Journal of Computational Physics

JOURNAL OF COMPUTATIONAL PHYSICS AUTHOR INFORMATION PACK TABLE OF CONTENTS XXX <ul style="display: flex;"><li style="flex:1">.</li><li style="flex:1">.</li></ul>•••••• <a href="#1_0">Description </a><a href="#2_0">Audience </a><a href="#2_1">Impact Factor </a><a href="#2_2">Abstracting and Indexing </a><a href="#2_3">Editorial Board </a><a href="#6_0">Guide for Authors </a>p.1 p.2 p.2 p.2 p.2 p.6 ISSN: 0021-9991 DESCRIPTION .Journal of Computational Physics has an open access mirror journal <a href="/goto?url=https://www.journals.elsevier.com/journal-of-computational-physics-x" target="_blank">Journal of Computational Physics: </a><a href="/goto?url=https://www.journals.elsevier.com/journal-of-computational-physics-x" target="_blank">X </a>which has the same aims and scope, editorial board and peer-review process. To submit to Journal of Computational Physics: X visit <a href="/goto?url=https://www.editorialmanager.com/JCPX/default.aspx" target="_blank">https://www.editorialmanage</a><a href="/goto?url=https://www.editorialmanager.com/JCPX/default.aspx" target="_blank">r</a><a href="/goto?url=https://www.editorialmanager.com/JCPX/default.aspx" target="_blank">.</a><a href="/goto?url=https://www.editorialmanager.com/JCPX/default.aspx" target="_blank">com/JCPX/default.aspx</a>. The Journal of Computational Physics 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. The Journal of Computational Physics 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 35 pages. In order to estimate the page limit, please use our <a href="/goto?url=https://www.elsevier.com/__data/promis_misc/JCOMP-template.zip" target="_blank">template</a>. 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 <a href="/goto?url=https://www.elsevier.com/journals/journal-of-computational-physics/0021-9991/guide-for-authors" target="_blank">data </a>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. You can link to data posted in a repository or upload them to <a href="/goto?url=https://www.elsevier.com/authors/author-services/research-data/mendeley-data-for-journals" target="_blank">Mendeley Data</a>. We also encourage authors to submit research elements describing their data to <a href="/goto?url=https://www.journals.elsevier.com/data-in-brief" target="_blank">Data in Brief </a>and software to <a href="/goto?url=https://www.journals.elsevier.com/softwarex/" target="_blank">Software X</a>. Benefits to authors <ul style="display: flex;"><li style="flex:1">AUTHOR INFORMATION PACK 23 Sep 2021 </li><li style="flex:1"><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">www.elsevie</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">r</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">.</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">com/locate/jcp </a></li><li style="flex:1">1</li></ul>We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our <a href="/goto?url=https://www.elsevier.com/authors/author-services" target="_blank">author services</a>. Please see our <a href="/goto?url=https://www.elsevier.com/journals/journal-of-computational-physics/0021-9991/guide-for-authors" target="_blank">Guide for Authors </a>for information on article submission. If you require any further information or help, please visit our <a href="/goto?url=https://service.elsevier.com/app/home/supporthub/publishing/" target="_blank">Support Center </a>AUDIENCE .Experimental and theoretical physicists and chemists working with computational techniques. IMPACT FACTOR .2020: 3.553 © Clarivate Analytics Journal Citation Reports 2021 ABSTRACTING AND INDEXING .Scopus ACM Guide to Computing Literature CompuMath Citation Index Chemical Abstracts Current Contents - Physical, Chemical & Earth Sciences Embase Mathematical Reviews Research Alert Science Abstracts Science Citation Index Zentralblatt MATH INSPEC EDITORIAL BOARD .Editor in Chief Rémi Abgrall, University of Zurich, Zurich Switzerland 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 of America 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 - Suzukakedai Campus, Yokohama, 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 Habib Ammari, ETH Zurich, Zurich, Switzerland Mathematical fundamentals for metamaterials and topological properties at subwavelength scales, Super-resolution imaging, Hybrid medical imaging, Mathematics for bio-inspired imaging Dinshaw Balsara, University of Notre Dame, Notre Dame, Indiana, United States of America Computational physics; Computational astrophysics; High performance computation Alvin Bayliss, Northwestern University, Evanston, Illinois, United States of America <ul style="display: flex;"><li style="flex:1">AUTHOR INFORMATION PACK 23 Sep 2021 </li><li style="flex:1"><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">www.elsevie</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">r</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">.</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">com/locate/jcp </a></li><li style="flex:1">2</li></ul>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 of America Inverse problems, waves in random media, reduced order models Tan Bui-Thanh, The University of Texas at Austin, The Oden Institute for Computational Engineering and Sciences Department of Aerospace Engineering and Engineering Mechanics, Austin, Texas, United States of America Inverse problems, Uncertainty quantification. High-order (DG/HDG) FEM methods, Reduced-order modeling (model order reduction), Model-aware Machine Learning Juan Cheng, Institute of Applied Physics and Computational Mathematics, Beijing, China 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 of America Numerical linear algebra, machine learning for computational engineering, parallel computing, hierarchical solvers (LU, QR factorizations) for large sparse matrices, task-based parallel programming systems Giacomo Dimarco, University of Ferrara Department of Mathematics and Computer Science, Ferrara, Italy Kinetic equations; Monte Carlo methods; Multiscale numerical methods; Collective dynamics; SelfOrganization; Uncertainty quantification; Computational plasma Physics Yalchin Efendiev, Texas A&M University Department of Mathematics, College Station, Texas, United States of America Numerical analysis, Scientific Computing, Multiscale Simulation, Uncertainty Quantification Ron Fedkiw, Stanford University, Stanford, California, United States of America Solid-fluid coupling; Interfaces; Compressible flow; Incompressible flow Frederic G. Gibou, University of California Santa Barbara, Santa Barbara, California, United States of America Level set methods; Finite difference/volume approximations of PDEs; Parallel computing Jan Hesthaven, Federal Polytechnic School of Lausanne, Lausanne, Switzerland 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 of America Computational Fluid Dynamics; Immersed Boundary Methods; Uncertainty Quantification; Turbulence Modeling Shi Jin, Shanghai Jiao Tong University - Fahua Campus, Shanghai, China Kinetic equations, hyperbolic conservation laws, quantum dynamics, high frequency waves, uncertainty quantification George E. Karniadakis, Brown University, Providence, Rhode Island, United States of America Stochastic multiscale methods; Uncertainty quantification; Fractional PDEs; Atomistic methods; Spectral and spectral element methods; Machine learning Barry Koren, Eindhoven University of Technology, Eindhoven, Netherlands Scientific Computing; Computational Fluid Dynamics Tony Lelievre, National College of Civil Engineering, Marne La Vallee, France 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 Lin Lin, University of California Berkeley Department of Mathematics, Berkeley, California, United States of America Electronic structure theory; Quantum many-body physics; Quantum computation Li-Shi Luo, Old Dominion University, Norfolk, Virginia, United States of America 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 of America 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 of America Computational fluid dynamics; Biofluid dynamics; Fluid-structure interaction; Flow control; Biomimetics and immersed boundary methods Parviz Moin, Stanford University, Stanford, California, United States of America Computational fluid dynamics; High fidelity numerical simulation of multi-physics turbulent flows Jim Morel, Texas A&M University, College Station, Texas, United States of America <ul style="display: flex;"><li style="flex:1">AUTHOR INFORMATION PACK 23 Sep 2021 </li><li style="flex:1"><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">www.elsevie</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">r</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">.</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">com/locate/jcp </a></li><li style="flex:1">3</li></ul>Deterministic, Monte Carlo, and hybrid deterministic/Monte Carlo methods for neutral and chargedparticle transport; Radiation-hydrodynamics methods Jan Nordström, Linköping University, Linköping, Sweden Initial boundary value problems; Boundary and interface conditions; High order methods; Wellposedness and stability; Wave and uncertainty propagation Stanley Osher, University of California Los Angeles, Los Angeles, California, United States of America Nonlinear hyperbolic equations; Level set methods; Image and information processing; Optimization Jianxian Qiu, Xiamen University, Xiamen, China 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 Mario Ricchiuto, French Institute for Research in Computer Science and Automation, Rocquencourt, France Numerical methods for partial differential equations, Hyperbolic balance laws, Unstructured grids, Residual distribution and finite element methods, Immersed and embedded methods, Free surface flows, Geophysical flows, Compressible flows Pierre Sagaut, Laboratory of Mechanics Modelling and Clean Processes, Marseille, France Guglielmo Scovazzi, Duke University Department of Civil and Environmental Engineering, Durham, North Carolina, United States of America 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 of America Modeling high-speed multi-material compressible flows; Meshing; PDE discretization methods; Interface Reconstruction Chi-Wang Shu, Brown University, Providence, Rhode Island, United States of America Finite difference; Finite volume and finite element methods; Computational fluid dynamics Piotr Smolarkiewicz, National Center for Atmospheric Research, Boulder, Colorado, United States of America Scientific computing; Geophysical flows of all scales; Solar dynamo; Non-Newtonian fluids; Dynamics of continuous media Eric Sonnendrücker, Max-Planck-Institute of Plasma Physics, Garching, Germany Computational plasma physics; modelling and simulation of magnetic confinement fusion; numerical methods for kinetic, gyrokinetic and fluid plasma models; geometric and structure preserving numerical methods Mark Sussman, Florida State University, Tallahassee, Florida, United States of America Multiphase Flows, Deforming boundary problems, Adaptive Mesh Refinement, Transport processes on Fluidic Interfaces, High performance Computing Huazhong Tang, Peking University, Beijing, China Tao Tang, Southern University of Science and Technology, Shenzhen, China Spectral and high order methods; Adaptive methods; Computational fluid dynamics. Chrysoula Tsogka, University of California Merced, Merced, California, United States of America wave propagation, random media, coherent interferometry, imaging, time reversal Eli Turkel, Tel Aviv University, Tel Aviv, Israel 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 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. Jens Honore Walther, Technical University of Denmark, Kgs Lyngby, Denmark Dongbin Xiu, The Ohio State University, Columbus, Ohio, United States of America Uncertainty quantification; Approximation theory; Data assimilation Nicholas Zabaras, University of Notre Dame, Notre Dame, Indiana, United States of America Artificial Intelligence, Scientific Computing, Machine Learning, Deep Learning, Inverse Problems, Data Science, Computational Mathematics, Computational Statistics Stephane Zaleski, Sorbonne University, Paris, France Volume-of-Fluid Method; Multiphase Flow; Surface Tension; Interface Tracking; Free Surface Editors Emeriti Jeremiah U. Brackbill John Kileen <ul style="display: flex;"><li style="flex:1">AUTHOR INFORMATION PACK 23 Sep 2021 </li><li style="flex:1"><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">www.elsevie</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">r</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">.</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">com/locate/jcp </a></li><li style="flex:1">4</li></ul>Phil L. Roe Gretar Tryggvason <ul style="display: flex;"><li style="flex:1">AUTHOR INFORMATION PACK 23 Sep 2021 </li><li style="flex:1"><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">www.elsevie</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">r</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">.</a><a href="/goto?url=http://www.elsevier.com/locate/jcp" target="_blank">com/locate/jcp </a></li><li style="flex:1">5</li></ul>GUIDE FOR AUTHORS .Your Paper Your Way We now differentiate between the requirements for new and revised submissions. You may choose to submit your manuscript as a single Word or PDF file to be used in the refereeing process. Only when your paper is at the revision stage, will you be requested to put your paper in to a 'correct format' for acceptance and provide the items required for the publication of your article. To find out more, please visit the Preparation section below. INTRODUCTION Journal of Computational Physics has an open access mirror journal, Journal of Computational Physics: X. Submission checklist You can use this list to carry out a final check of your submission before you send it to the journal for review. Please check the relevant section in this Guide for Authors for more details. Ensure that the following items are present: One author has been designated as the corresponding author with contact details: • E-mail address • Full postal address All necessary files have been uploaded: Manuscript: • Include keywords • All figures (include relevant captions) • All tables (including titles, description, footnotes) • Ensure all figure and table citations in the text match the files provided • Indicate clearly if color should be used for any figures in print Graphical Abstracts / Highlights files (where applicable) Supplemental files (where applicable) Further considerations • Manuscript has been 'spell checked' and 'grammar checked' • All references mentioned in the Reference List are cited in the text, and vice versa • Permission has been obtained for use of copyrighted material from other sources (including the Internet) • A competing interests statement is provided, even if the authors have no competing interests to declare • Journal policies detailed in this guide have been reviewed • Referee suggestions and contact details provided, based on journal requirements For further information, visit our <a href="/goto?url=https://service.elsevier.com/app/home/supporthub/publishing/" target="_blank">Support Center</a>. BEFORE YOU BEGIN Ethics in publishing Please see our information on <a href="/goto?url=https://www.elsevier.com/about/policies/publishing-ethics#Authors" target="_blank">Ethics in publishing</a>. Declaration of competing interest All authors must disclose any financial and personal relationships with other people or organizations that could inappropriately influence (bias) their work. Examples of potential conflicts of interest include employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/ registrations, and grants or other funding. Authors should complete the declaration of competing interest statement using <a href="/goto?url=https://www.elsevier.com/declaration-of-competing-interests" target="_blank">this template </a>and upload to the submission system at the Attach/Upload Files step. Note: Please do not convert the .docx template to another file type. Author signatures

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