Communications in Computational Physics最新文献

A Causality-DeepONet for Causal Responses of Linear Dynamical Systems 线性动力系统因果响应的因果深网

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-06-01 DOI: 10.4208/cicp.oa-2023-0078

Lizuo Liu,Kamaljyoti Nath, Wei Cai

引用次数: 0

JefiPIC: A 3-D Full Electromagnetic Particle-in-Cell Simulator Based on Jefimenko’s Equations on GPU JefiPIC：基于杰菲门科方程的 GPU 3-D 全电磁粒子池模拟器

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-06-01 DOI: 10.4208/cicp.oa-2023-0156

Jian-Nan Chen,Jun-Jie Zhang,Hai-Liang Qiao,Xue-Ming Li, Yong-Tao Zhao

{"title":"JefiPIC: A 3-D Full Electromagnetic Particle-in-Cell Simulator Based on Jefimenko’s Equations on GPU","authors":"Jian-Nan Chen,Jun-Jie Zhang,Hai-Liang Qiao,Xue-Ming Li, Yong-Tao Zhao","doi":"10.4208/cicp.oa-2023-0156","DOIUrl":"https://doi.org/10.4208/cicp.oa-2023-0156","url":null,"abstract":"This paper presents a novel 3-D full electromagnetic particle-in-cell (PIC)\u0000code called JefiPIC, which uses Jefimenko’s equations as the electromagnetic (EM) field\u0000solver through a full-space integration method. Leveraging the power of state-of-the-art graphic processing units (GPUs), we have made the challenging integral task of\u0000PIC simulations achievable. Our proposed code offers several advantages by utilizing the integral method. Firstly, it offers a natural solution for modeling non-neutral\u0000plasmas without the need for pre-processing such as solving Poisson’s equation. Secondly, it eliminates the requirement for designing elaborate boundary layers to absorb\u0000fields and particles. Thirdly, it maintains the stability of the plasma simulation regardless of the time step chosen. Lastly, it does not require strict charge-conservation\u0000particle-to-grid apportionment techniques or electric field divergence amendment algorithms, which are commonly used in finite-difference time-domain (FDTD)-based\u0000PIC simulations. To validate the accuracy and advantages of our code, we compared\u0000the evolutions of particles and fields in different plasma systems simulated by three\u0000other codes. Our results demonstrate that the combination of Jefimenko’s equations\u0000and the PIC method can produce accurate particle distributions and EM fields in open-boundary plasma systems. Additionally, our code is able to accomplish these computations within an acceptable execution time. This study highlights the effectiveness\u0000and efficiency of JefiPIC, showing its potential for advancing plasma simulations.","PeriodicalId":50661,"journal":{"name":"Communications in Computational Physics","volume":"80 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141515596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

A Model-Data Asymptotic-Preserving Neural Network Method Based on Micro-Macro Decomposition for Gray Radiative Transfer Equations 基于微宏分解的灰色辐射传输方程的模型-数据渐近保留神经网络方法

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-06-01 DOI: 10.4208/cicp.oa-2022-0315

Hongyan Li,Song Jiang,Wenjun Sun,Liwei Xu, Guanyu Zhou

{"title":"A Model-Data Asymptotic-Preserving Neural Network Method Based on Micro-Macro Decomposition for Gray Radiative Transfer Equations","authors":"Hongyan Li,Song Jiang,Wenjun Sun,Liwei Xu, Guanyu Zhou","doi":"10.4208/cicp.oa-2022-0315","DOIUrl":"https://doi.org/10.4208/cicp.oa-2022-0315","url":null,"abstract":"We propose a model-data asymptotic-preserving neural network(MD-APNN) method to solve the nonlinear gray radiative transfer equations (GRTEs). The\u0000system is challenging to be simulated with both the traditional numerical schemes\u0000and the vanilla physics-informed neural networks (PINNs) due to the multiscale characteristics. Under the framework of PINNs, we employ a micro-macro decomposition technique to construct a new asymptotic-preserving (AP) loss function, which includes the residual of the governing equations in the micro-macro coupled form, the\u0000initial and boundary conditions with additional diffusion limit information, the conservation laws, and a few labeled data. A convergence analysis is performed for the\u0000proposed method, and a number of numerical examples are presented to illustrate the\u0000efficiency of MD-APNNs, and particularly, the importance of the AP property in the\u0000neural networks for the diffusion dominating problems. The numerical results indicate that MD-APNNs lead to a better performance than APNNs or pure Data-driven\u0000networks in the simulation of the nonlinear non-stationary GRTEs.","PeriodicalId":50661,"journal":{"name":"Communications in Computational Physics","volume":"5 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141502900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

Localization in the Incommensurate Systems: A Plane Wave Study via Effective Potentials 不相称系统中的定位：通过有效势能进行的平面波研究

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.oa-2023-0203

Ting Wang,Yuzhi Zhou, Aihui Zhou

引用次数: 0

Finite-Volume TENO Scheme with a New Cell-Interface Flux Evaluation Strategy for Unstructured Meshes 针对非结构网格采用新的单元界面流量评估策略的有限体积 TENO 方案

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.oa-2023-0289

Tian Liang, Lin Fu

{"title":"Finite-Volume TENO Scheme with a New Cell-Interface Flux Evaluation Strategy for Unstructured Meshes","authors":"Tian Liang, Lin Fu","doi":"10.4208/cicp.oa-2023-0289","DOIUrl":"https://doi.org/10.4208/cicp.oa-2023-0289","url":null,"abstract":"The development of high-order shock-capturing schemes is critical for compressible fluid simulations, in particular for cases where both shock waves and small-scale turbulence structures present. As one of the state-of-the-art high-order numerical\u0000schemes, the family of high-order targeted ENO (TENO) schemes proposed by Fu et\u0000al. [Journal of Computational Physics 305 (2016): 333-359] has been demonstrated to\u0000perform well for compressible gas dynamics on structured meshes and recently extended to unstructured meshes by Ji et al. [Journal of Scientific Computing 92(2022):\u00001-39]. In this paper, with the observation that the TENO scheme not only provides\u0000the high-order reconstructed data at the cell interface but also features the potential to\u0000separate the local flow scales in the wavenumber space, we propose a low-dissipation\u0000finite-volume TENO scheme with a new cell-interface flux evaluation strategy for unstructured meshes. The novelty originates from the fact that the local flow scales are\u0000classified, following a strong scale separation in the reconstruction process, as “very\u0000smooth” or not. When the corresponding large central-biased stencil for the targeted\u0000cell interface is judged to be “very smooth”, a low-dissipation Riemann solver, even\u0000the non-dissipative central flux scheme, is employed for the cell-interface flux computing. Otherwise, a dissipative approximate Riemann solver is employed to avoid spurious oscillations and achieve stable shock-capturing. Such a strategy provides separate\u0000control over the numerical dissipation of the high-order reconstruction process and\u0000the cell-interface flux calculation within a unified framework and leads to a resultant\u0000finite-volume method with extremely low-dissipation properties and good numerical\u0000robustness. Without parameter tuning case by case, a set of canonical benchmark simulations has been conducted to assess the performance of the proposed scheme.","PeriodicalId":50661,"journal":{"name":"Communications in Computational Physics","volume":"191 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140940447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

A Comparative Study of Hydrodynamic Lattice Boltzmann Equation in Phase-Field-Based Multiphase Flow Models 基于相场的多相流模型中的流体力学晶格玻尔兹曼方程比较研究

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.re-2023-0066

Qiang He,Yiqian Cheng,Fengming Hu,Weifeng Huang, Decai Li

{"title":"A Comparative Study of Hydrodynamic Lattice Boltzmann Equation in Phase-Field-Based Multiphase Flow Models","authors":"Qiang He,Yiqian Cheng,Fengming Hu,Weifeng Huang, Decai Li","doi":"10.4208/cicp.re-2023-0066","DOIUrl":"https://doi.org/10.4208/cicp.re-2023-0066","url":null,"abstract":"In recent years, phase-field-based models for multiphase flows have gained\u0000significant popularity, particularly within the lattice Boltzmann (LB) community. These\u0000models typically use two lattice Boltzmann equations (LBEs), one for interface tracking\u0000and the other for solving hydrodynamic properties. However, for the purposes of this\u0000paper, we focus only on the LB model for hydrodynamics. Our goal is to undertake a\u0000comparative investigation into the differences between three classical hydrodynamic\u0000LB models proposed by Lee et al. [1], Liang et al. [2] and Fakhari et al. [3]. The interface-tracking equation used in this study is based on the conservative phase-field model.\u0000We provide a detailed derivation of the governing equations in each model using the\u0000Chapman-Enskog analysis. Additionally, three discretization methods for the interaction forces are introduced, and a modified method for the gradient term is proposed\u0000based on the nonequilibrium distribution method. The accuracy of three LB models\u0000in combination with four discretization methods is examined in this study. Based on\u0000the results, it appears that different combinations of models and methods are appropriate for different types of problems. However, some suggestions for the selection of\u0000hydrodynamic models and discrete methods for the gradient term are provided in this\u0000paper.","PeriodicalId":50661,"journal":{"name":"Communications in Computational Physics","volume":"3 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140886665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

The Positivity-Preserving Finite Volume Coupled with Finite Element Method for the Keller-Segel-Navier-Stokes Model 用于凯勒-西格尔-纳维尔-斯托克斯模型的保正有限体积与有限元方法

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.oa-2023-0309

Ping Zeng, Guanyu Zhou

{"title":"The Positivity-Preserving Finite Volume Coupled with Finite Element Method for the Keller-Segel-Navier-Stokes Model","authors":"Ping Zeng, Guanyu Zhou","doi":"10.4208/cicp.oa-2023-0309","DOIUrl":"https://doi.org/10.4208/cicp.oa-2023-0309","url":null,"abstract":"We propose a linear decoupled positivity-preserving scheme for the\u0000chemotaxis-fluid system, which models the interaction between aerobic bacteria and\u0000the fluid flow surrounding them. This scheme comprises the finite element method\u0000(FEM) for the fluid equations on a regular triangulation and an upwind finite volume\u0000method (FVM) for the chemotaxis system on two types of dual mesh. The discrete\u0000cellular density and chemical concentration are represented as the piecewise constant\u0000functions on the dual mesh. They can also be equivalently expressed as the piecewise linear functions on the triangulation in the sense of mass-lumping. These discrete solutions are obtained by the upwind finite volume approximation satisfying\u0000the laws of positivity preservation and mass conservation. The finite element method\u0000is used to compute the numerical velocity in the triangulation, which is then used\u0000to determine the upwind-style numerical flux in the dual mesh. We analyze the $M$-property of the matrices from the discrete system and prove the well-posedness and\u0000the positivity-preserving property. By using the $L^p$-estimate of the discrete Laplace\u0000operators, semigroup analysis, and induction method, we are able to establish the optimal error estimates for chemical concentration, cellular density, and velocity field in $(l^∞(W^{1,p}), l^∞(L^p),l^∞(W^{1,p}))$-norm. Several numerical examples are presented to verify the theoretical results.","PeriodicalId":50661,"journal":{"name":"Communications in Computational Physics","volume":"308 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140940615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0

A Characteristic Mapping Method for Vlasov-Poisson with Extreme Resolution Properties 具有极限分辨率特性的 Vlasov-Poisson 特征映射方法

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.oa-2024-0012

Philipp Krah,Xi-Yuan Yin,Julius Bergmann,Jean-Christophe Nave, Kai Schneider

引用次数: 0

Geometric Decomposition and Efficient Implementation of High Order Face and Edge Elements 高阶面和边元素的几何分解与高效实现

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.oa-2023-0249

Chunyu Chen,Long Chen,Xuehai Huang, Huayi Wei

引用次数: 0

A Data-Driven Scale-Invariant Weighted Compact Nonlinear Scheme for Hyperbolic Conservation Laws 双曲守恒定律的数据驱动尺度不变加权紧凑非线性方案

IF 3.7 3区物理与天体物理

Communications in Computational Physics Pub Date : 2024-05-01 DOI: 10.4208/cicp.oa-2023-0162

Zixuan Zhang,Yidao Dong,Yuanyang Zou,Hao Zhang, Xiaogang Deng

{"title":"A Data-Driven Scale-Invariant Weighted Compact Nonlinear Scheme for Hyperbolic Conservation Laws","authors":"Zixuan Zhang,Yidao Dong,Yuanyang Zou,Hao Zhang, Xiaogang Deng","doi":"10.4208/cicp.oa-2023-0162","DOIUrl":"https://doi.org/10.4208/cicp.oa-2023-0162","url":null,"abstract":"With continuous developments in various techniques, machine learning is\u0000becoming increasingly viable and promising in the field of fluid mechanics. In this\u0000article, we present a machine learning approach for enhancing the resolution and robustness of the weighted compact nonlinear scheme (WCNS). We employ a neural\u0000network as a weighting function in the WCNS scheme and follow a data-driven approach to train this neural network. Neural networks can learn a new smoothness\u0000measure and calculate a weight function inherently. To facilitate the machine learning task and train with fewer data, we integrate the prior knowledge into the learning\u0000process, such as a Galilean invariant input layer and CNS polynomials. The normalization in the Delta layer (the so-called Delta layer is used to calculate input features)\u0000ensures that the WCNS3-NN schemes achieve a scale-invariant property (Si-property)\u0000with an arbitrary scale of a function, and an essentially non-oscillatory approximation of a discontinuous function (ENO-property). The Si-property and ENO-property\u0000of the data-driven WCNS schemes are validated numerically. Several one- and two-dimensional benchmark examples, including strong shocks and shock-density wave\u0000interactions, are presented to demonstrate the advantages of the proposed method.","PeriodicalId":50661,"journal":{"name":"Communications in Computational Physics","volume":"27 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140941880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

引用次数: 0