrate the efficiency of the DMP method in low- to moderate-rarefaction and signal regimes.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114096"},"PeriodicalIF":3.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An efficient multidomain RBF mesh deformation method based on MPI/OpenMP hybrid parallel interpolation","authors":"Zhenyu Hu,&nbsp;Yu Yuan,&nbsp;Dapeng Xiong,&nbsp;Chenglong Wang,&nbsp;Mingbo Sun,&nbsp;Yongchao Sun","doi":"10.1016/j.jcp.2025.114113","DOIUrl":"10.1016/j.jcp.2025.114113","url":null,"abstract":"<div><div>Radial basis function (RBF) interpolation has been prevalent in mesh deformation schemes due to its great quality-preserving ability and generality. However, the cost time scales as <span><math><mrow><mi>O</mi><mo>(</mo><msup><mrow><msub><mi>N</mi><mi>s</mi></msub></mrow><mn>3</mn></msup><mo>)</mo></mrow></math></span>, where <span><math><msub><mi>N</mi><mi>s</mi></msub></math></span> is the number of surface nodes, which makes full RBF interpolation prohibitively expensive to implement for large mesh. The key improvement is the application of efficient reduced-data methods. But the greedy-type reduced-data method remains expensive when applied to large-scale meshes, requiring iterative linear system solutions and interpolation error calculations to generate the reduced dataset. Furthermore, a supplementary surface correction procedure must be implemented to ensure exact surface shape. In this paper, a novel multidomain method is proposed that stochastically splits the surface nodes into <span><math><mi>n</mi></math></span> small subsets and a small sub-RBF interpolant is constructed on each subset. The mesh deformation is computed by the weight of sub-RBF interpolations. Since the above processes are independent, this method is perfectly parallel. The computational complexity analysis reveals that this method reduces the solution cost to <span><math><mrow><mi>O</mi><mo>(</mo><msup><mrow><msub><mi>N</mi><mi>s</mi></msub></mrow><mn>3</mn></msup><mo>/</mo><msup><mi>n</mi><mn>2</mn></msup><mo>)</mo></mrow></math></span> for a serial algorithm, and this method can be faster than the multiscale method Kedward et al.(2017) in all stages. By appropriately selecting the weighting coefficients, the exact surface shape is naturally preserved and the surface correction issue is eliminated. Further enhancements are achieved by dividing the volume into near-surface, intermediate, far-surface and stationary domains based on their distances from the surface. These domains can adopt distinct weighting schemes and utilize varying numbers of radial centers. The efficiency and accuracy of this method are analyzed in detail using two-dimensional (2D) airfoils, a three-dimensional (3D) scramjet combustor and a 3D hypersonic vehicle examples. In comparison with the conventional greedy method and the contemporary multiscale method, this method gains higher efficiency and comparable mesh quality.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114113"},"PeriodicalIF":3.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minimizing information loss reduces spiking neuronal networks to differential equations","authors":"Jie Chang ,&nbsp;Zhuoran Li ,&nbsp;Zhongyi Wang ,&nbsp;Louis Tao ,&nbsp;Zhuo-Cheng Xiao","doi":"10.1016/j.jcp.2025.114117","DOIUrl":"10.1016/j.jcp.2025.114117","url":null,"abstract":"<div><div>Spiking neuronal networks (SNNs) are widely used in computational neuroscience, from biologically realistic modeling of local cortical networks to phenomenological modeling of the whole brain. Despite their prevalence, a systematic mathematical theory for finite-sized SNNs remains elusive, even for idealized homogeneous networks. The primary challenges are twofold: 1) the rich, parameter-sensitive SNN dynamics, and 2) the singularity and irreversibility of spikes. These challenges pose significant difficulties when relating SNNs to systems of differential equations, leading previous studies to impose additional assumptions or to focus on individual dynamic regimes. In this study, we introduce a Markov approximation of homogeneous SNN dynamics to minimize information loss when translating SNNs into ordinary differential equations. Our only assumption for the Markov approximation is the fast self-decorrelation of synaptic conductances. The system of ordinary differential equations derived from the Markov model effectively captures high-frequency partial synchrony and the metastability of finite-neuron networks produced by interacting excitatory and inhibitory populations. Besides accurately predicting dynamical statistics, such as firing rates, our theory also quantitatively captures the geometry of attractors and bifurcation structures of SNNs. Thus, our work provides a comprehensive mathematical framework that can systematically map parameters of single-neuron physiology, network coupling, and external stimuli to homogeneous SNN dynamics.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114117"},"PeriodicalIF":3.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finite difference alternative WENO schemes with Riemann invariant-based local characteristic decompositions for compressible Euler equations","authors":"Yue Wu,&nbsp;Chi-Wang Shu","doi":"10.1016/j.jcp.2025.114104","DOIUrl":"10.1016/j.jcp.2025.114104","url":null,"abstract":"<div><div>The weighted essentially non-oscillatory (WENO) schemes are widely used for hyperbolic conservation laws due to the ability to resolve discontinuities and maintain high-order accuracy in smooth regions at the same time. For hyperbolic systems, the WENO procedure is usually performed on local characteristic variables that are obtained by local characteristic decompositions to avoid oscillation near shocks. However, such decompositions are often computationally expensive. In this paper, we study a Riemann invariant-based local characteristic decomposition for the compressible Euler equations that reduces the cost. We apply the WENO procedure to the local characteristic fields of the Riemann invariants, where the eigenmatrix is sparse and thus the computational cost can be reduced. It is difficult to obtain the cell averages of Riemann invariants from those of the conserved variables due to the nonlinear relation between them, so we only focus on the finite difference alternative WENO versions. The efficiency and non-oscillatory property of the proposed schemes are well demonstrated by our numerical results.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114104"},"PeriodicalIF":3.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A coupled PFEM-DEM model for fluid-granular flows with free surface dynamics applied to landslides","authors":"Thomas Leyssens,&nbsp;Michel Henry,&nbsp;Jonathan Lambrechts,&nbsp;Vincent Legat,&nbsp;Jean-François Remacle","doi":"10.1016/j.jcp.2025.114082","DOIUrl":"10.1016/j.jcp.2025.114082","url":null,"abstract":"<div><div>Free surface and granular fluid mechanics problems combine the challenges of fluid dynamics with aspects of granular behaviour. This type of problem is particularly relevant in contexts such as the flow of sediments in rivers, the movement of granular soils in reservoirs, or the interactions between a fluid and granular materials in industrial processes such as silos. The numerical simulation of these phenomena is challenging because the solution depends not only on the multiple phases that strongly interact with each other, but also on the need to describe the geometric evolution of the different interfaces. This paper presents an approach to the simulation of fluid-granular phenomena involving strongly deforming free surfaces. The Discrete Element Method (DEM) is combined with the Particle Finite Element Method (PFEM) and the fluid–grain interface is treated by a two-way coupling between the two phases. The fluid-air interface is solved by a free surface model. The geometric and topological variations are therefore naturally provided by the full Lagrangian description of all phases. The approach is validated on benchmark test cases such as two-phase dam failures and then applied to a historical landslide event.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114082"},"PeriodicalIF":3.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A micro-macro decomposition-based asymptotic-preserving random feature method for multiscale radiative transfer equations","authors":"Jingrun Chen ,&nbsp;Zheng Ma ,&nbsp;Keke Wu","doi":"10.1016/j.jcp.2025.114103","DOIUrl":"10.1016/j.jcp.2025.114103","url":null,"abstract":"<div><div>This paper introduces the Asymptotic-Preserving Random Feature Method (APRFM) for the efficient resolution of multiscale radiative transfer equations. The APRFM effectively addresses the challenges posed by stiffness and multiscale characteristics inherent in radiative transfer equations through the application of a micro-macro decomposition strategy. This approach decomposes the distribution function into equilibrium and non-equilibrium components, allowing for the approximation of both parts through the random feature method (RFM) within a least squares minimization framework. The proposed method exhibits remarkable robustness across different scales and achieves high accuracy with fewer degrees of freedom and collocation points than the vanilla RFM. Additionally, compared to the deep neural network-based method, our approach offers significant advantages in terms of parameter efficiency and computational speed. These benefits have been substantiated through numerous numerical experiments conducted on both one- and two-dimensional problems.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114103"},"PeriodicalIF":3.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive ray-tracing method for eikonal equations on spheres using STVDRK integrators and SENO interpolations","authors":"Wai Ming Chau,&nbsp;Shingyu Leung","doi":"10.1016/j.jcp.2025.114100","DOIUrl":"10.1016/j.jcp.2025.114100","url":null,"abstract":"<div><div>We develop an efficient adaptive framework for obtaining high-order multivalued solutions to wavefront propagation problems on a unit sphere, as described by the surface eikonal equations. A key development in our approach is the reformulation of the conventional ray-tracing system, which typically tracks solutions in <span><math><mrow><msup><mi>S</mi><mn>2</mn></msup><mo>×</mo><msup><mi>R</mi><mn>3</mn></msup></mrow></math></span>, into a system of differential equations where the phase space is <span><math><mrow><msup><mi>S</mi><mn>2</mn></msup><mo>×</mo><msup><mi>S</mi><mn>2</mn></msup></mrow></math></span>. Central to our methodology are the SLERP Total Variation Diminishing Runge-Kutta (STVDRK) methods and Spherical Essentially Non-Oscillatory (SENO) interpolation techniques. These numerical innovations provide a robust adaptive strategy for modeling the evolution of the wavefront without relying on any projection steps. By effectively maintaining accuracy and stability while evolving solutions on the unit sphere, our framework significantly enhances the representation of evolving curves and improves the overall robustness of the numerical solutions. This adaptive approach significantly surpasses traditional methods, providing a way for more accurate modeling of wavefront propagation in complex geometries.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114100"},"PeriodicalIF":3.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An explicit, energy-conserving particle-in-cell scheme","authors":"Lee F. Ricketson ,&nbsp;Jingwei Hu","doi":"10.1016/j.jcp.2025.114098","DOIUrl":"10.1016/j.jcp.2025.114098","url":null,"abstract":"<div><div>We present an explicit temporal discretization of particle-in-cell schemes for the non-relativistic Vlasov equation that results in exact energy conservation when combined with an appropriate spatial discretization. The scheme is inspired by a simple, second-order explicit scheme that conserves energy exactly in the Eulerian context. We show that direct translation to particle-in-cell does not result in strict conservation, but derive a simple correction based on an analytically solvable optimization problem that recovers conservation. While this optimization problem is not guaranteed to have a real solution for every particle, we provide a correction that makes imaginary values extremely rare and still admits <span><math><mrow><mi>O</mi><mo>(</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>12</mn></mrow></msup><mo>)</mo></mrow></math></span> fractional errors in energy for practical simulation parameters. We present the scheme in both electrostatic – where we use the Ampère formulation – and electromagnetic contexts. With an electromagnetic field solve, the field update is most naturally linearly implicit, but the more computationally intensive particle update remains fully explicit. We also show how the scheme can be extended to use the fully explicit leapfrog and pseudospectral analytic time-domain (PSATD) field solvers. The scheme is tested on standard kinetic plasma problems, confirming its conservation properties.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114098"},"PeriodicalIF":3.8,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144123816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fully implicit low Mach number algorithm for flows with heat transfer","authors":"Ilker Topcuoglu ,&nbsp;Xiang Yang ,&nbsp;Robert Kunz","doi":"10.1016/j.jcp.2025.114091","DOIUrl":"10.1016/j.jcp.2025.114091","url":null,"abstract":"<div><div>A class of implicit algorithms are presented to solve the momentum, continuity and enthalpy equations simultaneously for low Mach number flows that are driven by heat transfer and buoyancy. An exact Newton linearization is pursued, and quadratic convergence is obtained for buoyantly unstable heated perfect gas flow, with and without system acceleration. The novelty of this work is an orders of magnitude acceleration in convergence rate compared to fully segregated and partially segregated schemes that invoke Picard linearization, which exhibit linear convergence characteristics. Elements of an algebraic multigrid strategy are developed to solve the block coupled system of equations that arise. Intergrid transfer operations are based on the additive correction method, and coarse grid agglomeration is performed with anisotropic coarsening. An Incomplete LU factorization is used for smoothing error on different grid levels. A variety of low Mach number flow problems with heat transfer are studied to demonstrate convergence performance of the scheme. Quadratic convergence and significant CPU time improvements are observed for all test cases.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114091"},"PeriodicalIF":3.8,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adjoint shape optimization from the continuum to free-molecular gas flows","authors":"Ruifeng Yuan,&nbsp;Lei Wu","doi":"10.1016/j.jcp.2025.114102","DOIUrl":"10.1016/j.jcp.2025.114102","url":null,"abstract":"<div><div>An adjoint-based shape optimization method for solid bodies subjected to both rarefied and continuum gas flows is proposed. The gas-kinetic BGK equation with the diffuse-reflection boundary condition is used to describe the multiscale gas flows. In the vicinity of the gas-solid interface, a body-fitted mesh is utilized, and the sensitivity with respect to the boundary geometry is analyzed through a combined continuous and discrete adjoint methods. The primal and adjoint governing equations are resolved using efficient multiscale numerical schemes, ensuring the precision of the sensitivity analysis in all flow regimes. The sensitivity data is subsequently integrated into a quasi-Newton optimization algorithm to facilitate rapid convergence towards the optimal solution. Numerical experiments reveal that the discretization of the molecular velocity space can induce sensitivity oscillations; however, these can be effectively eliminated by employing appropriate parameterization of the boundary geometry. In optimizing 2D airfoils for drag reduction under varying degrees of gas rarefaction, our method achieves the optimal solution in just a dozen optimization iterations and within a time frame of 5 to 20 minutes (utilizing parallel computation with 40 to 160 cores), thereby underscoring its exceptional performance and efficiency.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"537 ","pages":"Article 114102"},"PeriodicalIF":3.8,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}