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Journal of Computational Physics
基本信息
期刊名称 Journal of Computational Physics
J COMPUT PHYS
期刊ISSN 0021-9991
期刊官方网站 https://www.sciencedirect.com/journal/journal-of-computational-physics
是否OA No
出版商 Academic Press Inc.
出版周期 Monthly
文章处理费 登录后查看
始发年份 1966
年文章数 667
影响因子 3.8(2023)  scijournal影响因子  greensci影响因子
中科院SCI期刊分区
大类学科 小类学科 Top 综述
物理2区 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 计算机:跨学科应用3区
PHYSICS, MATHEMATICAL 物理:数学物理1区
CiteScore
CiteScore排名 CiteScore SJR SNIP
学科 排名 百分位 7.6 1.679 1.678
Mathematics
Applied Mathematics
35/635 94%
Mathematics
Numerical Analysis
6/88 93%
Mathematics
Computational Mathematics
15/189 92%
Mathematics
Modeling and Simulation
27/324 91%
Physics and Astronomy
Physics and Astronomy (miscellaneous)
8/81 90%
补充信息
自引率 13.2%
H-index 213
SCI收录状况 Science Citation Index Expanded
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PubMed Central (PMC) http://www.ncbi.nlm.nih.gov/nlmcatalog?term=0021-9991%5BISSN%5D
投稿指南
期刊投稿网址 https://www.editorialmanager.com/JCOMP
收稿范围
The Journal of Computational Physics (JCP) focuses on the computational aspects of physical problems. JCP encourages original scientific contributions in advanced mathematical and numerical modeling reflecting a combination of concepts, methods and principles which are often interdisciplinary in nature and span several areas of physics, mechanics, applied mathematics, statistics, applied geometry, computer science, chemistry and other scientific disciplines as well: the Journal's editors seek to emphasize methods that cross disciplinary boundaries.

JCP also encourages the submission of papers that develop innovative methods bridging mathematical, physical modeling and algorithmization, e.g. at the frontier between predictive simulation and machine learning. When addressing problems previously covered by other approaches, a comparison should be provided. As for any paper in JCP, the efficacy, robustness, computational complexity, as well as reproducibility should be addressed.

JCP also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract. Review articles providing a survey of particular fields are particularly encouraged. Full text articles have a recommended length of 25 pages for the initial submission. Submissions significantly exceeding this limit will not be considered. In order to estimate the page limit, please use our template.

Published conference papers are welcome provided the submitted manuscript is a significant enhancement of the conference paper with substantial additions.

Reproducibility, that is the ability to reproduce results obtained by others, is a core principle of the scientific method. As the impact of and knowledge discovery enabled by computational science and engineering continues to increase, it is imperative that reproducibility becomes a natural part of these activities. The journal strongly encourages authors to make available all software or data that would allow published results to be reproduced and that every effort is made to include sufficient information in manuscripts to enable this. This should not only include information used for setup but also details on post-processing to recover published results.
收录体裁
投稿指南 https://www.sciencedirect.com/journal/journal-of-computational-physics/publish/guide-for-authors
投稿模板
参考文献格式 https://www.elsevier.com/journals/journal-of-computational-physics/0021-9991/guide-for-authors
编辑信息

Editor in Chief

Rémi Abgrall

University of Zurich

Numerical schemes for hyperbolic problems; Multiphase flows; Interface problems; Hamilton Jacobi;Unstructured meshes; High order schemes

Executive Editors

Nikolaus Adams

Technical University of Munich Chair of Aerodynamics and Fluid mechanics, Garching, Germany

Flow physics; Modelling and simulation of multi-scale flows and complex fluids; Dissemination of fundamental research into applications.

Luis Chacon

Los Alamos National Laboratory, Los Alamos, New Mexico, United States

Computational physics algorithm development and implementation; Computational co-design; Computational and theoretical plasma physics at the macroscopic scale, the kinetic scale, and across these scales (multi-scale); Magnetic reconnection; Magnetic confinement; Inertial confinement.

Feng Xiao

Tokyo Institute of Technology School of Engineering Department of Mechanical Engineering and Science, Meguro-Ku Tokyo, Japan

Computational fluid dynamics; Interfacial multiphase flows; Compressible and incompressible flows; Unified approach; Finite volume method; Unstructured grids; Numerical modeling for geophysical fluid dynamics

Associate Editors

Dinshaw Balsara

University of Notre Dame, Notre Dame, Indiana, United States

Email Dinshaw Balsara

Computational physics; Computational astrophysics; High performance computation

Alvin Bayliss

Northwestern University, Evanston, Illinois, United States

Email Alvin Bayliss

Numerical methods for partial differential equations; Spectral and finite difference methods; Computational wave propagation

Liliana Borcea

University of Michigan Department of Mathematics, Ann Arbor, Michigan, United States

Email Liliana Borcea

Inverse problems, waves in random media, reduced order models

Juan Cheng

Institute of Applied Physics and Computational Mathematics, Beijing, China

Email Juan Cheng

Lagrangian and Arbitrary-Lagrangian-Eulerian (ALE) method for compressible hydrodynamics equations; Numerical method for radiation transfer equations; High order numerical method for hyperbolic conservation laws

Eric Darve

Stanford University, Stanford, California, United States

Email Eric Darve

Pierre Degond

Imperial College London, London, United Kingdom

Email Pierre Degond

Collective dynamics; self-organization; complex systems; biology; Social sciences; Analysis of partial differential equations; Asymptotic analysis; Multiscale numerical methods

Giacomo Dimarco

University of Ferrara Department of Mathematics and Computer Science, Ferrara, Italy

Email Giacomo Dimarco

Kinetic equations; Monte Carlo methods; Multiscale numerical methods; Collective dynamics; Self-Organization; Uncertainty quantification; Computational plasma Physics

Yalchin Efendiev

Texas A&M University Department of Mathematics, College Station, Texas, United States

Email Yalchin Efendiev

Expertise: Numerical analysis, Scientific Computing, Multiscale Simulation, Uncertainty Quantification

Ron Fedkiw

Stanford University, Stanford, California, United States

Email Ron Fedkiw

Solid-fluid coupling; Interfaces; Compressible flow; Incompressible flow

Frederic G. Gibou

University of California Santa Barbara, Santa Barbara, California, United States

Email Frederic G. Gibou

Level set methods; Finite difference/volume approximations of PDEs; Parallel computing

Jan Hesthaven

Federal Polytechnic School of Lausanne, Lausanne, Switzerland

Email Jan Hesthaven

Numerical methods for PDE’s; High-order methods; Absorbing boundary conditions; Reduced order modeling; Wave-problems; Conservation laws; Computational electromagnetics

Gianluca Iaccarino

Stanford University, Stanford, California, United States

Email Gianluca Iaccarino

Computational Fluid Dynamics; Immersed Boundary Methods; Uncertainty Quantification; Turbulence Modeling

Shi Jin

Shanghai Jiao Tong University - Fahua Campus, Shanghai, China

Email Shi Jin

Kinetic equations, hyperbolic conservation laws, quantum dynamics, high frequency waves, uncertainty quantification

George E. Karniadakis

Brown University, Providence, Rhode Island, United States

Email George E. Karniadakis

Stochastic multiscale methods; Uncertainty quantification; Fractional PDEs; Atomistic methods; Spectral and spectral element methods; Machine learning

Barry Koren

University of Technology Eindhoven, Eindhoven, Netherlands

Email Barry Koren

Scientific Computing; Computational Fluid Dynamics

Tony Lelievre

National College of Civil Engineering, Marne La Vallee, France

Email Tony Lelievre

Computational statistical physics, Rare event sampling, Free energy calculation, Metastability, Model Order Reduction, quantum Monte carlo methods, Free surface flow, Multiscale models of complex fluids

Li-Shi Luo

Old Dominion University, Norfolk, Virginia, United States

Email Li-Shi Luo

Kinetic methods for CFD (lattice Boltzmann equation, lattice gas automata, and gas-kinetic scheme); Kinetic theory and non-equilibrium statistical mechanics; non-equilibrium and complex fluids; DNS and LES of turbulence

Karel Matouš

University of Notre Dame, Notre Dame, Indiana, United States

Email Karel Matouš

Predictive computational science and engineering at multiple spatial and temporal scales including multi-physics interactions; Development of advanced numerical methods; High performance parallel computing.

Rajat Mittal

Johns Hopkins University, Baltimore, Maryland, United States

Email Rajat Mittal

Computational fluid dynamics; Biofluid dynamics; Fluid-structure interaction; Flow control; Biomimetics and immersed boundary methods

Parviz Moin

Stanford University, Stanford, California, United States

Email Parviz Moin

Computational fluid dynamics; High fidelity numerical simulation of multi-physics turbulent flows

Jim Morel

Texas A&M University College Station, College Station, Texas, United States

Email Jim Morel

Deterministic, Monte Carlo, and hybrid deterministic/Monte Carlo methods for neutral and charged-particle transport; Radiation-hydrodynamics methods

Jan Nordström

Linköping University, Linköping, Sweden

Email Jan Nordström

Initial boundary value problems; Boundary and interface conditions; High order methods; Well-posedness and stability; Wave and uncertainty propagation

Stanley Osher

University of California Los Angeles, Los Angeles, California, United States

Email Stanley Osher

Nonlinear hyperbolic equations; Level set methods; Image and information processing; Optimization

Jianxian Qiu

Xiamen University, Xiamen, China

Email Jianxian Qiu

Numerical solutions of conservation laws and in general convection dominated problems using: Finite difference essentially non-oscillatory (ENO) methods and weighted ENO (WENO) methods, Finite element discontinuous Galerkin methods (DG), Numerical solution of Hamilton-Jacobi type equations, Computational fluid dynamics, Simulations of multi-phase flow using DG and WENO method

Pierre Sagaut

Laboratory of Mechanics Modelling and Clean Processes, Marseille, France

Email Pierre Sagaut

Guglielmo Scovazzi

Duke University Department of Civil and Environmental Engineering, Durham, North Carolina, United States

Email Guglielmo Scovazzi

Finite element methods, Computational fluid and solid mechanics, Multiphase porous media flows, Computational methods for fluid and solid materials under extreme load conditions, Turbulent flow computations, Instability phenomena

Mikhail Shashkov

Los Alamos National Laboratory, Los Alamos, New Mexico, United States

Email Mikhail Shashkov

Modeling high-speed multi-material compressible flows; Meshing; PDE discretization methods; Interface Reconstruction

Chi-Wang Shu

Brown University, Providence, Rhode Island, United States

Email Chi-Wang Shu

Finite difference; Finite volume and finite element methods; Computational fluid dynamics

Piotr Smolarkiewicz

National Center for Atmospheric Research, Boulder, Colorado, United States

Email Piotr Smolarkiewicz

Scientific computing; Geophysical flows of all scales; Solar dynamo; Non-Newtonian fluids; Dynamics of continuous media

John A. Strain

University of California Berkeley, Berkeley, California, United States

Email John A. Strain

Huazhong Tang

Peking University, Beijing, China

Email Huazhong Tang

Tao Tang

Southern University of Science and Technology, Shenzhen, China

Email Tao Tang

Spectral and high order methods; Adaptive methods; Computational fluid dynamics.

Eli Turkel

Tel Aviv University, Tel Aviv, Israel

Email Eli Turkel

Fast acceleration algorithms for Navier Stokes; High order compact methods for wave equation in general shaped domains; Time Reversal for source and obstacle location; Reading ostraca from first Temple era

Karen Veroy-Grepl

RWTH Aachen University, Aachen, Germany

Email Karen Veroy-Grepl

Numerical methods for partial differential equations, Model order reduction and its use in optimization, Uncertainty quantification and data assimilation, as well as development and application of these methods for problems in medicine, Heat transfer, Solid and fluid mechanics and Multi-scale materials engineering.

Evgenii Vorozhtsov

Institute of Theoretical and Applied Mechanics named after Christianovich SB RAS, Novosibirsk, Russian Federation

Email Evgenii Vorozhtsov

Finite difference and finite volume methods for the Euler equations and for incompressible Navier-Stokes equations; Stability of difference schemes; Numerical grid generation; Immersed boundary methods; Application of computer algebra methods in CFD; postprocessing of the CFD results

Jens Honore Walther

Technical University of Denmark, Kongens(Kgs) Lyngby, Denmark

Email Jens Honore Walther

Dongbin Xiu

OHIO STATE UNIVERSITY, Columbus, Ohio, United States

Email Dongbin Xiu

Uncertainty quantification; Approximation theory; Data assimilation

Nicholas Zabaras

University of Warwick, Coventry, United Kingdom

Email Nicholas Zabaras

Stephane Zaleski

Sorbonne University, Paris, France

Email Stephane Zaleski

Volume-of-Fluid Method; Multiphase Flow; Surface Tension; Interface Tracking; Free Surface

Editors Emeriti

Jeremiah U. Brackbill

John Kileen

Phil L. Roe

Gretar Tryggvason

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